076005Unit-III

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Unit-III (Research Methods and Analysis)

Qualitative and Quantitative Methods

The contrast between positivist sociology and the verstehen approach has beenreformulated in modern sociology as a distinction between quantitative and qualitative

methodological approaches, respectively. Quantitative sociology is generally a numericalapproach to understanding human behavior. Surveys with large numbers of participants

are aggregated into data sets and analyzed using statistics, allowing researchers to discern patterns in human behavior.

Qualitative sociology generally opts for depth over breadth. The qualitative approach

uses in-depth interviews, focus groups, or analysis of content sources (books, magazines, journals, TV shows, etc.) as the data source. These sources are then analyzed

systematically to discern patterns and to arrive at a better understanding of human behavior.

Drawing a hard and fast distinction between quantitative and qualitative sociology is a bit

misleading. The first step in all sciences is the development of a theory and thegeneration of testable hypotheses. While there are some individuals who begin analyzing

data without a theoretical orientation to guide their analysis, most begin with a theoreticalidea or question and gather data to test that theory.

The second step is the collection of data. This is really where the two approaches differ.

Quantitative sociology focuses on numerical representations of the research subjects

(e.g., Do conservative Christian fathers spend more time in child care than secularfathers, when measured in hours?) Qualitative sociology focuses on the ideas foundwithin the discourse and rhetoric of the research subjects e.g., What is the narrative

homosexual men use to explain their continued participation in religions that condemntheir sexual orientation? The goal of both approaches is to answer a question and/or test a

theory.

Quantitative and QualitativeLike the distinction drawn between positivist sociology and Verstehen sociology, there is

often a distinction drawn between two types of sociological investigation: quantitativeand qualitative.

Quantitative methods of sociological research approach social phenomena from the

perspective that they can be measured and/or quantified. For instance, social class,following the quantitative approach, can be divided into different groups - upper-,

middle-, and lower-class - and can be measured using any of a number of variables or acombination thereof: income, educational attainment, prestige, power, etc. Quantitative

sociologists tend to use specific methods of data collection and hypothesis testing,including: experimental designs, surveys, secondary data analysis, and statistical analysis.

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Qualitative methods of sociological research tend to approach social phenomena from theVerstehen perspective. They are used to develop a deeper understanding of a particular

phenomenon. They also often deliberately give up on quantity - necessary for statistical

analysis - in order to reach a depth in analysis of the phenomenon studied. Even so,qualitative methods can be used to propose relationships between variables. Qualitativelyoriented sociologists tend to employ different methods of data collection and hypothesis

testing, including: participant observation, interviews, focus groups, content analysis andhistorical comparison.

While there are sociologists who employ and encourage the use of only one or the other

method, many sociologists see benefits in combining the approaches. They viewquantitative and qualitative approaches as complementary. Results from one approach

can fill gaps in the other approach. For example, quantitative methods could describelarge or general patterns in society while qualitative approaches could help to explain

how individuals understand those patterns.

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Techniques of Data Collection

Reliable data is of supreme significance to establish sociology as a science. Needless to

say, recent decades have seen much use of statistical and other informations collectedthrough various techniques which have their relative advantages and limitations.

Interview, observation, and questionnaire are some such data collection techniques.

Collection of quantitative data is one of the ways of collecting necessary evidence forreaching clear and sound decisions. This implies that statistical work must be directed

towards actual or potential problems or for testing hypothesis and theories. Data have nostanding in themselves, they have a basis for existence only when there is a problem.

Thus, statistics is not really concerned with gathering of numerical information in thehope that it may be useful to solve the problems.

Though statistics deals with quantitative data, it should be clearly understood that for purposes of interpretation, policy formulation and action, merely an analysis ofquantitative data may not be enough. They may need to be supplemented by historical

data, ascriptive data or knowledge gained though non-quantitative sources.

Techniques of data collection are broadly divided into two groups or sources:(a) Primary sources in which original research and material gathering are summarized.

These may be observation, interview, questionnaire, schedule etc.

(b) Secondary sources which use data collection through primary sources for certainspecific purpose or for general presentation in summary form. For example, publication

of government, reports, newspaper, research paper etc.

(a) PRIMARY SOURCE OF DATA COLLECTION

Participant and Quasi-Participant (Non-Participant) observation

The research method of studying intensively a small social collectivity over a period oftime by joining it and participating in its activities is also known as ethnography or field

research. It is typically used in the study of small communities, gangs, total institutions,informal groups and other small scale settings. The research techniques employed

include informal interviewing of participants and of informants (selected individuals who provide detailed interpretations of the setting being observed), participation of the

researcher in the activities being studied, and observation of key events in the life of thecollectivity.

To begin with, in sociology observations were made merely through the eye. Later on

participant observation was introduced by sociologists. As the time passed by, theystarted using both participant and quasi-participant observations for a single study. They

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have also worked out guidelines as to when and to what extent participant and quasi- participant observations have to be made use of.

What is known as participant and quasi-participant observation is the common feature of

non-controlled or controlled observation. In non-controlled participation no effort ismade to use precision instruments. The major aim of such observation is to observe thenaturalness and completeness of social behaviour. In controlled observation mechanical

instruments are used as aids for the purpose of accuracy and standardization.

From the last five decades a number of mechanical instruments have come into use likeone-way screens and mirrors, movement recorders, sound recorders, motion pictures,

rating scales, observation schedules etc. On occasions, laboratory controlled observationis made use of for a comprehensive, systematic and sophisticated study of a social factor.

In participant observation the investigator might disguise himself as a member of the

group that he proposes to observe. Nels Anderson disguised himself as a Hobo toobserve the social behaviour of Hobos. (Some writers regard Nels Anderson’s study as

the best example of participant and quasi-participant observation. He spent two or threeyears studying the life of Hobos be they on the road, in the jungle and lodging house, and

in Chicago’s Hobo College). At times the investigator adopts a role which makes himacceptable to the group without revealing his real purpose. He may join a group claiming

himself to be a social historian or a botanist.

Whenever the members of a group are unaware of the scientist’s purpose, their behaviourwould be open. An investigator can feel, as for example, the exhaustion and acceleration

of a tribal dance, the cold and hunger of the Hobo, the bitterness of the steel worker whohas been bullied by the foreman, etc. In non-controlled participant observation the

observer shares the life of the observed group. It may be intermittent like the study ofWhyte’s ‘Street Corner Society’.

The degree of participation, however, depends on the nature of the study and the practical

demands of the situation. In certain cases there is a compelling necessity for participantobservation since the subject is novel. On the other hand, a familiar subject does not need

such an observation.

This tool, however, has certain disadvantages in field research. As the investigator becomes a participant, his own range of experience shrinks. He is likely to occupy a

particular position within the group with a definite circle of friends. Observing from thiscircle of friends, he misses what the fringe individuals are doing. On occasions the

investigator might become a member of the rung of the hierarchy of the group. While being a member of the rung, he might unconsciously change the group behaviour. Added

to this, as the investigator tends to emotionally become one with the group, he losesobjectivity. He reacts in anger instead of recording; seeks ego satisfaction rather than

observing the behaviour of others.

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This natural difficulty in participant observation can be got over if the investigator issufficiently trained and possesses the qualities of attachment and detachmentsimultaneously. After all, a scientist in a laboratory is both attached and detached. If a

social scientist can develop the same attitude, he can make an excellent use of participant

observation, as for example, Dr. Verrier Elwin. After being attracted by Gandhiji, heslowly drifted into the study of the tribes of India. In the process he even married a Gondwoman. This is an extreme version of losing oneself in a group. In spite of this complete

identification, Dr. Verrier Elwin shows extraordinary insight into tribal life as borne out by his books. What is needed is a child-like delight while living amidst a group. Such an

equation, however, is more possible in simple or exotic societies rather than in complexsocieties.

Since participant observation is a difficult process, there is need for non-participant

observation. This sort of a technique is adopted by the anthropologist. He may, forexample, go on a fishing trip as a part of a society but in the preparations that are being

made for the ceremony he coolly interviews the important participants.

Nonetheless, pure non-participant observation is difficult, since such situations can become uncomfortable. A sociologist cannot become a drug addict to study the narcotic

smugglers: neither can he join a juvenile gang nor a spiritualist sect. Yet he can take partin great many activities of groups in order to avoid the awkwardness of total non-

participation. Le Play used this method a century ago in a study of European workingclass family; the Lynds, in their study of Middletown. Non-participant observation is,

then usually quasi-participant observation.

Both these types of observation have to be under some form of discipline. To begin with,a plan of the investigation must be drawn up in order to identify the facts to be observed

and the facts to be ignored. Such a document is some kind of field experience diary. Itmight contain sub-headings like price situations, sex relations, economic relations, etc.

Indeed, while the researcher takes note of such heads, he can also take cognizance ofother interesting occurrences like relations with other societies, food habits, etc.

Whenever such material is recorded, they would help the purpose of correcting someerrors that could have crept into the original purpose of the investigation.

Secondly, the recordings in the diary are sent to the colleagues who are not in the field so

that their suggestions might further enrich the process of gathering data.

Thirdly, there is no inherent contradiction between participant and non-participantobservations. Both must be used in such proportion as is conducive to the study of the

field that is chosen.

Fourthly, either kind of observation should be supplemented by highly systematizedobservation like detailed questionnaires, psychological and sociological tests, etc. What

all the sociologist or the social anthropologist does in an unsystematic fashion, to beginwith, has to be after all given a pattern. It is universal in every science that the

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participation of the individual behaviour must be corrected in various ways. In short, both participant and non-participant observations have to be carefully planned so that the purposes of such investigations bear fruit.

Regarding the shortcomings of the observation technique itself, there is a handful.

First, the observation may be lured by the conspicuous, dramatic and interesting factors.

Such failing isolates the observed features from its cultural context and habitual modes oflife. Such data exists on paper, floating in the air, while the third dimension, the actual

life, may be missing.

Secondly, the observer is generally tempted to note the outward appearance in the light ofhis own standards of culture. Frugal way of living might be mistaken for miserliness

since such a living may be in conformity with the religion professed by the subject understudy.

Thirdly, it is necessary to check any observation for its omissions because of oversight or

lack of orientation at the beginning of the study.

INTERVIEWS

Interviews are one of the most widely used methods of gathering data in sociology. Theyconsist of the researcher asking the interviewee or respondent a series of questions.

Interviews can be classified as ‘structured’ or ‘unstructured’ though many fall somewhere between these two extremes. In a structured interview, the wording of the questions and

the order in which they are asked remains the same in every case. The result is a fairlyformal question and answer session. Unstructured interviews are more like an informal

conversation. The interviewer usually has particular topics in mind to cover but few ifany previously formed questions. He has the freedom to phrase questions as he likes, ask

the respondent to develop his answers and probe responses which might be unclear andambiguous. This freedom is often extended to the respondent who may be allowed to

direct the interview into areas which interest him.

Data from structured interviews are generally regarded as more reliable. Thus, the more

structured or standardized an interview, the more easily its results can be tested byresearchers investigating other groups. By comparison data from unstructured interviews

are seen as less reliable. Questions are phrased in a variety of ways and the relationship between interviewer and respondent is likely to be more intimate. It is unclear to what

degree answers are influenced by these factors.

In general, structured interviews are regarded as appropriate for obtaining answers toquestions of ‘fact’ such as the age, sex and job of the respondent. Unstructured

interviews are seen as more appropriate for eliciting attitudes and opinions.

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Various studies have suggested that interviews pose serious problems of reliability andvalidity. This is partly due to the fact that interviews are interaction situations. Thus theresults of an interview will depend in part on the way the participants define the situation,

their perception of each other and so on.

Interviewers, like everybody else, have values, attitudes and expectations. Howevermuch the interviewer tries to disguise his views, they may well be communicated to the

respondent. This is particularly likely on the more informal situation of the unstructuredinterview. As a result the interviewer may ‘lead’ the respondent whose answers will then

reflect something of the interviewer’s attitudes and expectations.

To counter this problem, interviewers are often advised to be ‘non-directive’, to refrainfrom offering opinions, to avoid expressions of approval and disapproval. It is suggested

that they establish ‘rapport’ with their respondents, that is a warm, friendly relationshipwhich implies sympathy and understanding, but at the same time guard against

communicating their own attitudes and expectations.

QUESTIONNAIRES

A questionnaire consists of a list of pre-set questions to which respondents are asked tosupply answers. Researchers who use questionnaires regard them as a comparatively

cheap, fast and efficient method for obtaining large amounts of quantifiable data onrelatively large number of people.

Questions usually fall into the following categories. Firstly, questions may be ‘open-

ended’. For example, ‘This firm has an exceptionally good industrial relations record.Why do you think this is so?’ Open-ended questions allow the respondent to compose

his own answer rather than choosing between a number of given answers.

A second type of question, sometimes known as a ‘closed’ or ‘fixed choice’ question,requires a choice between a number of given answers like ‘yes’, ‘no’, ‘doubtful’, etc.

Questionnaires may be administered in a number of ways. Often they are given toindividuals by interviewers, in which case they take the form of structured interviews.

The postal questionnaire, as its name suggests, is mailed to respondents with a stampedaddressed envelope for return to the researcher. It provides an inexpensive way of

gathering data, especially if respondents are dispersed over a wide geographical area.The return rate, though it does not often exceed 50% of the sample population is

generally around 25%.

Once a survey has begun, the questionnaire cannot be changed since the object of theexercise is to present all respondents with the same stimuli so as to obtain comparable

data. Great care is therefore needed in the design of the questionnaire.

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Questionnaires provides data which can be easily quantified. They are largely designedfor this purpose. The questionnaire is one of the main tools of measurement in positivistsociology.

These methods of questionnaire and interview, however, have a very limited role inunderstanding the sociology of India. Regarding certain matters, the villagers are rightlysecretive about their own economic position as well as their personal life. A town-

dweller would be very reluctant to reveal his caste. Another difficulty in making use ofthis tool in India is the illiteracy of the rural people. Coupled with this, the men who are

sent out to interview and the men who prepare the questionnaire cannot evencommunicate with the rural people. The dialect, the medium and the inflexion, that are

used when a villager speaks, vary from district to district and at times from one cluster ofvillages to another.

Underlying these difficulties, there is one more hurdle. The language of measurement

and quantification is generally not known to villagers. When a villager is queried abouthis material possessions, he would simply say: all is well, and when he is asked about the

number of his children, he would reply: it was all the kindness of God. Such being thesituation in rural India, the tools of social anthropologists would be more relevant: live

amidst the people, speak their language, develop an empathy for the people andunderstand their legends, myths and traditions that go into the making the village social

structures.

SECONDARY SOURCES OF DATA COLLECTION:

Secondary sources of data are important for social scientists. These also give figures/facts pertaining to a period of time. These documents can be classified as:

(a) Personal Document(i) Autobiographies

(ii) Diaries(iii)Letters

(b) Formal Document

(i) Records(ii) Reports

(iii) Speeches, additionals, pamphlets

While using the secondary sources of data collection, two things have to be kept in mind.(a) Authenticity and Meaning

(b) The interpretation of available sources.(i) That is, the moment you do not understand what the author is saying you tend

to become biased.

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(ii) Facts have to be clearly understood i.e. what author is saying, with eachscholar having several meaning you should be clear about it.

Personal Documents

Is a spontaneous first person description by an individual of his own actions, experiencesand beliefs, for example, autobiographical diaries and letters etc. i.e. which describe thesubject’s experiences and his beliefs or which give insight into his cultural background.

Are mostly useful in opinion and market research.

Disadvantages(1) Possibility of distortion by the respondent. Since they are subjective in nature.

(2) Personal experience is revealed in a delicate and pleasing way. Dramatic eventsdescribed might exaggerated.

(3) Distortion enters during the process of translating private thoughts into permanentrecords i.e. in the course of interpretation facts can be changed/destroyed. Your

biased or preconception ideas come up.(4) While translating some authors have a habit of justifying the weakness of the past

conduct.

(5) Literary dishonest, which compels the writer to idealize his experiences.(6) Loss of memory of right sequences of events.

Because of these limitations the document are called Secondary sources of data which

has secondary importance.

Three kinds of personal documents are noticed:(1) Autobiographies

(2)

Diaries(3) Letters – impressions of others

Formal Documents(1) Records: Concerned with description of events of the past. The most satisfactory

document has little scope of error. Most authentic. It preserves not only what wassaid, but also how it was said. All the details of the past are known for example,Parliament proceedings are recorded, business and legal papers.

(2) Reports: Are the one’s which are usually written after the event, they are oftenintended to create an impression rather than merely aid memory and they are less

intimate. Compare to Records, more chances of errors. Less reliable than records.

Reports sometimes justify the recording events, for example, failures of the general,ambassador or scientist. Newspaper reports have also frequent propagandist intention.

The reporter may be tempted to distort his story in search of news value.

Apart from records and reports a variety of other existing documents can be put to use,for example, editorial, speeches, pamphlets, letters to the editor, mass communication.

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One of the greatest difficulty of secondary sources of data are to know whether relevantmaterial can be found, and if found, of getting permission to study it. Wide coverage is

not possible. There is also generalization being made on secondary sources.

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Variables

For moving from abstract concepts to the practice of social research, we have to explore

some additional terms. One such term is ‘variable’. A variable is a characteristic that

takes on two or more values. It is something that changes. It changes according todifferent factors. Some variables changes easily, like the stock-exchange value, whileother variables are constant, like the name of someone. Researchers often seek to

measure variables.

The variable can be a number, a name of anything where value can change. An exampleof a variable is temperature. The temperature varies according to other variable and

factors. You can measure different temperature inside and outside. If it is a sunny day,chances are that the temperature will be higher than if it’s cloudy. Another thing that can

make the temperature change is whether something has been done to manipulate thetemperature, like lighting a fire in the chimney.

Types of Variables:

Variables are classified in various groups as under:

(i) Independent and Dependent variables

(ii) Experimental and Measure variables

(iii) Quantitative and Qualitative variables

(i) Independent and Dependent Variables:

An independent variable (that factor that the scientist manipulates) is the presumed‘cause’ of the dependent variable (the factor that the scientist observes) – the

presumed ‘effect’.

When we say, A causes B, it means A is independent variable and B is dependentvariable. The independent variable thus is one which explains or accounts forvariations in the dependent variable. A dependent variable is one which changes in

relationship to changes in another variable.

In a controlled experiment, the independent variable is the experimental variable, i.e.one which is withheld from the control group. In experiments, the independent

variable is the variable manipulated by the experimenter. For example, in studying juvenile delinquency (dependent variable), the independent variables (i.e. causes)

could be poverty, type of associations, nature of family control and so on.

It may be noted that a variable which is dependent in one study can be independent inanother. Take the case of relation between farmer’s income and availability of water.

If we take income as dependent variable and water availability (for irrigation) asinterdependent variable, the relationship between the two variables may be shown as:

higher the availability of water, higher would be income and vice versa. But, if we

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want to show relationship between income (independent variable) and quality of life(dependent variable), we may say: higher the income, higher the quality of life (orliving standard). In the first study, income is the result and in the second study it is

the cause.

(ii) Experimental and Measured Variables:

The experimental variables spell out the details of the investigator’s manipulationswhile the measured variables refer to measurement. Experimental variables are called

‘active variables’, while measured variables are ‘assigned variables’. In other word,any variable that is manipulated is an active variables (e.g. income, literacy level,

infrastructure etc) and variables that cannot be manipulated is an assigned variable(e.g. male-female, married–unmarried rural-urban; first, second, third etc.)

(iii) Quantitative and Qualitative Variables:

The quantitative variable is one whose values or categories consist of numbers and

differences between its categories can be expressed numerically. Thus, age, income,size are quantitative variables.

The qualitative variable is one which consists of discreet categories rather than

numerical units. This variable has two or more categories that are distinguished fromeach other. For example, sex (male, female), class (lower, middle, upper) caste,

religion etc, are all qualitative variables.

The variables selected for analysis are called explanatory variables and all other

variables are extraneous. “Extraneous variables” are those that might affect therelationship between the independent and dependent variables.

Thus, variables may have different degrees of magnitudes or different categories (e.g.

positive or negative) so that the category of characteristics, in which the case falls,differentiates it from others.

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Sampling

A sample is a subset of the population that represents the entire group. When the population (or universe) is too large for the researcher to survey all its members because

of its cost, the number of personnel to be employed, or the time constraints, a smallcarefully chosen sample is extracted to represent the whole. The sample is expected to

reflect the characteristics of the population.

Classification of Sampling Methods:Sampling methods are classified into Probability or Non-probability. If the purpose of

research is to draw conclusions or make predictions affecting the population as a whole(as most research usually is), then one must use probability sampling. But, if one is only

interested in exploring how a small group, perhaps even a representative group, is doingfor purposes of illustration or explanation, then one may use non-probability sampling.

(i) Probability Sampling:In probability samples, each member of the population has a known non-zero probability

of being selected. The key point behind all probabilistic sampling approaches is randomselection. The advantage of probability sampling approaches is random selection. The

advantage of probability sampling is that sampling error can be calculated, which is thedegree to which a sample might differ from the population. Probability methods include

random sampling, systematic sampling, and stratified sampling.

(a) Random sampling is the purest form of probability sampling. Each member of

the population has an equal and known chance of being selected. The prerequisite

for a random sample is that each and every item of the universe has to beidentified. Random selection is effective in a clearly defined population that is

relatively small and self-contained. When the population is large, it is often

difficult or impossible to identify its each and every member, so the assemblage

of available subjects becomes biased. One obtains a list of all residents or the

voters list or telephone directory, and then selects a sample using a sequence of

numbers from a random numbers table. Random numbers can also be created in

numerous computer softwares.

(b) Systematic sampling is also called an “Nth

-name selection” technique. After the

required sample size has been calculated, every Nth

record is selected from a listof population members. As long as the list does not contain any hidden order, this

sampling method is as good as the random sampling method. Its only advantage

over the random sampling technique is simplicity. Systematic sampling is

frequently used to select a specified number of records from a computer file.

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(c) Stratified sampling is a commonly used probability method that is superior to

random sampling because it reduces the sampling error. A stratum is a subset of

the population that shares at least one common characteristics. Examples of strata

might be males and females, or managers or non-managers. The researcher first

identifies the relevant strata and their actual representation in the population.

Random sampling is then used to select a ‘sufficient’ number of subjects from

each stratum. ‘Sufficient’ refers to a sample size large enough for the researcher

to be reasonably confident that the stratum represents the population. Stratified

sampling is most successful when (i) the within variance of each stratum is less

than the overall variance of the population; (ii) when the strata is the population

are of unequal size of have unequal incidence; and (iii) when sampling is cheaper

in the strata.

(d) Cluster random sampling is useful when the population is dispersed across a

wide geographic region. This method allows one to divide the population into

clusters and then select the clusters at random. Thereafter one can either study all

the members of the selected clusters or again take random (simple or systematic)

sample of these sampled clusters. If the latter system is followed, it is called

multi-stage sampling. This method, for example, could be effective to study a

tribal group or a community that is dispersed. The villages could be used as

clusters and can be randomly selected.

(ii) Non-probability Sampling

In non-probability sampling, members are selected from the population in some non-random manner. In this method, the degree to which the sample differs from the

population remains unknown. Non-probability methods including Convenience sampling,Judgment sampling, Quota sampling and Snowball sampling.

(a)

Convenience sampling is used in exploratory research where the investigator is

interested in getting an inexpensive approximation of the fact. As the name

implies, the sample is selected because it is convenient. Also called haphazard or

accidental, this method is based on using people who are a captive audience, just

happen to be walking by, or show a special interest in research. The use of

volunteers is an example of convenience sampling. This method is often used

during preliminary research efforts to get a gross estimate of the results, without

incurring the cost or time required to select a random sample.

(b) Judgment sampling is a common non-probability method. The researcher selects

the sample based on judgment. This is usually an extension of convenience

sampling. For example, a researcher may decide to draw the entire sample from

one ‘representative’ village, even though the population may be distributed over a

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number of villages. When using this method, the researcher ‘feels’ that the chosen

sample is representative of the entire population.

(c) Purposive sampling, much similar to judgment sampling, is where the researcher

targets a group of people believed to be typical or average, or a group specially picked for some unique purpose. The researcher never knows if the sample is

representative or the population, and this method is largely limited to exploratory

research.

(d) Quota sampling is the non-probability equivalent of stratified sampling. Like

stratified sampling, the researcher first identifies the strata and their proportions in

the population. Then convenience or judgment sampling is used to select the

required number of subjects from each stratum. The researcher resorts to

haphazard or accidental sampling, and makes no effort to contact people who are

difficult to reach. This differs from stratified sampling, where the strata are filled

by random sampling.

(e) Snowball sampling is a special non-probability method used when the desired

sample characteristic is rare. It may be extremely difficult or cost prohibitive to

locate respondents in these situations. Snowball sampling relies on referrals from

initial subjects to generate additional subjects. In other words, snowball sampling

comprises identification of respondents who in turn refers researches to other

respondents. This technique provides a means to access relatively invisible and

vulnerable social groups. While this technique can dramatically lower the search

costs, it comes at the expense of introducing bias because the technique itself

reduces the likelihood that the sample will represent a good cross-section of the

population. For example, an investigator finds a rare genetic trait in a person, and

starts tracing his pedigree to understand the origin, inheritance and etiology of the

disease.

The reliability of a sample taken from a population can be assessed by the spread of thesampling distribution, measured by the standard deviation of this distributed, called thestandard error. As a general rule, the larger is the size of the sample the smaller the

standard error.

Advantages of Sampling:

(1) When there is large population or universe, sampling technique is best suited for the

collection of data and it economics money, time and effort.

(2) A higher percentage of accuracy can be ensured only through sampling survey.

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(3) The sample technique enables the investigators to collect the required information

from relatively a large size of population or the availability of data as unlimited incharacter.

(4) There are certain types of study where census method cannot be adopted at all.Sampling method is to be necessarily followed to make an attempt to evaluate in suchcases.

(5) When the items of an universe or population is more homogeneous in nature,

sampling technique is more feasible and useful.

Limitations of Sampling:

(1) When the various units of the survey population are not alike and liable to change

frequently, the conclusions derived from one set of units are not comparable with

another set of units.

(2) If due care is not taken in conducting a sample survey through a proper selection

of sample units, the conclusions will be much misleading and erroneous in nature.

(3) In a sample survey, only a small proportion of the entire universe or population isstudied and thus inferences are made about the entire universe or population. So

there is always likely to be a certain amount of inaccuracy or errors in suchinferences. Such errors are known as sampling error or sampling fluctuations.

Such sampling errors are not likely to be there in a census survey.

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Hypothesis

A hypothesis is an assumption about relations between variables. It is a tentative

explanation of the research problem or a guess about the research outcome. Before

starting the research, the researcher has a rather general, diffused, even confused notionof the problem. It may take long time for the researcher to say what questions he had

been seeking answers to. Hence, an adequate statement about the research problem isvery important.

What is a good problem statement? It is an interrogative statement that asks: whatrelationship exists between two or more variables? It then further asks questions like: Is

A related to B or not? How are A and B related to C? Is A related to B under conditionsX and Y? Proposing a statement pertaining to relationship between A and B is called a

hypothesis.

According to Theodorson and Theodorson, “a hypothesis is a tentative statementasserting a relationship between certain facts. Kerlinger describes it as “a conjectural

statement about something, the validity of which is usually unknown”. This statement isintended to be tested empirically and is either verified or rejected. If the statement is not

sufficiently established, it is not considered a scientific law.

Webster has defined hypothesis as “a tentative assumption made in order to draw out and

test its logical or empirical consequences”. ‘Test’ here means “either to prove it wrong or

to confirm it”. Since statements in hypothesis have to be put to empirical investigation,the definition of hypothesis excludes all statements which are merely opinions (e.g. aging

increases ailments), value judgements (e.g. contemporary politicians are corrupt and have

a vested interest to serve), or normative (e.g. all people should go for a morning walk). Normative statement is a statement of what ought to be, not a factual statement that can be shown through investigation to be right or wrong.

In other words, a hypothesis carries clear implications for testing the stated relationship,i.e. it contains variables that are measurable and specifying how they are related. A

statement that lacks variables or that does not explain how the variables are related toeach other is no hypothesis in scientific sense.

Following are a few examples of hypotheses:

Group study increases higher division achievement.

Hostlers use more alcohol than non-hostlers.

Young girls (between 15-30 years) are more victims of crimes againstwomen than middle-aged women.

Lower-class men commit more crimes than middle-class men.

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High-status high-ability students participate much less in students’agitations than low-status low-ability students.

Suicide rates vary inversely with social integration.

Young people are more satisfied with efforts for social development bydemocratic leadership than by autocratic leadership.

Criteria for Hypothesis ConstructionHypothesis is never formulated in the form of a question. Bailey, Becker, Selltiz et al,

and Sarantakos have pointed out a number of standards to be met in formulating ahypothesis:

1. It should be empirically testable, whether it is right or wrong.

2. It should be specific and precise.

3. The statements in the hypothesis should not be contradictory.

4. It should specify variables between which the relationship is to beestablished.

5. It should describe one issue only.

A hypothesis can be formed either in descriptive or relational form. In the former, it

describes events, whereas in the latter it establishes relations between variables. Ahypothesis can also be formed in the directional, non-directional or null form.

Nature of Hypotheses

A scientific justified hypothesis must meet the following criteria:

● It must accurately reflect the relevant sociological fact.

● It must not be in contradiction with approved relevant statements of other

scientific disciplines.

● It must consider the experience of other researchers.

Hypotheses cannot be described as true or false. They can only be relevant or irrelevant

to the research topic. For instance, the causes of poverty in a village can be explored in

terms of:

(i) Low development of agriculture (caused by lack of irrigation, sandy soil,

erratic rainfall and use of traditional agricultural implements) causes poverty.

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(ii) Lack of infrastructure (electricity, roads, markets) causes poverty.

(iii)Barriers in rural development are resource barriers (water, soil, minerals),support barriers (rainfall, irrigation, livestock) and social system barriers (credit,

infrastructure, extravagant expenditure and market barriers).

The important hypotheses could be:

1. Rural poverty is positively co-related with availability of/and accessibility

to credit.

2. Rural poverty is the result of lack of infrastructural facilities.

3. Poverty is associated with extravagant social expenditure.

4. Rural poverty is adversely related to resource barriers (water, soil,

minerals).

Difficulties in Formulating Hypotheses

According to Goode and Hatt, three main difficulties in formulating hypotheses are:

1. Inability to phrase the hypothesis properly.

2. Absence of clear theoretical framework or knowledge of theoreticalframework, e.g. awareness of rights among women depends upon personality,

environment (education and family and aspirations).

3. Lack of ability to utilize the theoretical framework logically, e.g. workers’

commitment and role skills and role learning.

Evaluating whether a hypothesis is good or bad depends upon the amount of information

it provides about the phenomenon. For example, let us take the following, given in three

forms:

(i) X is associated with Y.

(ii) X is dependent on Y.

(iii)As X increases Y decreases.

Of these three forms, third form explains the phenomenon better. We can take two more

examples of good and bad hypotheses:

(i) More the institutionalised controls, more the strains.

(ii) Rigid institutionalised control hampers goal-attainment.

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Sarantakos has pointed out following three functions of hypotheses:

1. to guide social research by offering directions to the structure and

operation;

2.

to offer a temporary answer to the research question; and

3. to facilitate statistical analysis of variables in the context of hypothesis

testing.

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Validity and Reliability

Physical and life scientists can directly observe most of their subject matter, which givesthem a distinct advantage for assessing validity and reliability. Social scientists, on the

other hand, do not have this advantage because most of the concepts they examine areabstract rather than concrete. How does one observe, for example, abstract concepts such

as self-esteem and marital satisfaction? Such measurements can be made, and with agreat deal of validity and reliability; doing so, however, requires a thorough

understanding of these requirements and how to assess them in practice.

Here, we will discuss validity and reliability and procedures for assessing them insociological research.

VALIDITY

According to Carmines and Zeller, “Validity” is the extent to which an instrumentmeasures what it is supposed to measure.

Scientists distinguish among different types of validity, and across disciplines refer to the

same type of validity using different names, which sometimes can create confusion aboutwhat type of validity is being assessed! Basically, validity can be classified as either non-

empirical or empirical.

Non-Empirical ValidityBy "empirical," we mean "related to observation," or "data-based." The first form of

validity we will discuss is non-empirical, meaning not related to observations or dataanalysis. Content validity (sometimes called face or representational validity) is the

consensus (i.e., intersubjective, negotiated) opinion of the community of scholars as towhether the items used to measure a construct refer to the domain of the construct and to

no other construct (i.e., the community of scholars is all persons trained within ascientific discipline, typically persons with a PhD degree). In other words, the issue of

content validity is, "Does the community of scholars agree that a particular set ofobserved variables is appropriate to measure a particular physical entity or abstract

construct?"

It is important to note that content validity is assessed only by the opinions of thecommunity of scholars. There is no empirical assessment of content validity.

Empirical Validity

Empirical validity is assessed by evaluating the extent to which a measure relates to othermeasures consistent with theoretically derived hypotheses concerning the concepts being

measured. Empirical validity is intrinsically linked to theory. Hence, we assume ameasure of a concept is valid if a theoretically derived hypothesis relating the concept to

another concept receives support through observation and data analysis. If wehypothesize, for example, that the greater the self-esteem the greater the marital

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satisfaction, and this hypothesis receives empirical support, then we assume we havemeasured each concept correctly and that each concept has empirical validity.

RELIABILITY

According to Carmines and Zeller, “Reliability” is the extent to which a measurementinstrument or procedure yields the same results on repeated trial. Without reliable

measures, scientists cannot build or test theory, and therefore cannot develop productiveand efficient procedures for improving human well being.

Reliability Assessment

Reliability assessment is the evaluation we make of how much measurement error wehave experienced in collecting our data. To collect data with as little measurement error

as possible we must:

1. Develop measures of constructs that are as valid as possible, and

2.

Follow methodological procedures that have been shown to reduce measurementerror as much as possible.

Suppose we want to know the width of our classroom from wall to wall. If we use ayardstick, for example, and measure very carefully, it is likely we will record very nearly

the same number for this width across repeated trials. We would then have a very reliablemeasure of width, which would result in a small standard error for a parameter estimate

that included width as a variable (assuming we also measured the other variable in thehypothesis with high reliability).

Now, suppose we want to measure the self-esteem of the people in our classroom.

Unfortunately, we cannot observe self-esteem with our senses; so we must devise sometype of measuring instrument that can be used with high reliability. How do we build a

measuring instrument for self-esteem that provides very similar measures on repeatedtrials? We must meet three conditions:

1. We must define self-esteem as precisely as possible by describing its conceptual

domain (its meaning) without confusing it with the domain of other constructs.Self-esteem must have a clear definition and it must not be confused with thedefinition of other constructs.

2. We must have good indicators of self-esteem, ones with high content validity.3. We must collect our data with as much accuracy as is possible.

Analyzing the above discussion we can conclude that reliability is a necessary but

insufficient condition for validity in research; reliability is a necessary precondition ofvalidity, and validity may be a sufficient but not necessary condition for reliability. In

other words, both complement each other but not coterminous.