Ressearch Full Notes

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UNIT-1 RESERACH METHODOLOGY

MEANING:

It is a scientific and systematic search for pertinent (correct) information on a specific topic.

It is an art of scientific investigation. It is the search for knowledge through objectives and

systematic approach concerning generalization and formulation of a theory.

DEFINITION:

According to advance learners dictionary of current English, research methodology is a

careful investigation or inquiry especially through search for new facts in any branch of

knowledge.

According to Redman & Mery, It is a systemized effort to gain knowledge.

According to Clifford woody, research comprises defining and redefining problems;

formulating hypothesis or suggest solutions; collecting, organising and evaluating data; making

deduction and reaching conclusion and at last carefully testing the conclusion to determine

whether they fit the formulating hypothesis

According to D.sleinger and M.stephenson, in the encyclopaedia of social sciences defined

research as, the manipulation of things, concepts or symbols for the purpose of generalising to

extend, correct or verify knowledge, whether that knowledge aids in construction of theory or in

the practice of an art

OBJECTIVES OF RESEARCH:

1. To gain familiarity with the phenomenon or to achieve new in size into it.

2. To portray accurately the characteristics of a particular individual, situation or a group.

3. To determine the frequency with which something occurs or with it is associated with

something else.

4. To test a hypothesis of a casual relationship between variables.

IMPORTANCE OF RESEARCH:

1. It gives the research the necessary training in gathering material and arranging them;participation in the field work when required; training in techniques for the collection of

data appropriate to particular problem; in the use of statistics, questionnaires, control


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experimentation and in recording evidence; sorting it out and in recording evidence; sorting

it out and interpreting it.

2. The knowledge of research methodology provides good training especially to the new

research worker and enables him to do better.

3. Helps him to develop disciplined thinking to observe the field objectively.

4. Knowledge of how to do research will inculcate the ability to evaluate and use researchresults with reasonable confidence.

5. Knowledge of research methodology provides tools to look at things in life objectively.

6. Help the consumer of research results to evaluate them and enables him to take rational

decisions.

SIGNIFICANCE OF RESEARCH:

1. Research inculcates scientific and inductive thinking and it promotes the

development of logical habits of thinking and organisation.

2. The role of research in several field of applied economics whether related to business

or to the economy as a whole has greatly increased in modern times.

3. Research provides basis for nearly all government policies in our economic system.

4. Research has its special significance in solving various operations and planning

problems of business and industry market research.

5. Research is equally important for social scientist in the studying social relationship

and in seeking answers to various social problems. It provides the intellectual

satisfaction of knowing practical solutions.

6. Thus, research provides guidelines for solving different business, governmental and

social problems

TYPES OF RESEARCH:

1. Descriptive Vs Analytical

2. Applied Vs Fundamental

3. Quantitative Vs Qualitative

4. Conceptual Vs Empirical (experiment)

5. Other types of research

a) One time research

b) Longitudinal research


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c) Laboratory research (Field setting research or Simulation research)

d) Clinical (or) diagnostic research

e) Exploratory research

f) Historical research

g) Conclusion oriented research

h) Decision oriental research.

I i) DescriptiveDescriptive research includes survey and fact finding enquiries of different

kinds. It is used mostly in social science and business research. It is otherwise called as Export

facts Research. This research describes the state of affairs as it exist at present. The main

characteristics of the variables. The researcher reports only what has happened or what of all kind.

This methods of research aims at answering what and why of the current stateof some system. Eg.

This type of research is used to measure such items like : Frequency of shopping, b) attrition rate,

c) Preferences of people, d) level of job satisfaction.

Analytical ResearchThe research has to use facts information already available and analyze

these information make a critical evaluation.

Applied Vs Fundamental :-

i) Applied Research Applied research aims at finding a solution for an immediate

problem facing a society. Eg an industry or business organization. The aim of applied

research is to discover a solution for some pressing practical problem. This research is

aimed at certain conclusions facing a concrete social or business problem. Eg:- Researech

to identify social, economic or business or political trends that may affect a particular

organization.

ii) Basic/ fundamental research / pure research gathering knowledge for knowledge

sake. It means the investigation of problems to further and develop existing knowledge.

This research is mainly concerned with generalization and formulation of theories Eg.

Investigation into natural phenomena, mathematics, physics or astronomy, study on the

behavior of individuals to make some generalization about their social learning, memory

pattern and intelligence level.

III).Quantitive and Qualities:


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i) Quanititative research : This research is based on the measurement of quantity or amount. It

is applicable to phomena relating to or involving quality. This research aims at discovering

the underlying motives and desires using indepth interviews for the purpose. Motivation

research is an important type of qualitative research. Eg : - Word ariciaf test, sentence

completion test, story completion test, projective techniques. This research is specially

important in the behavioral sciences where the aim is to discover the underlying motives,interests, personality and attitudes of human beings.

IV)Conceptual vs. Empirical :

i) Conceptual research : This research is related to some abstract ideas or theory. It is

generally used by philosophers and thinkers to develop new concept or to re interpret the

existing ones.

ii)Empirical Research (Experimental) This research mainly relies on experience or

observation alone without due regard for system and theory. The research should collect

enough data to prove or disprove his hypothesis. It is considered that evidence gathered

through experiment or empirical study provides the most powerful support possible for the

given hypothesis.

IV) Other types of research :-a) One time researchresearch is confined to a single time period.

b) Longitudinal researchresearch is carried on over several time periods.

c) Laboratory research (Field setting research or simulation research)the emphasis

in laboratory research is on controlling certain variables in such a way as to

observe the relationship between two or more variables.

d) Clinical (or) diagnostic researchThis research follows case study method or in-

depth approaches to reach the basic casual relationship. It takes only a few

samples and studies the phenomenon in depth and observes the effect.

e) Exploratory research - the objective of this research is the development of

hypothesis rather than their testing

f) Historical ResearchIt utilizes historical sources like documents, literature etc to

study or ideas of the past.

Involved in defining a problem


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1.Statement of the problem in a general way.

2.Understanding the nature of the problem.

3.Surveying the available literature.

4.Developing the ideas through discussions.

5.Rephrasing the research problem.

6.Technical terms with special meanings used in the statement of the problem should be clearly

defined.

7.Basic assumptions relating to the research problem should be clearly stated..

8.The suitability of time period,sources of data available must also been considered.

9.Scope and limitations of the study must be mentioned explicitly

RESEARCH DESIGN:

Research design is the arrangement of conditions for collection and analysis of data in a

manner that aims combine relevance to the research purpose with economy in procedure. It is the

conceptual structure within which research is conducted. It is the blueprint for the collection ,

measurement and analysis of data.

TYPES OF RESEAECH DESIGN:

Sampling design-deals with method of selecting items for the observation design- it

relates to the conditions under which observation are to be made.

Statistical design-it concern with how manage to be observed and how information and

data gathered are to be analyzed.

Operational design-deals with the techniques by which the procedures specified can be

carried out.

FEATURE OF GOOD RESEARCH DESIGN:


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Its a plan,that specifies the sources and type of information relevant to the research

problem.

It is a strategy specifying which approach will be used for gathering and analyzing the

data . it also includes time and cost.

NEED FOR RESEARCH DESIGN:

For smooth sailing if conduct of the various research operations.

Making research efficient.

For yielding maximum information with minimum expenditure of effort,time and

money.

It stands for advance planning of the method to be adopted for collecting the data.

Help the researcher to organize his ideas where by it will be possible for him to look forflaws and inadequacies.

IMPORTANT CONCEPT RELATING TO RESEARCH DESIGN:

i. Dependent and independent variables:

Dependentif one variable depends upon another consequence of other variable, it is

called dependent.

Independentit variable that is antecedent to the dependent variable is called

independent variable.

Eg.height depends upon age.height-dependent variable,age-independent variable.

ii. Extraneous variable-independent variable that are not related to the purpose of the study

but may affect the dependent variable are called extraneous variable.

iii. Controlcontrol is used to minimize the effect of extraneous independent variables. Inexperimental research,the term control is used to refer to restrain experimental condition.

iv. Confounded relationshipwhen the dependent variable is not free from the influence of

extraneous variable,the relationship between dependent and independent variable is said

to be confounded by an extraneous variable.

v. Research hypothesisit is a predictive statement that relates an independent variable to a

dependent variable.

vi. Experimental and non-experimental hypothesis research-when the purpose of a research

is to test a research hypothesis,it is termed as hypothesis testing.


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Experimental hypothesis research-it is the research in which the independent

variable is manipulated.

Non-experimental hypothesis researchit is the research in which the independent

variable is not manipulated.

What is Ethics in Research & Why is it Important?

When most people think of ethics (or morals), they think of rules for distinguishing between right

and wrong, such as the Golden Rule ("Do unto others as you would have them do unto you"), a

code of professional conduct like the Hippocratic Oath ("First of all, do no harm"), a religious

creed like the Ten Commandments ("Thou Shalt not kill..."), or a wise aphorisms like the sayings

of Confucius. This is the most common way of defining "ethics": norms for conduct that

distinguish between acceptable and unacceptable behavior.

Most people learn ethical norms at home, at school, in church, or in other social settings. Although

most people acquire their sense of right and wrong during childhood, moral development occurs

throughout life and human beings pass through different stages of growth as they mature. Ethical

norms are so ubiquitous that one might be tempted to regard them as simple commonsense. On the

other hand, if morality were nothing more than commonsense, then why are there so many ethical

disputes and issues in our society?

One plausible explanation of these disagreements is that all people recognize some common

ethical norms but different individuals interpret, apply, and balance these norms in different ways

in light of their own values and life experiences.

Most societies also have legal rules that govern behavior, but ethical norms tend to be broader and

more informal than laws. Although most societies use laws to enforce widely accepted moral

standards and ethical and legal rules use similar concepts, it is important to remember that ethics

and law are not the same. An action may be legal but unethical or illegal but ethical. We can also

use ethical concepts and principles to criticize, evaluate, propose, or interpret laws. Indeed, in the

last century, many social reformers urged citizens to disobey laws in order to protest what they

regarded as immoral or unjust laws. Peaceful civil disobedience is an ethical way of expressing

political viewpoints.


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Another way of defining 'ethics' focuses on the disciplines that study standards of conduct, such

as philosophy, theology, law, psychology, or sociology. For example, a "medical ethicist" is

someone who studies ethical standards in medicine. One may also define ethics as a method,

procedure, or perspective for deciding how to act and for analyzing complex problems and

issues. For instance, in considering a complex issue like global warming, one may take an

economic, ecological, political, or ethical perspective on the problem. While an economist mightexamine the cost and benefits of various policies related to global warming, an environmental

ethicist could examine the ethical values and principles at stake.

Many different disciplines, institutions, and professions have norms for behavior that suit their

particular aims and goals. These norms also help members of the discipline to coordinate their

actions or activities and to establish the public's trust of the discipline. For instance, ethical normsgovern conduct in medicine, law, engineering, and business. Ethical norms also serve the aims or

goals of research and apply to people who conduct scientific research or other scholarly or

creative activities. There is even a specialized discipline, research ethics, which studies these

norms.

There are several reasons why it is important to adhere to ethical norms in research. First,

norms promote the aims of research, such as knowledge, truth, and avoidance of error. For

example, prohibitions against fabricating, falsifying, or misrepresenting research data promote the

truth and avoid error. Second, since research often involves a great deal of cooperation and

coordination among many different people in different disciplines and institutions, ethical

standards promote the values that are essential to collaborative work, such as trust,

accountability, mutual respect, and fairness. For example, many ethical norms in research, such as

guidelines for authorship, copyright and patenting policies, data sharing policies, and

confidentiality rules in peer review, are designed to protect intellectual property interests while

encouraging collaboration.

Most researchers want to receive credit for their contributions and do not want to have their ideas

stolen or disclosed prematurely. Third, many of the ethical norms help to ensure that researchers

can be held accountable to the public. For instance, federal policies on research misconduct,

conflicts of interest, the human subjects protections, and animal care and use are necessary in

order to make sure that researchers who are funded by public money can be held accountable to

the public. Fourth, ethical norms in research also help to build public support for research.


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People more likely to fund research project if they can trust the quality and integrity of research.

Finally, many of the norms of research promote a variety of other important moral and social

values, such as social responsibility, human rights, animal welfare, compliance with the law, and

health and safety.

Ethical lapses in research can significantly harm human and animal subjects, students, and thepublic. For example, a researcher who fabricates data in a clinical trial may harm or even kill

patients, and a researcher who fails to abide by regulations and guidelines relating to radiation or

biological safety may jeopardize his health and safety or the health and safety of staff and

students.

Codes and Policies for Research Ethics

Given the importance of ethics for the conduct of research, it should come as no surprise that

many different professional associations, government agencies, and universities have adopted

specific codes, rules, and policies relating to research ethics. Many government agencies, such as

the National Institutes of Health (NIH), the National Science Foundation (NSF), the Food and

Drug Administration (FDA), the Environmental Protection Agency (EPA), and the US

Department of Agriculture (USDA) have ethics rules for funded researchers. Other influential

research ethics policies include the Uniform Requirements for Manuscripts Submitted to

Biomedical Journals (International Committee of Medical Journal Editors), the Chemist's Code of

Conduct (American Chemical Society), Code of Ethics (American Society for Clinical Laboratory

Science) Ethical Principles of Psychologists (American Psychological Association), Statements on

Ethics and Professional Responsibility (American Anthropological Association), Statement on

Professional Ethics (American Association of University Professors), the Nuremberg Code and

the Declaration of Helsinki (World Medical Association).

The following is a rough and general summary of some ethical principals that various codes

address*:

Honesty

Strive for honesty in all scientific communications. Honestly report data, results, methods and

procedures, and publication status. Do not fabricate, falsify, or misrepresent data. Do not deceive

colleagues, granting agencies, or the public.


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Objectivity

Strive to avoid bias in experimental design, data analysis, data interpretation, peer review,

personnel decisions, grant writing, expert testimony, and other aspects of research where

objectivity is expected or required. Avoid or minimize bias or self-deception. Disclose personal or

financial interests that may affect research.

Integrity

Keep your promises and agreements; act with sincerity; strive for consistency of thought and

action.

Carefulness

Avoid careless errors and negligence; carefully and critically examine your own work and the

work of your peers. Keep good records of research activities, such as data collection, research

design, and correspondence with agencies or journals.

Openness

Share data, results, ideas, tools, resources. Be open to criticism and new ideas.

Respect for Intellectual Property

Honor patents, copyrights, and other forms of intellectual property. Do not use unpublished data,

methods, or results without permission. Give credit where credit is due. Give proper

acknowledgement or credit for all contributions to research. Never plagiarize.

Confidentiality


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Protect confidential communications, such as papers or grants submitted for publication, personnel

records, trade or military secrets, and patient records.

Responsible Publication

Publish in order to advance research and scholarship, not to advance just your own career. Avoidwasteful and duplicative publication.

Responsible Mentoring

Help to educate, mentor, and advise students. Promote their welfare and allow them to make their

own decisions.

Respect for colleagues

Respect your colleagues and treat them fairly.

Social Responsibility

Strive to promote social good and prevent or mitigate social harms through research, public

education, and advocacy.

Non-Discrimination

Avoid discrimination against colleagues or students on the basis of sex, race, ethnicity, or other

factors that are not related to their scientific competence and integrity.

Competence


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Maintain and improve your own professional competence and expertise through lifelong education

and learning; take steps to promote competence in science as a whole.

Legality

Know and obey relevant laws and institutional and governmental policies.

Animal Care

Show proper respect and care for animals when using them in research. Do not conduct

unnecessary or poorly designed animal experiments.

Human Subjects Protection

When conducting research on human subjects, minimize harms and risks and maximize benefits;

respect human dignity, privacy, and autonomy; take special precautions with vulnerable

populations; and strive to distribute the benefits and burdens of research fairly.

* Adapted from Shamoo A and Resnik D. 2009.Responsible Conduct of Research, 2nd ed. (New

York: Oxford University Press).

Ethical Decision Making in Research

Although codes, policies, and principals are very important and useful, like any set of rules, they

do not cover every situation, they often conflict, and they require considerable interpretation. It is

therefore important for researchers to learn how to interpret, assess, and apply various research

rules and how to make decisions and to act in various situations. The vast majority of decisionsinvolve the straightforward application of ethical rules. For example, consider the following case,

Case 1:


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The research protocol for a study of a drug on hypertension requires the administration of the drug

at different doses to 50 laboratory mice, with chemical and behavioral tests to determine toxic

effects. Tom has almost finished the experiment for Dr. Q. He has only 5 mice left to test.

However, he really wants to finish his work in time to go to Florida on spring break with his

friends, who are leaving tonight. He has injected the drug in all 50 mice but has not completed allof the tests. He therefore decides to extrapolate from the 45 completed results to produce the 5

additional results.

Many different research ethics policies would hold that Tom has acted unethically by fabricating

data. If this study were sponsored by a federal agency, such as the NIH, his actions would

constitute a form ofresearch misconduct, which the government defines as "fabrication,falsification, or plagiarism" (or FFP). Actions that nearly all researchers classify as unethical are

viewed as misconduct. It is important to remember, however, that misconduct occurs only when

researchers intend to deceive: honest errors related to sloppiness, poor record keeping,

miscalculations, bias, self-deception, and even negligence do not constitute misconduct.

Also, reasonable disagreements about research methods, procedures, and interpretations do not

constitute research misconduct.

Unit-2

SAMPLING DESIGN


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STEPS IN SAMPLING DESIGN:

i. Types of universe

ii. Sampling unit

iii. Source list

iv. Size of sample

v. Parameters of interest

vi. Budgetary constraint

vii. Sampling procedure.

CRITERIA OF SELECTING A SAMPLING PROCEDURE:

COST

Cost of data collection Cost of an incorrect inference

Causes of incorrect inference

a.System bias inappropriate sampling frame

Defective measuring device

Indeterminacy principle Nature bias in data

reporting.

b.sampling errors.

SAMPLING DESIGN:

It is a definite plan for obtaining sample from a given population. It refers to the technique

or the procedure the researcher would adopt in selecting items for the sample. It is determined

before data collection.

Basic concepts concering testing of hypothesis:-

a)Null hypothesis and alternate hypothesis(h0-Null hypothesis,h1-Alternate)


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Non-random or Non-probability

1. Purposive sample /Deliberate sampling

2. Quota sampling

3. Convenient sampling

b)The level of significance (5%)

c) Decision rule (or) Test of hypothesis.

d) Type I and II error.

4) Preparing the Research Design

Exploration Descriptive Diagnosis Experimentation

5) Determining sample design:-

Universe /Population

Census inquiry

Sample

Sample, size

Sampling

Sample Design

Types of sampling method

Random or probability

1. Simple random sample

2. Systematic sample

3. Stratified random sample

4. Multi stage random sample

5. Cluser sample/Area sample

6. Sequential sample /sample in installments

7. Replicated or interpenetrating sample


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6) Collecting the data:-

Primary data

Experiment Survey

Ways of data collection through survey

I. Observation

II. Personal Interview

III. Telephone interview

IV. Mailing of questionnaries

V. Schedules

7) Execution of the Project

Execution in a systematic manner and in time

8) Analysis of data:-

Coding

Editing

Tabulation

Analysis using stat tools

9) HypothesisTesting:-

Chi-square test, E-test, f-test

10) Generalizations of Interpretation:-

Arriving certain generalization

Interpretating data based on some theory.

11) Preparation of the report:-

1. Layout of the Report

Preliminary Maintest Endmatter

2. Report should be consises and objective.


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3. Charts x Illustrations.

4. Confidence limits must be mentioned.


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I. The purpose of the research should d be clearly defined and common concepts should be

used.

II. The research procedure should be described in sufficient detail.

III. Procedural design of the research should be carefully planned to yield objective results.

IV. Analysis of the data should be sufficiently adequate to reveal its significance and methods

of analysis used should be appropriate.V. Conclusion should be confined to the data of the research.

VI. Greater confidence in research is required.

Problems encountered by researches in India:-

I. Lack of scientific training in the research methodology.

II. There is insufficient interaction between the university research department and business

units Government departments and other research institutions

III. Business units in our country do not have confidence that the information obtained by them

will not be misused.

IV. Research studies overlapping the under taken quite often.

V. Many of out libraries are not able to get the copies of old and new acts/rules, report and

other government publications in time.

Defining the research problem:

To define a problem correctly, a researcher must know what a problem is. A research problem

refers to some difficulty which a researchers experiences in the content of either a theoretical or

practical situation and wants to obtain a solution for the same.

Components of research problem:

I. There must be an individual or a group which has some difficulty or the problem.

II. There must be some objectives to be attained.

III. There must be some alternatives for obtaining the objectives.

IV. There must remain some doubt in the mind of the researcher with regard to the selection of

alternatives.

V. There must be some environment to which the difficulty pertains.

Need for defining the problem.

Problem must be unambiguously defined will help to discriminate relevant data from the data. It is

a pre requistic for any study.


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Types of samples design

The first step in developing any sample design is define the set of objects called universe. It can

be finite or infinite.

Sampling unit- A decision has to be taken concerning a sampling unit before selecting sample. It

may be geographical (state, village, district etc) or construction unit (house, flats etc) or social unit(clubs, family, schools) or an individual) socialistit is also known as sampling frame from

which sample is to be drawn. It contains name of all items of a universe. It source list is not

available , researcher has to prepare it.

4) Size of the sample (or) sample sizeit refers to the number of items to be selected from the

universe to confute the sample . Sample size should be optimum.

5) Parameters of interest - in determining the sample design, one must consider the question of

specific population parameters which are of great interest.

Budgetary constraint- cost consideration have major impact upon decisions relating to sample size

and sample.

procedure- finally, the researcher about the technique to the used in selecting the sample.

Criteria of selecting a sampling procedure

Two costs are involved in sampling

I. cost of data collection

II. cost of incorrect inferences.

the reasons for the cause of incorrect inferences are:

1. Systematic bias

2. Sampling error

1. Systematic bias:-

It results from errors in the sampling procedure and it is the result of one or more of the

following factors

Inappropriate sampling frame.

Defective measuring device.

Indeterminacy principle.

Natural bios in data reporting


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2. sampling error:-

It is the random variations in the sample estimates around the tree population parameters.

Sampling error decreases with increase in sample size.

Characteristics of good sample design:

it must result in truly representative sample it must be the one that results in small errors.

It must be visible in the context of funds for the research study.

Measurement & scaling techniques

Measurement

Measurement scales

a) Nominal scales

b) Ordinal scales

c) Interval scales

d) Ratio scale

Measurement

It is the process of mapping aspects of a domain on to other aspects of a range according to same

rule of correspondence.

Types of measurement scales

I)Nominal scale

It is simply a system of assigning number or symbols to events in order to label them. It provides

convenient pay of keeping track of people, objects and it is the lowest and least powerful level of

nominal scale (eg) assigning numbers to basket ball in order to identity them.

ii) Ordinal Scale:

The lowest level of the ordered scale used places events in order but there is no equal in the

scale. It permits ranking of items from highest to lowest. (eg):- Ranking of students in a class.

iii) Interval scale:


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It provides more powerful measurement than ordinal scales since it incorporates the concept

of equality of interval. Intervals are established by some rule. Eg: Age1520 yrs etc.

iv) Ratio scale:

It have an absolute or true zero of measurement. It facilitates a kind of comparison in case

of an interval scale. Eg: 1:4 Item2 is 4 times better than item1.

Sources of Error in Measurement:

Measurement should be precise and unambiguous in an ideal research study. The following

are the possible sources of error in measurement.

i) Respondent:

At times the respondents may be reluctant to express strong negative feeling or he may leave

little knowledge or he may not admit his ignorance.

ii) Situation:

Any condition which places a strain on interview can have serious effects on the interviewer

respondent rapport.

iii. MEASURES :

Interviewer can distort responses by rewarding or recording a questions , his

behaviour, style and looks may encourage or discourage replies from the respondent.

iv. INSTRUMENT :

Error may arise because of the defective measuring instrument. Eg:- complex

word, ambiguous meaning, poor printing , inadequate space for replies, poor sampling etc.

SCALING :-

ScalingSale classifications

a) Subject orientation

b) Responses form


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c) Degree of subjectivity

d) Scale properties

e) Number of dimension

f) Scale construction techniques

Scaling:-

It describes the procedures of assigning numbers to various degree of opinion, attitude and

other concepts.

Definition:-

Scale is a continuum consisting of highest point and the lowest point along with several

intermediate points between these two extreme points. scaling is the procedure for assignment of

numbers to a property of objects in ordern to impart some of the characteristics of number to the

properties in question .

Scale classification:

a.subject orientation:-

scale may be designed to measure characteristics of the respondent completes it or to

judge the object which is presented to the respondent.

b. Rsponse from:-

scales are classified into

i. Categorical scale(rating scale)

ii. Comparative scale(ranking scale)

c.Dgree of subjectivity:-

with this basis, the scale data may be based on whether we measure subjective

personal preferences or non preference judgements.

d.Scale properties:-

on this basis, scales are classified into nominal , ordinal, interval, ratio scale.

e.Number of dimensions:-

on this basis, scales are classified into unidimensional scales, multidimensional

scales.


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f.Scale construction techniques:-

the following are the approaches for scale construction techniques.

i. Arbitrary approach.

ii. Consensus approach.

iii. Item analyse approach.iv. Cumulative scales approach.

v. Factor scales approach.

i.Arbitrary approach:-

the scales is developed on adhoc basis. It is mostly widely used approach.

ii. Consensus approach.

Here, panel of judges evaluate the items chosen for inclusion in the research.

iii. Item analyse approach.

Under this approach, a number of individual items are develop[ped into a test which is

given to a group of respondents.

iv.Cumulative scales approach.

Scales are chjopsen on the basis of their confirmation of to some ranking of items

with ascending or descending order.

V.factor scales approach.

This is constructed on the basis of inter correlation of items which indicates that a

common factor accounts for the relationship between items.

IMPORTANT SCALING TECHNIQUES:-

1.RATING SCALE:-

Rating scales involves quantitative description of a limited number of ascepts of a

thing or of traits. When rating scales are used in an object in absolute term against some specified

criteria are judged.

Eg:- 1. likedislike (2 point scaling tech)

2. above avg-avg-below avg (3 point scaling)


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3. Like very muchlike some whatneturaldislike some whatdislike very much (5

point)

4. excellentgood avg below avgpoor.

a.GRAPHICAL RATING SCALE (3-7points)

It is quite simple and ti is commonly used in practice. Under it various points are

usually put along the line to form a continuum. The rates indicates his rating by simple making a

mark at the appropriate point on a line.

Eg:- how do you like the product ?

o Like very much.

o Like some what.

o Neutral

o Dislike some what.o Dislike very much.

b.ITEMISED RATING SCALER:-

It present series of statements from which a respondents select one as best

reflecting his evaluation .

Eg:- suppose you wish inquire how well does a worker get along with his fellow workers.

o He is almost always involved in some friction with the fellow workers.

o He is often at odds with one or more of his fellow workers.

o He sometime get involved in friction .

o He infrequently becomes involved in friction with workers.

o He almost never gets involved in friction with fellow workers.

2.RANKING SCALE:-

Under ranking scales, relative judgement against other similar objects are made.


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Approaches of Ranking scale:

a) Method of paired comparison:

Under it, the respondent can express his attitude by making a choice between two objects.

Eg: Choice between a new flavor of soft drinks and established brand of a drink

The number of judgements required in the paired comparison is given by the formula:

N = n (n-1) NNo of judgement

2

nNo of stimulior objects to be judged

b) Methods of Rank order:

Under this method, the respondents are asked to rank their choices. This method is

easier and faster than the method of paired comparison.

SCALE CONSTRUCTION TECHNIQUES:

Name of the scale Construction

Approach

Name of the scale developed

1. Arbitrary Approach

2. Consensus scale approach

3. Item Analysis Approach

4. Cumulative scales approach

5. Factor scales approach

Arbitrary scale

Differential scale (Thurston)

Summated scales (Likert scale)

Cumulative scales (Guttmans

scalogram)

Factor scale (Osgoods semanticdifferential scale, Multi-

dimensional scale)


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1. Arbitrary Scale:

Arbitrary scales are developed on adhoe basis.

The researcher first collects few statements or items which the believes are unambiguous

and appropriate a given topic.

2. Differential Scales: (Thurstone scale)

This scale have been developed using the on sensus scale approach

Panel of judges evaluate the topic is relevant or not

Under this approach the selection of items made by a panel of judges who evaluate the

items in terms of whether they are relevant to the topic or not

3. Summated Scales: (Likert scale)

Summated scales are developed by utilizing the tem analysis approach where in a particular

item is evaluates on the basis of how well it disuiminates between those persons whose total

score is high and those whose score is low.

Summated scales consist of a no of statement which express either a favorable or

unfavorable attitude towards the given object. Each response is given a numerical score

indicating its favorableness or unfavorableness and the scores are totaled to measure the

respondents attitude.

Eg: When ask to express opinion where one consider his job quite pleasant, the respondent may

respond in any one of the following ways.

*Strongly Agree *Agree *Undecided

*Disagree *Strongly *Disagree

4. Cumulative scales:

Lewis Guttmans scale gram consists of series of statement to which a respondent expresses

his agreement or disagreement. The special feature of this type of scale is that statements in

its form a cumulative series.

5. Factor Scale:

Factor scales are developed through factor analysis on the basis of inter correlation of items

which indicate that a common factor accounts for the relationship between items. A

important factor scale based on factor analysis is

Semantic differential scaling


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Multi dimensional scaling

Unit -3

Processing and Analysis of Data

Processing Operations:

a) Editing

b) Coding Acc to Attributes

c) Classification

d) Tabulation According to class Intervals

Chi-Square Test:

It is the most important test among other tests developed by statisticians.

It is symbolically written as x2

It is a statistical measure used for comparing a variance to a theoretical variance

It is non-parametric test used to determine if categorical datas source dependency or the

two classifications are independent It is a technique used to do the following:-

to test the goodness of fit


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to test the significance of association between two attributes

to test the homogeneity or the significance of population variance

i) As a test of goodness of fit

Chi square test enables to see how well does the assume theoretical distribution fit to the

observed data. If the calculated value of Chi Square is less than the table value at a certainlevel of significance, the fit is considered to be good one otherwise is it not considered to be

good one.

ii) As a test of independence.

Chi square test enables to explain whether or not the two attributes are associated.

Formula :-

X2 = E (OijEij) 2

Eij

Where,

OijObserved frequency of the cell in the i row and j column

EijExpected frequency of the cell in the i row and j column

I = row, j = column

Degree of freedom = (C1) (R1) where

C = Column (No. Of columns)

R = No. Of Rows.

CONDITIONS FOR THE APPLICATION OF CHI SQUARE TEST

Observations recorded and used are collected on a random basis.

All the items in the sample must be independent.

No group should contain very few items must also be reasonably large.


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The constraints must be linear.

Hypothesis Testing :-

Note :- Refer step 3 of the Research process.

Procedure for hypothesis Testing:-

Step 1)

Making a Formal statementFormulate null hypothesis (Ho) and alternate hypothesis (Ha). It

also indicates whether we should use one-tailed test or two-tailed test.

Step 2)

Selecting a significance levelGenerally 5% of 1% level is adopted

Factors that affect the level of significance:

a) Magnitude of the difference between sample means.

b) Size of the samplesc) Variability of measurements with in samples

d) Whether hypothesis is directional or non-directional

Step 3)

Deciding the distribution to usewhether to use normal distribution or t-distribution.

Step 4)

Selecting a random sample and computing a appropriate value.

Step 5)

Calculation of the probability-by using the formula for each text.

Step 6)


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Comparing the probability. If the calculated probability is greater than the value,we reject null

hypothesis otherwise we accept the null hypothesis.

Statistics in research:-

1. StatisticsDescriptive Statistics inferential statistics

(sampling statistics)

2. Important measures of statistics

Measures of Measures of Measures of Measures of other measure Central Tend

dispersion Asymmetry relationship

(statistical averages) (skweness)

Arithmetaic Mean Range *measures of *Karl pearson`s

Median Mean deviation skweness based coff.of correlati

Mode Standard deviation on mean & mode *

Geometric (mean (GM) Coefficient of *quartiles

Harmonic Mean (HM) standard deviation *methods of

Coefficient of moments

Varation *kurtosis

Chi Square Test problems:

The following table give the number of screws declared fit and also unfit by three inspectors X, Yx Z.


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Test the hypothesis that the proportion of screws declared unfit by the three inspectors are the

same.-

X NO. OF

SCREWS

Y

Z TOTAL

INSPECTOR 50/ X 47 /Y 56/ Z EF

FIT SCREWS 50 47 56 153 153 x 55

180

UNFIT

SCREWS

5 14 8 27 153 x 61

180

TOTAL 55 61 64 180

Table value X21df= 3.84, X22df= 5.99.

1. Null Hypothesis (Ho)Proportiion of screws declared unfit by three inspectors are same.

Alternate Hypothesis (Ha)Proportion of screws declared unfit by the three inspectors are

different.

2. Level of significance = 5% (or) 0.05.

3. X2 = E (OE) Degree of freedom = (C- 1) (R- 1)

E (DF) = (31 ) (21)

= 2

Expected Frequency (E) 2df = 5.99

X Y Z

Fit screws 46.75 51.85 54.4

Unfit screws 8.25 9.15 9.6

Table Value

O E (OE) (OE)2

(O- E)2

E

50 46.75 3.25 10.56 0.226

47 51.85 -4.85 20.52 0.454


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56 54.4 1.6 2.56 0.047

5 8.25 -3.25 10.56 1.28

14 9.15 4.85 23.52 2.570

8 9.6 -1.6 2.56 0.267

4.844

Since the calculated value of X2 (4.844) less than table value (5.99), the null hypothesis is

accepted. Hence, the proportion of screws declared unfit by three inspectors are the same.

Measures of central Tendency (Statistical Averages) :--

i) Mean is defined as the value which we get by dividing the total of the values of various

given items is a series by the total number of items.

Mean (X) = Exi = X1 + X2 + ...... + Xn where,

N n

E denotes summation, Xi denotes value of ith items, n denotes total number of item

ii) MedianIt is the value of the middle term of series when it is arranged in ascending or

descending order of magnitude.Median (M) value of n + 1 th item.

2

iii) Mode (z)It is the most commonly or frequently occurring value in a series.

iv) Geometric Mean (GM)It is defined as the nth route of the product of the values of n items

in a given series.

GM = n x i

= n X 1 x X2 x X3 ........ Xn Where n = no of items

Xi = ith value of the value X, conventional product notation.

Harmonic Mean (HM)It is defined as the reciprocal of the average of reciprocals of the values

of the items in a series.

HM = E Rec Xi


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N

= Rec. Rec.X1 + Rec X2 + ..... + Recxn where

n

RecReciprocal, Xi - value of the variable X,

NTotal number of items.

Measures of Dispersion :-

i) Range It is the difference between the values of the extreme items of a series.

Range = Highest value of - Lowest value of

an item is series an item in series

ii) Mean DeviationIt is the average of difference of the values of items from same averages

of the series.

i) Mean deviation mean (Si) = XiX where, Ssymbol for mean deviation

n

ii) Mean deviation from median (Sm) = Xim- XArthimetic mean

n mmedian

iii)Mean deviation from mode (Sz) = XiZ zmode

n

iii)Standard DeviationIt is defined as the square root of the averages of squares of deviation.

(Standard Deviation) = (XiX ) 2

N


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Correlation :

Correlation is used to determine the relationship between two or more variables and to what extent

they are related to each other.

i) Charles Spearmens (rank correlation) =

Co-efficient of correlation

r s = 1 - 6di2

n (n

2

-1)

where, di = difference between ranks of ith pair of two variables, n = no. of pairs of observation.

It is a technique of determining the degree of correlation between two variables where ranks are

given to variables.

ii) Karl Pearsons coefficient of correlation (simple correlation) :-

it is the most widely used method of measuring the degree of relationship between two variables.

r = (XiX) (yiy)

n. x x - y

Simple Regression Analysis:-

Regression is the determination of statistical relationship between two or more variables.

Regression equation of Y on X.

Y = a + bx

Yestimated value of Y for a value of X.

4. MARKETING RESEARCH

Xstandard deviation X


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DefinitionAmerican marketing association defines marketing research as a, systemetic

gathering, recording and analysing of data about problems relating to marketing of goods

and services.

Zalgtman and Burger defines marketing research as, the field which involves the

diagnosis of information needs and selection of relevant interrelated variables about which

valid and reliable information is gathered, recorded and analysed.

EVOLVING TECHNIQUES IN MERKETING RESEAECH:

S.NO DECADE TECHNIQUES

1. Prior to 1910 First hand observations and

elementary service.

2. 1910 to 1920 Sales analysis, operating cost

analysis.

3. 1920 to 1930 Questionnaire construction

survey technique.

4. 1930 to 1940 Quota sampling simple

correlation analysis. Store

auditing techniques.

5. 1940 to 1950 Probability sampling

regression methods. Advanced

statistical inference. Consumer

and store panels.

6. 1950 to 1960 Motivation research operation

research multiple regression

and attitude measuring

instruments.


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7. 1960 to 1970 Factor analysis and

discriminate analysis

mathematical models.

Bayesian statistical analysis

and decision theory, scaling

theory, computer data

processing and analysis.

Marketing simulation.

Information storage and

retrieval.

8. 1970 to 1980 Non-parametric multi-

dimensional scaling.Econometric models

comprehensive marketing

models. Test marketing

laboratories. Multi- attributes

models.

9. 1980 onwards Advanced mathematical

models.

COMPANIES EMPLOYING MARKETING RESEARCH CONSULTANT FOR

CONDUCTING RESEARCH FOR MARKETING PROBLEMS:

i. Private sector companies - Tesco, Telco, Hindustan lever, DCM, vim co, escorts, plasco,

Pfizer.

ii. Public sector companiesBHEL, oil, STC, MMTC, SAIL, Coal India.

NATURE OF MARKETING RESEARCH:

i. MR as an economic resource.


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ii. MR as a system of authority.

iii. As a function of marketing management.

iv. As a team work or group effort.

v. As an art or a profession.

vi. As an interdisciplinary process.

1. MR as an economic resource:Production is a door to success but marketing is the key which turns the lock. Peter

Ducker says business is the creation of customers. So, to manage a business is to manage its

marketing function effectively. For making marketing management effective, we have to gather

and analyses information on environmental forces (customers, suppliers, distributors etc..,). This

information on environment can be made available to the organization through a sound marketing

information system. Hence, the entrepreneur has to develop and improve marketing research of his

organization to facilitate decision making process. With the help of proper information, he can co-ordinate the activities of marketing department with other functional departments. Thus, MR is the

most active and critical managerial resource.

2. MR as a system of authority:A system is an assemblage of interacting and interrelated elements. So as to form a

complex whole to accomplish certain common objectives. Authority is legal right to command

others to act or not to act in a described manner. Marketing research is also a system having

activities such as collecting, recording, tabulating, analyzing and interpreting the data. Each of

these activities is performed by some specialists. Thus, he possesses an authority to guide or direct

workers under his command supervision. Thus, MR functions as a system of authority in an

organization.

3. MR as a function of marketing management:


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Marketing management functions like planning, implementing and control retailing to

marketing mix are performed in an effective manner only when information on marketing mix

elements (product, price, promotion, place) and environmental factors (customer need &

activities, competitor strategies, dealers demand, suppliers policy etc) are made available to

marketing executives operating at various levels of management. thus, marketing research is a

very important function of marketing management.

4. MR as teamwork or a group work:MR is performed by a group or team of executives carrying out different functional activities.

An integrated effort is needed from all the MR executives who are doing different jobs.

5. MR as an art or science:Art is a style of performing a particular activity. It does not have its own techniques and

depends for this on others disciplines. Science is a systematic body of knowledge pertaining to an

area of study and some general truth explaining the past events or phenomena. MR is either an art

(studying a consumer behavior) or science (conducting market research for introducing a new

product.

6.MR as a profession:

A profession refers to any occupation by which a person earns his livelihood. It requires

specialized skills and training in a particular field. A professional should have the following

criterias:

a) Knowledge

b) Competent application

c) Social responsibility

d) Self control

e) Community action

MC.FARLAND has identified the following characteristics of management as a profession:

a) existence of knowledge

b) acquiring knowledge

c) existing of representative body

d) ethical standard

e) reasonable remuneration

7.MR as a interdisciplinary process:

Research is conducted in all the disciplines of physical and social sciences in almost the

similar manner as in the field of marketing.

SCOPE OF MARKETING RESEARCH:


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MR activities are purely classified into 7 categories:

i) product and service research

ii) market research

iii) promotion research

iv) distribution research

v) pricing research

vi) corporate responsibility researchvii) miscellaneous research

TYPES OF RESEARCH RESEARCH ACTIVITES COVERED

1) RESEARCH ON MARKET a) Analyzing market potentials for existing

products and estimating demand for the new

product.

b) Sales forecasting.

c) Characteristics of product marketing.

d) Analyzing sales potentials.

e) Studying trend in markets.

2) RESEARCH ON PRODUCT

AND SERVICES

a) Customer acceptances of proposed new

product .

b) Comparative study of competitive products.

c) Determining new uses of present products.

d) Market testing of proposed products.

e) Studying customers dissatisfaction with

products.

f) Product line research.g) Packaging and designing research.

3) RESEARCH ON

PROMOTION

a) Evaluating and advertising effectively.

b) Analyzing advertising and selling practices.

c) Selecting advertising media

d) Motivational studies.

e) Establishing sales territories.

f) Evaluating present and proposed sales

methods.

g) Studying competitive pricing.

h) Analyzing salesmans effectiveness.

i) Establishing sales quotas.


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4) RESEARCH ON

DISTRIBUTION

a) Location and design of distribution center.

b) Handling and package of merchandising.

c) Cost analysis of transportations method.

d) Dealer supply and storage requirement.

5) RESEARCH IN PRICING a) Demand elasticitys.

b) Perceived prices.

c) Cost analysis.

d) Margin analysis.

6) CORPORATE

RESPONSIABILITY

RESEARCH

a) Anti-pollution.

b) Consumerism

c) Attitude of consumers to package design and

promotional strategy.

d) Attitudes to company adding to social cost.

Eg : union carbide methol gas leakage tragedyat Bhopal.

7) MISCELLANEOUS

RESEARCH

a) Research on diversification.

b) Satisfaction and motivation of sales personnel

c) Governmental action and attitudes to

corporate sectors.

d) International marketing study

e) Ecological impact studies.f) Long range forecasting.

Importance of MR:

Business executives are in causingdepending upon marketing research. They want quick and

pertinent (stable) accurate information flow from the internal and external environment of firm to

facilitate the process of decision making. The increasing importance of MR is based on the

following three trends:-

Shift from local to national and international market.

Transition from consumer needs to consumer wants.

Shift from price competition to non-price competition.

Role of MR:

MR plays a vital role of making available the right information at the right time in the right place

and to the right person for using decision making. Thus it facilitates, decision making concerningmarketing mix element. All firms have to use marketing information, if they want to be successful

in the business operation. Following are the major uses of marketing information:-

Consumer goods manufacturers-


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They use MR product ideas to new package design, measure effectiveness of their

promotional efforts are determine brand, product and company image. E.g.: Hindustan

lever, godrej, TAMCO, fractor, gramble.

Industrial goods manufacturers-

They use MR to achieve a certain extent to determine market and sales potential by carrying

out customer order, territory and product line analysis. They use MR for forecasting their

production. E.g.:- kirloskar, Voltar, Telco.

Market intermedies-

Agent merchants, brokers, wholesalers, retailers, jobbers, salesman, distributors, dealers use

MR to gather information through their experience in handling a last number of customers.

Consumer services-

Banks, insur5ance companies, gas agencies, transport companies, Tourism Company,

hospitals use MR to know more information on consumer attitudes.

Media & business services-

Ad agencies, consultancy firms, TV, newspaper, magazine, radio etc are the heavy users of

marketing research. E.g.: massive, Thomson associates, TATA consultancy etc are engaged

in MR.

FARMERS-

Farmers have also realised the importance of MR as they are interested to get better revenue

for their agricultural products. They use MR to know where they should sell and what time

and price for their products like grains, rice, wheat, vegetables, seeds, sugarcane etc. Rural markets-

Business people who operate in rural market also require MR to a greater extent. They

intent to have information on consumer needs, wants and perceptions in rural market. E.g.:

Mahindra & Mahindra excorts etc.

Non-business users-

Government agencies, educational organisation, management association, management

institutions have also started using MR information. They use MR for gathering and

analyzing pertinent market information. So that, they can improve their knowledge and skillin their respective areas. All India management association, AICT,etc.

Government organisation-

Information collected by certain organisation like economics & statistical department is of

immense help to the government in formulating their policies and plans.

Miscellaneous users-

Governmental & non-governmental MR agencies, conduct research on feasibility of new

projects forecasting the market demand, competitors activities, consumer behaviour,

environmental, economic, political and technological changes, public policy changes,marketing mix elements changes.

USES/ADVANTAGES/SIGNIFICANCE OF MR:-


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It helps in obtaining sufficient background information where absolutely nothing is known

about the problem area or product field in question.

It helps in concept identification and its exploration.

It is used to identify relevant and salient behavioural patterns, beliefs, opinions, attitudes,

motivation etc.

MR is useful in establishing priorities among categories of behaviour and psychological

variables like beliefs, opinion and attitudes.

Quantitative MR is generally helpful in defining problem areas fully and formulating

hypothesis for further investigation and qualification.

MR is useful during a preliminary screening process in order to reduce a large number of

possible contenders to a smaller number of probable ones.

MR also helps in obtaining large amount of data about belief, attitudes etc as data input for

multi-variate analysis studies.

It is also used in conducting post research investigation or postmodern to amplify (explore)

and explain certain points emerging from some major study without having to repeat these

on a large scale.

It is used in piloting questionnaires to test comprehension word forms, memory factor etc.

Qualitative MR is used where we cannot discover in a simple straight forward manner like

direct questioning, why people behave as they do because the field of enquiry is personal

and embarrassing in some way.

LIMITATIONS/DISADVANTAGES:-

MR uses the techniques of science but in itself is not an exact science. Therefore the result

obtained is not very accurate as compared to physical and chemical sciences.

MR is carried out in open market place where so many variables are acting on the research

settings.

MR is carried out on consumers, dealers, wholesalers, retailers who are human beings. So,

the customer and the respondents start behaving artificially when they know their attitudes,

opinions, beliefs etc are being studied. This aspect of human behaviour distorts the MR

results.

Subjectivity is the main limitation of MR. it is very difficult to verify the research results.

MR projects generally take longer time period than other projects. Hence, time gap affects

the successful implementation of research results.

Research intentionally or unintentionally is biasing research results in MR.

The lack of appropriate training to researchers leads to misinterpretation of questions to be

asked for data collection.

Some research sponsoring agencies are instructing the research to come out with particular

type of solutions to a particular type of problem.

Many research executives are not very clear about the research problem and its objectives.

In India, research is taken as the time wasting and resource wasting activity. Therefore, MR

doesnt get its pure resource allocation in the organizations.


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Researchers are not much motivated to make use of computers for analyzing the research

results.

MARKETING INFORMATION SYSTEM (MIS)

It is a set of procedures and methods for the planned and regular collection and dissemination

of information for uses in marketing decision making.

Definition:

MIS is defined as the structure introducing complex of persons. Machines and procedures

designed to generate and orderly flow of pertinent information collected from both intra and extra

firm sources, for use as the basis for decision making in specific responsibility areas of marketing

management.

Difference between marketing research and marketing information systems:

Sales control research / Techniques in sales forecasting:

The different techniques used for forecasting the sales of new product are as follows:

1) Survey of buyers intention

2) Delphi method

3) Sales force polling

4) Time series analysis and trend projection

1) Survey of buyers intention:The most direct method of estimating demand in short run is to ask customers what they

are planning to buy for the forecasting year. This method is most useful when bulk of the sales is

made to industrial buyers. When shortages are expected customers may argugate their

requirements. This method is not very useful in the case of household customers due to several

reasons like customers inability to foresee their choice, Irregular nature of buying intentions, large

number of household buyers etc.

2) Delphi Method: this method, a group of experts are questioned repeatedly until the responses,

coverage along a single line. Each expert is given the opportunity to react to the views of other

experts. This method saves time and money but it can be successful when experts are

knowledgeable and objective in their approach.

3) Sales Force Polling:In this method, salesman are asked to estimate expected sales in their respective

territories. Salesman are closer to the customers and therefore they are likely to have the


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most intimate feel of the market. The estimates of individual salesman are consolidated to

find out the total estimated sales. This method is simple and based on first hand knowledge

of salesman but this method is subjective and suitable for short term forecasting.

Process Of Marketing Research:

Marketing research is a scientific and systematic exercise consisting of the following steps:

i. Problem Formulation.

ii. Decision on fact gathering procedure.

iii. Data collection.

iv. Marketing sample.

v. Date evaluation.

vi. Interpreting the data.

vii. Report generation.

a. Executive report

b. Technical report

c. Data report

d. Popular report (or) persuasive report.

i. Problem Formulation:The precise definition of the problem helps in determining the techniques to be used, the

extent of information to be collected and one should clearly state the problem. Marketing elements

of the problem should be isolated and identified in precise terms.

ii. Decision on fact gathering procedure: (planning the research design)It consist of the following steps:

a) Establishing the facts that are available at present and

The additional facts required are:

Determining the reliable data.

Setting and organization for the collection of additional information required.

DATA COLLECTION:


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This is the method of obtaining information from a sample of respondents. When the

available data are insufficient, fresh data have to be collected.Usually, survey techniques are used

for gathering information.

MARKETING SAMPLE:

A sample is the small group taken from the total group. Sampling is essential to substantiate

and interpret the data.

DATA EVALUATION:

Locating the source and collecting information is only a part of the job. For the same set of

facts, different interpreters will draw different conclusions depending upon their individual view

points and their interest.

INTERPRETINGTHEDATA:

Correct interpretation of data makes the research meaningful and purposeful. The best factstudy would become useless by wrong or improper interpretation of facts. Technical competence,

broad understanding, intimate knowledge of the problem at hand are some of the prerequisites for

a correct interpretation of the data.

REPORT GENERATION:

The final step in MR is summarizing the result and making a report. The finding and

recommendation are also included.

TYPES OF REPORT:

Executive Report-It is meant for an executive to carry out the plan as quickly as possible.

Technical Report-This report will contain the statement of the problem; research methodology

etc.The purpose of this report is to collect and present necessary technical information.

Data ReportThis report doesnt contain any interpretations. It merely presents the finding in

tables and charts.

Popular Report-It is non-technical and hence, of no value in commercial field. Narration of an

incident is a kind of popular report.

SALES CONTROL RESEARCH/TECHNIQUES IN SALES FORECASTING:

Time series analysis and trend projection:

A long standing firm has considerable data on sales pertaining to several years.

Such data when arranged peonlogically (alphabet order) becomes time series. The trend of the


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time series can be projected to estimate future sales. This method is simple and inexpensive but it

is based on the assumption that past rate of change with continue in future economic indicators of

sales like income level of people, regression equations and executive judgment can also be used to

forecast sale

UNIT-5

INTERPRETATION AND REPORT WRITING

Interpretation-Interpretation refers to task of drawing inferences (results) from the collected facts

after an analytical and/or experimental study. It is a search for border meaning of research

findings

Need for interpretationTechniques for interpretation

Ire cautions in interpretations

REPORT WRITING:

1) Different steps in writing a report:

Logical analysis of the subject matter.

Preparation of final outline.

Preparation of rough draftRewriting and polishing of the rough draft.

Preparation of final bibliography.

Writing the final draft.

2) Layout of the research report:

It consists of three components:

Preliminary pagesMain text

End matter

3) Types of report:

There are two types:

Technical Report

Popular Report

4) Mechanics of writing a research report.

THE ROLE OF COMPUTER IN RESEARCH


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Computer have always assisted to solve the problems faced by the mankind since the time of

invention, the size of the computers have drastically reduced from that of a room to that can be

accommodated in a human palm. The word computer means something which computes or a

machine for performing calculations automatically, but, today computer means not merely

a calculator. It does vast variety of jobs with tremendous speed and efficiency. Today people usecomputers in almost every walk of life. Computers have become a subject of study at schools

electronic computers have now become an indispensable part of every profession: so do research.

COMPUTER IN RESEARCH PROCESS

There are five major phases of the research process. They are:

1. Conceptual phase

2. Design and planning phase

3. Empirical phase

4. Analytic phase and

5. Dissemination phase

1. Role of Computer in Conceptual Phase

the conceptual phase consists of formulation of research problem, review of literature, theoretical

frame work and formulation of hypothesis.

Role of computers in literature review: computers help for searching the literatures (for review of

literature) and bibliographic reference stored in the electronic database of the world wide webs. It

can thus be used for storing relevant published articles to the retrieved whenever needed. This has

the advantage over searching the literatures in the form of books, journals and other news letters atthe libraries which consume considerable amount of time and effort.

2. Role of Computers in Design and Planning Phase

Design and planning phase consist of research design, population, research variables, sampling

plan, reviewing research plan and pilot study

Role of Computers for Sample Size Calculation:Several softwares are available to calculate

the sample size required for a proposed study. The standard deviation of the data from the pilotstudy is required for the sample size calculation.

3. Role of computers in empirical phase

Empirical phase consist of collecting and preparing the data for analysis:


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Data Storage: The data obtained from the subjects are stored in computes are word files or excel

spread sheets. This has the advantage of making necessary corrections or editing the whole layout

of the tables if needed, which is impossible or time consuming incase of writing in papers. Thus,

computers help in data entry, data editing, data management including follow up actions etc.

computers also allow for greater flexibility in recording the data while they are collected as well

as grater ease during the analysis of these data.In research studies, the preparation and inputting data is the most labor-intensive and time

consuming aspect of the work. Typically the data will be initially recorded on a questionnaire or

record for suitable for its acceptance by the computer. To do this the researcher in conjunction

with the statistician and the programmer, will convert the data into Microsoft word file or excel

spreadsheet. These spread sheets can be directlyopened with statistical softwares for analysis

4. Role of Computers in Data AnalysisThis phase consist of statistical analysis of the data and interpretation of results.

Data analysis: many softwares are now available to perform the mathematical part of the research

process i.e. the calculations using various statistical methods.Softwares like SPSS, NCSS-PASS,

STATA and SYSAT are some of the widely used. They can be like calculating the sample size for

a proposed study, hypothesis testing and calculating the power of the study. Familiarity with any

one package will suffice to carry out the most intricate statistical analysis.Computers are useful

not only for statistical analysis, but also to monitor the accuracy and completeness of the data as

they are collected.

5. Role of Computer in Research Dissemination

This phase is the publication of the research study.

ResearchPublishing: the research article is typed in word format and converted to portable data

format (PDF) and stored and/or published in the world wide web.

gretlis an example of anopen sourcestatistical package

ADMBa software suite for non-linear statistical modeling based on C++ which uses

automatic differentiation.

Bayesian Filtering Library

Chronuxfor neurobiological time series data

DAPA free replacement for SAS

ELKIasoftware frameworkfor development ofdata miningalgorithms inJava.

Fityknonlinear regression software (GUI and command line)
http://en.wikipedia.org/wiki/Gretlhttp://en.wikipedia.org/wiki/Gretlhttp://en.wikipedia.org/wiki/Open_sourcehttp://en.wikipedia.org/wiki/Open_sourcehttp://en.wikipedia.org/wiki/Open_sourcehttp://en.wikipedia.org/wiki/ADMBhttp://en.wikipedia.org/wiki/ADMBhttp://en.wikipedia.org/wiki/Bayesian_Filtering_Libraryhttp://en.wikipedia.org/wiki/Bayesian_Filtering_Libraryhttp://en.wikipedia.org/wiki/Chronuxhttp://en.wikipedia.org/wiki/Chronuxhttp://en.wikipedia.org/wiki/DAP_(software)http://en.wikipedia.org/wiki/DAP_(software)http://en.wikipedia.org/wiki/Environment_for_DeveLoping_KDD-Applications_Supported_by_Index-Structureshttp://en.wikipedia.org/wiki/Environment_for_DeveLoping_KDD-Applications_Supported_by_Index-Structureshttp://en.wikipedia.org/wiki/Software_frameworkhttp://en.wikipedia.org/wiki/Software_frameworkhttp://en.wikipedia.org/wiki/Software_frameworkhttp://en.wikipedia.org/wiki/Data_mininghttp://en.wikipedia.org/wiki/Data_mininghttp://en.wikipedia.org/wiki/Data_mininghttp://en.wikipedia.org/wiki/Java_(programming_language)http://en.wikipedia.org/wiki/Java_(programming_language)http://en.wikipedia.org/wiki/Java_(programming_language)http://en.wikipedia.org/wiki/Fitykhttp://en.wikipedia.org/wiki/Fitykhttp://en.wikipedia.org/wiki/File:Gretl_screenshot.pnghttp://en.wikipedia.org/wiki/Fitykhttp://en.wikipedia.org/wiki/Java_(programming_language)http://en.wikipedia.org/wiki/Data_mininghttp://en.wikipedia.org/wiki/Software_frameworkhttp://en.wikipedia.org/wiki/Environment_for_DeveLoping_KDD-Applications_Supported_by_Index-Structureshttp://en.wikipedia.org/wiki/DAP_(software)http://en.wikipedia.org/wiki/Chronuxhttp://en.wikipedia.org/wiki/Bayesian_Filtering_Libraryhttp://en.wikipedia.org/wiki/ADMBhttp://en.wikipedia.org/wiki/Open_sourcehttp://en.wikipedia.org/wiki/Gretl


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gretlgnu regression, econometrics and time-series Library

JAGSJust another Gibbs sampler (JAGS) is a program for analysis of Bayesian

hierarchical models using Markov Chain Monte Carlo (MCMC) developed by Martyn

Plummer. It is similar to WinBUGS.

JHepWorkJava-based statistical analysis framework for scientists and engineers. It

includes an advanced IDE andJythonshell.

JMulTi

Octaveprogramming language (very similar to Matlab) with statistical features

Mondrian (software)- data analysis tool using interactive statistical graphics with a link to

R.

OpenBUGS

OpenEpiA web-based, open source, operating-independent series of programs for use in

epidemiology and statistics based on JavaScript and HTML

OpenMxA package forStructural equation modelingrunning inR.

Orange, amachine learningandbioinformaticssoftware

Ploticussoftware for generating a variety of graphs from raw data

PSPPA free software replacement for SPSS

RAfreeimplementation of theSlanguage.

R CommanderGUI interface forR

RapidMiner, amachine learningtoolbox

Rattle GUIGUI interface forR

Scilabuses GPL compatibleCeCILLlicense

SciPy(aPythonlibrary for scientific computing) contains the stats sub-package which is

partly based on the venerable |STAT(a.k.a PipeStat, formerly UNIX|STAT) software

Shogun, anopen sourceLarge ScaleMachine Learningtoolbox that provides several SVM

(Support Vector Machine) implementations (like libSVM, SVMlight) under a common

framework and interfaces to Octave, Matlab, Python, R

SimfitSimulation, curve fitting, statistics, and plotting

SOCR

SOFA Statisticsa desktop GUI program focused on ease of use, learn as you go, and

beautiful output.

Statistical LabR-based and focusing on educational purposes

Wekais also a suite ofmachine learningsoftware written at theUniversity of Waikato.
http://en.wikipedia.org/wiki/Gretlhttp://en.wikipedia.org/wiki/Gretlhttp://en.wikipedia.org/wiki/Just_another_Gibbs_samplerhttp://en.wikipedia.org/wiki/Just_another_Gibbs_samplerhttp://en.wikipedia.org/wiki/JHepWorkhttp://en.wikipedia.org/wiki/JHepWorkhttp://en.wikipedia.org/wiki/Jythonhttp://en.wikipedia.org/wiki/Jythonhttp://en.wikipedia.org/wiki/Jythonhttp://en.wikipedia.org/wiki/JMulTihttp://en.wikipedia.org/wiki/JMulTihttp://en.wikipedia.org/wiki/GNU_Octavehttp://en.wikipedia.org/wiki/GNU_Octavehttp://en.wikipedia.org/wiki/Mondrian_(software)http://en.wikipedia.org/wiki/Mondrian_(software)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/OpenBUGShttp://en.wikipedia.org/wiki/OpenBUGShttp://en.wikipedia.org/wiki/OpenEpihttp://en.wikipedia.org/wiki/OpenEpihttp://en.wikipedia.org/wiki/OpenMxhttp://en.wikipedia.org/wiki/OpenMxhttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/Orange_(software)http://en.wikipedia.org/wiki/Orange_(software)http://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Ploticushttp://en.wikipedia.org/wiki/Ploticushttp://en.wikipedia.org/wiki/PSPPhttp://en.wikipedia.org/wiki/PSPPhttp://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/Free_softwarehttp://en.wikipedia.org/wiki/Free_softwarehttp://en.wikipedia.org/wiki/Free_softwarehttp://en.wikipedia.org/wiki/S_(programming_language)http://en.wikipedia.org/wiki/S_(programming_language)http://en.wikipedia.org/wiki/S_(programming_language)http://en.wikipedia.org/wiki/R_Commanderhttp://en.wikipedia.org/wiki/R_Commanderhttp://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/RapidMinerhttp://en.wikipedia.org/wiki/RapidMinerhttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Rattle_GUIhttp://en.wikipedia.org/wiki/Rattle_GUIhttp://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/Scilabhttp://en.wikipedia.org/wiki/Scilabhttp://en.wikipedia.org/wiki/CeCILLhttp://en.wikipedia.org/wiki/CeCILLhttp://en.wikipedia.org/wiki/CeCILLhttp://en.wikipedia.org/wiki/SciPyhttp://en.wikipedia.org/wiki/SciPyhttp://en.wikipedia.org/wiki/Python_(programming_language)http://en.wikipedia.org/wiki/Python_(programming_language)http://en.wikipedia.org/wiki/Python_(programming_language)http://en.wikipedia.org/wiki/Shogun_(toolbox)http://en.wikipedia.org/wiki/Shogun_(toolbox)http://en.wikipedia.org/wiki/Open_sourcehttp://en.wikipedia.org/wiki/Open_sourcehttp://en.wikipedia.org/wiki/Open_sourcehttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Simfithttp://en.wikipedia.org/wiki/Simfithttp://en.wikipedia.org/wiki/SOCRhttp://en.wikipedia.org/wiki/SOCRhttp://en.wikipedia.org/wiki/SOFA_Statisticshttp://en.wikipedia.org/wiki/SOFA_Statisticshttp://en.wikipedia.org/wiki/Statistical_Labhttp://en.wikipedia.org/wiki/Statistical_Labhttp://en.wikipedia.org/wiki/R_programming_languagehttp://en.wikipedia.org/wiki/R_programming_languagehttp://en.wikipedia.org/wiki/R_programming_languagehttp://en.wikipedia.org/wiki/Weka_(machine_learning)http://en.wikipedia.org/wiki/Weka_(machine_learning)http://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/University_of_Waikatohttp://en.wikipedia.org/wiki/University_of_Waikatohttp://en.wikipedia.org/wiki/University_of_Waikatohttp://en.wikipedia.org/wiki/University_of_Waikatohttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Weka_(machine_learning)http://en.wikipedia.org/wiki/R_programming_languagehttp://en.wikipedia.org/wiki/Statistical_Labhttp://en.wikipedia.org/wiki/SOFA_Statisticshttp://en.wikipedia.org/wiki/SOCRhttp://en.wikipedia.org/wiki/Simfithttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Open_sourcehttp://en.wikipedia.org/wiki/Shogun_(toolbox)http://en.wikipedia.org/wiki/Python_(programming_language)http://en.wikipedia.org/wiki/SciPyhttp://en.wikipedia.org/wiki/CeCILLhttp://en.wikipedia.org/wiki/Scilabhttp://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/Rattle_GUIhttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/RapidMinerhttp://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/R_Commanderhttp://en.wikipedia.org/wiki/S_(programming_language)http://en.wikipedia.org/wiki/Free_softwarehttp://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/PSPPhttp://en.wikipedia.org/wiki/Ploticushttp://en.wikipedia.org/wiki/Bioinformaticshttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Orange_(software)http://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/Structural_equation_modelinghttp://en.wikipedia.org/wiki/OpenMxhttp://en.wikipedia.org/wiki/OpenEpihttp://en.wikipedia.org/wiki/OpenBUGShttp://en.wikipedia.org/wiki/R_(programming_language)http://en.wikipedia.org/wiki/Mondrian_(software)http://en.wikipedia.org/wiki/GNU_Octavehttp://en.wikipedia.org/wiki/JMulTihttp://en.wikipedia.org/wiki/Jythonhttp://en.wikipedia.org/wiki/JHepWorkhttp://en.wikipedia.org/wiki/Just_another_Gibbs_samplerhttp://en.wikipedia.org/wiki/Gretl


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Xlisp-stat

Yxilon

Public domain

Demetra+

CSPro

Epi Info

X-12-ARIMA

Freeware

BV4.1

GeoDA

MINUIT

WinBUGSBayesian analysisusingMarkov chain Monte Carlomethods

Winpepipackage of statistical programs for epidemiologists

Proprietary

ADAPAbatch and real-time scoring of statistical models

Analytica- visual analytics and statistics package

Angoss

ASRemlfor restricted maximum likelihood analyses

BMDPgeneral statistics package

CalEstgeneral statistics and probability package with didactic tutorials

Data Appliedfor building statistical models

DPScomprehensive statistics package

EViewsforeconometric analysis

FAMEa system for managingtime series statistics and time series databases

GAUSSprogramming languagefor statistics

GenStatgeneral statistics package

GLIMearly package for fittinggeneralized linear models GraphPad InStatVery simple with lots of guidance and explanations

GraphPad PrismBiostatistics and nonlinear regression with clear explanations

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