Q 1.Discuss the relative advantages and disadvantages of the different methods of distributing questionnaires to the respondents of a study. There are some alternative methods of distributing questionnaires to the respondents. They are: 1) Personal delivery, 2) Attaching the questionnaire to a product, 3) Advertising the questionnaire in a newspaper or magazine, and 4) News-stand inserts.

Personal delivery: The researcher or his assistant may deliver the questionnaires to the potential respondents, with a request to complete them at their convenience. After a day or two, the completed questionnaires can be collected from them. Often referred to as the self administered questionnaire method, it combines the advantages of the personal interview and the mail survey. Alternatively, the questionnaires may be delivered in person and the respondents may return the completed questionnaires through mail.

Attaching questionnaire to a product: A firm test marketing a product may attach aquestionnaire to a product and request the buyer to complete it and mail it back to the firm. A gift or a discount coupon usually rewards the respondent.

Advertising the questionnaire: The questionnaire with the instructions for completion may be advertised on a page of a magazine or in a section of newspapers. The potential respondent completes it, tears it out and mails it to the advertiser. For example, the committee of Banks Customer Services used this method for collecting information from the customers of commercial banks in India. This method may be useful for large-scale studies on topics of common interest.

Newsstand inserts: This method involves inserting the covering letter, questionnaire and self addressed reply-paid envelope into a random sample of newsstand copies of a newspaper or magazine.

Advantages and Disadvantages: The advantages of Questionnaire are: a. This method facilitates collection of more accurate data for longitudinal studies than any other method, because under this method, the event or action is reported soon after its occurrence. b. this method makes it possible to have before and after designs made for field based studies. For example, the effect of public relations or advertising

campaigns or welfare measures can be measured by collecting data before, during and after the campaign. c. the panel method offers a good way of studying trends in events, behavior or attitudes. For example, a panel enables a market researcher to study how brand preferences change from month to month; it enables an economics researcher to study how employment, income and expenditure of agricultural laborers change from month to month; a political scientist can study the shifts in inclinations of voters and the causative influential factors during an election. It is also possible to find out how the constituency of the various economic and social strata of society changes through time and so on. d. A panel study also provides evidence on the causal relationship between variables. For example, a cross sectional study of employees may show an association between their attitude to their jobs and their positions in the organization, but it does not indicate as to which comes first -favorable attitude or promotion. A panel study can provide data for finding an answer to this question. e. It facilities depth interviewing, because panel members become well acquainted with the field workers and will be willing to allow probing interviews.

The major limitations or problems of Questionnaire method are: a. this method is very expensive. The selection of panel members, the payment of premiums, periodic training of investigators and supervisors, and the costs involved in replacing dropouts, all add to the expenditure. b. it is often difficult to set up a representative panel and to keep it representative. Many persons may be unwilling to participate in a panel study. In the course of

the study, there may be frequent dropouts. Persons with similar characteristics may replace the dropouts. However, there is no guarantee that the emerging panel would be representative. c. A real danger with the panel method is panel conditioning i.e., the risk that repeated interviews may sensitize the panel members and they become untypical, as a result of being on the panel. For example, the members of a panel study of political opinions may try to appear consistent in the views they express on consecutive occasions. In such cases, the panel becomes untypical of the population it was selected to represent. One possible safeguard to panel conditioning is to give members of a panel only a limited panel life and then to replace them with persons taken randomly from a reserve list. d. the quality of reporting may tend to decline, due to decreasing interest, after a panel has been in operation for some time. Cheating by panel members or investigators may be a problem in some cases.

Q 2. In processing data, what is the difference between measures of central tendency and measures of dispersion? What is the most important measure of central tendency and dispersion? Measures of Central tendency: Arithmetic Mean The arithmetic mean is the most common measure of central tendency. It simply the sum of the numbers divided by the number of numbers. The symbol m is used for the mean of a population. The symbol M is used for the mean of a sample. The formula for m is shown below: m= X/N. Where X is the sum of all the numbers in the numbers in the sample and N is the number of numbers in the sample. As an example, the mean of the numbers 1+2+3+6+8=20/5=4 regardless of whether the numbers constitute the entire population or just a sample from the population. The table, Number of touchdown passes, shows the number of touchdown (TD) passes thrown by each of the 31 teams in the National Football League in the 2000 season. The mean number of touchdown passes thrown is 20.4516 as shown below. m= X/N=634/31 =20.4516

37 33 33 32 29 28 28 23 22 22 22 21 21 21 20 20 19 19 18 18 18 18 16 15 14 14 14 12 12 9 6 Table 1: Number of touchdown passes Although the arithmetic mean is not the only "mean" (there is also a geometric mean), it is by far the most commonly used. Therefore, if the term "mean" is used without specifying whether it is the arithmetic mean, the geometric mean, or some other mean, it is assumed to refer to the arithmetic mean.

Median The median is also a frequently used measure of central tendency. The median is the midpoint of a distribution: the same number of scores is above the median as below it. For the data in the table, Number of touchdown passes, there are 31 scores. The 16th highest score (which equals 20) is the median because there are 15 scores below the 16th score and 15 scores above the 16th score. The median can also be thought of as the 50th percentile.

Let's return to the made up example of the quiz on which you made a three discussed previously in the module Introduction to Central Tendency and shown in Table 2.

Student Dataset 1 Dataset 2 Dataset 3 You 3 3 3 John's 3 4 2 Maria's 3 4 2 Shareecia's 3 4 2 Luther's 3 5 1 Table 2: Three possible datasets for the 5-point make-up quiz

For Dataset 1, the median is three, the same as your score. For Dataset 2, the median is 4. Therefore, your score is below the median. This means you are in the lower half of the class.

Finally for Dataset 3, the median is 2. For this dataset, your score is above the median and therefore in the upper half of the distribution.

Computation of the Median: When there is an odd number of numbers, the median is simply the middle number. For example, the median of 2, 4, and 7 is 4. When there is an even number of numbers, the median is the mean of the two middle numbers. Thus, the median of the numbers 2, 4, 7, 12 is 4+7/2=5.5.

Mode The mode is the most frequently occurring value. For the data in the table, Number of touchdown passes, the mode is 18 since more teams (4) had 18 touchdown passes than any other number of touchdown passes. With continuous data such as response time measured to many decimals, the frequency of each value is one since no two scores will be exactly the same (see discussion of continuous variables). Therefore the mode of continuous data is normally computed from a grouped frequency distribution. The Grouped frequency distribution table shows a grouped frequency distribution for the target response time data. Since the interval with the highest frequency is 600-700, the mode is the middle of that interval (650).

Range Frequency 500-600 3 600-700 6 700-800 5 800-900 5 900-1000 0 1000-1100 1

Table 3: Grouped frequency distribution Measures of Dispersion: A measure of statistical dispersion is a real number that is zero if all the data are identical, and increases as the data becomes more diverse. It cannot be less than zero.

Most measures of dispersion have the same scale as the quantity being measured. In other words, if the measurements have units, such as metres or seconds, the measure of dispersion has the same units. Such measures of dispersion include: Standard deviation Interquartile range Range Mean difference Median absolute deviation Average absolute deviation (or simply called average deviation) Distance standard deviation

These are frequently used (together with scale factors) as estimators of scale parameters, in which capacity they are called estimates of scale. All the above measures of statistical dispersion have the useful property that they are locationinvariant, as well as linear in scale. So if a random variable X has a dispersion of SX then a linear transformation Y = aX + b for real a and b should have dispersion SY = |a|SX. Other measures of dispersion are dimensionless (scale-free). In other words, they have no units even if the variable itself has units. These include: Coefficient of variation Quartile coefficient of dispersion Relative mean difference, equal to twice the Gini coefficient There are other measures of dispersion: Variance (the square of the standard deviation) location-invariant but not linear in scale.

Variance-to-mean ratio mostly used for count data when the term coefficient of dispersion is used and when this ratio is dimensionless, as count data are themselves dimensionless: otherwise this is not scale-free.

Some measures of dispersion have specialized purposes, among them the Allan variance and the Hadamard variance. For categorical variables, it is less common to measure dispersion by a single number. See qualitative variation. One measure that does so is the discrete entropy.

Sources of statistical dispersion In the physical sciences, such variability may result only from random measurement errors. Instrument measurements are often not perfectly precise, i.e., reproducible. One may assume that the quantity being measured is unchanging and stable, and that the variation between measurements is due to observational error. In the biological sciences, this assumption is false. The variation observed might be intrinsic to the phenomenon. Distinct members of a population differ greatly. This is also seen in the arena of manufactured products; even there, the meticulous scientist finds variation. The simple model of a stable quantity is preferred when it is tenable. Each phenomenon must be examined to see if it warrants such a simplification.

Q 3. What are the characteristics of a good research design? Explain how the research design for exploratory studies is different from the research design for descriptive and diagnostic studies.

Good research design:Much contemporary social research is devoted to examining whether a program, treatment, or manipulation causes some outcome or result. For example, we might wish to know whether a new educational program causes subsequent achievement score gains, whether a special work release program for prisoners causes lower recidivism rates, whether a novel drug causes a reduction in symptoms, and so on. Cook and Campbell (1979) argue that three conditions must be met before we can infer that such a cause-effect relation exists:

1. Covariation. Changes in the presumed cause must be related to changes in the presumed effect. Thus, if we introduce, remove, or change the level of a treatment or program, we should observe some change in the outcome measures. 2. Temporal Precedence. The presumed cause must occur prior to the presumed effect. 3. No Plausible Alternative Explanations. The presumed cause must be the only reasonable explanation for changes in the outcome measures. If there are other factors, which could be responsible for changes in the outcome measures, we cannot be confident that the presumed cause-effect relationship is correct. In most social research the third condition is the most difficult to meet. Any number of factors other than the treatment or program could cause changes in outcome measures. Campbell and Stanley (1966) and later, Cook and Campbell (1979) list a number of common plausible alternative explanations (or, threats to internal validity). For example, it may be that some historical event which occurs at the same time that the program or treatment is instituted was responsible for the change in the outcome measures; or, changes in record keeping or measurement systems which occur at the same time as the program might be falsely attributed to the program. The reader is referred to standard research methods texts for more detailed discussions of threats to validity. This paper is primarily heuristic in purpose. Standard social science methodology textbooks (Cook and Campbell 1979; Judd and Kenny, 1981) typically present an array of research designs and the alternative explanations, which these designs rule out or minimize. This tends to foster a "cookbook" approach to research design - an emphasis on the selection of an available design rather than on the construction of an appropriate research strategy. While standard designs may sometimes fit real-life situations, it will often be necessary to "tailor" a research design to minimize specific threats to validity. Furthermore, even if standard textbook designs are used, an understanding of the logic of design construction in general will improve the comprehension of these standard approaches. This paper takes a structural approach to research design. While this is by no means the only strategy for constructing research designs, it helps to clarify some of the basic principles of design logic.

Minimizing Threats to Validity Good research designs minimize the plausible alternative explanations for the hypothesized cause-effect relationship. But such explanations may be ruled out or minimized in a number of ways other than by design. The discussion, which follows, outlines five ways to minimize threats to validity, one of which is by research design:

1. By Argument. The most straightforward way to rule out a potential threat to validity is to simply argue that the threat in question is not a reasonable one. Such an argument may be made either a priori or a posteriori, although the former will usually be more convincing than the latter. For example, depending on the situation, one might argue that an instrumentation threat is not likely because the same test is used for pre and post test measurements and did not involve observers who might improve, or other such factors. In most cases, ruling out a potential threat to validity by argument alone will be weaker than the other approaches listed below. As a result, the most plausible threats in a study should not, except in unusual cases, be ruled out by argument only.

2. By Measurement or Observation. In some cases it will be possible to rule out a threat by measuring it and demonstrating that either it does not occur at all or occurs so minimally as to not be a strong alternative explanation for the cause-effect relationship. Consider, for example, a study of the effects of an advertising campaign on subsequent sales of a particular product. In such a study, history (i.e., the occurrence of other events which might lead to an increased desire to purchase the product) would be a plausible alternative explanation. For example, a change in the local economy, the removal of a competing product from the market, or similar events could cause an increase in product sales. One might attempt to minimize such threats by measuring local economic indicators and the availability and sales of competing products. If there is no change in these measures coincident with the onset of the advertising campaign, these threats would be considerably minimized. Similarly, if one is studying the effects of special mathematics training on math achievement scores of children, it might be useful to observe everyday classroom behavior in order to verify that students were not receiving any additional math training to that provided in the study.

3. By Design. Here, the major emphasis is on ruling out alternative explanations by adding treatment or control groups, waves of measurement, and the like. This topic will be discussed in more detail below.

4. By Analysis. There are a number of ways to rule out alternative explanations using statistical analysis. One interesting example is provided by Jurs and Glass (1971). They suggest that one could study the plausibility of an attrition or mortality threat by conducting a two-way analysis of variance. One factor in this study would be the original treatment group designations (i.e., program vs. comparison group), while the other factor would be attrition (i.e., dropout vs. non-dropout group). The dependent measure could be the pretest or other available pre-program measures. A main effect on the attrition factor would be indicative of a threat to external validity or generalizability, while an interaction between group and attrition factors would point to a possible threat to internal validity. Where both effects occur, it is reasonable to infer that there is a threat to both internal and external validity.

The plausibility of alternative explanations might also be minimized using covariance analysis. For example, in a study of the effects of "workfare" programs on social welfare caseloads, one plausible alternative explanation might be the status of local economic conditions. Here, it might be possible to construct a measure of economic conditions and include that measure as a covariate in the statistical analysis. One must be careful when using covariance adjustments of this type -- "perfect" covariates do not exist in most social research and the use of imperfect covariates will not completely adjust for potential alternative explanations. Nevertheless causal assertions are likely to be strengthened by demonstrating that treatment effects occur even after adjusting on a number of good covariates.

5. By Preventive Action. When potential threats are anticipated some type of preventive action can often rule them out. For example, if the program is a desirable one, it is likely that the comparison group would feel jealous or demoralized. Several actions can be

taken to minimize the effects of these attitudes including offering the program to the comparison group upon completion of the study or using program and comparison groups which have little opportunity for contact and communication. In addition, auditing methods and quality control can be used to track potential experimental dropouts or to insure the standardization of measurement.

The five categories listed above should not be considered mutually exclusive. The inclusion of measurements designed to minimize threats to validity will obviously be related to the design structure and is likely to be a factor in the analysis. A good research plan should, where possible. Make use of multiple methods for reducing threats. In general, reducing a particular threat by design or preventive action will probably be stronger than by using one of the other three approaches. The choice of which strategy to use for any particular threat is complex and depends at least on the cost of the strategy and on the potential seriousness of the threat.

Design Construction Basic Design Elements. Most research designs can be constructed from four basic elements: 1. Time. A causal relationship, by its very nature, implies that some time has elapsed between the occurrence of the cause and the consequent effect. While for some phenomena the elapsed time might be measured in microseconds and therefore might be unnoticeable to a casual observer, we normally assume that the cause and effect in social science arenas do not occur simultaneously, In design notation we indicate this temporal element horizontally - whatever symbol is used to indicate the presumed cause would be placed to the left of the symbol indicating measurement of the effect. Thus, as we read from left to right in design notation we are reading across time. Complex designs might involve a lengthy sequence of observations and programs or treatments across time.

2. Program(s) or Treatment(s). The presumed cause may be a program or treatment under the explicit control of the researcher or the occurrence of some natural event or

program not explicitly controlled. In design notation we usually depict a presumed cause with the symbol "X". When multiple programs or treatments are being studied using the same design, we can keep the programs distinct by using subscripts such as "X1" or "X2". For a comparison group (i.e., one which does not receive the program under study) no "X" is used.

3. Observation(s) or Measure(s). Measurements are typically depicted in design notation with the symbol "O". If the same measurement or observation is taken at every point in time in a design, then this "O" will be sufficient. Similarly, if the same set of measures is given at every point in time in this study, the "O" can be used to depict the entire set of measures. However, if different measures are given at different times it is useful to subscript the "O" to indicate which measurement is being given at which point in time.

4. Groups or Individuals. The final design element consists of the intact groups or the individuals who participate in various conditions. Typically, there will be one or more program and comparison groups. In design notation, each group is indicated on a separate line. Furthermore, the manner in which groups are assigned to the conditions can be indicated by an appropriate symbol at the beginning of each line. Here, "R" will represent a group, which was randomly assigned, "N" will depict a group, which was nonrandom assigned (i.e., a nonequivalent group or cohort) and a "C" will indicate that the group was assigned using a cutoff score on a measurement.

Q 4. How is the Case Study method useful in Business Research? Give two specific examples of how the case study method can be applied to business research. While case study writing may seem easy at first glance, developing an effective case study (also called a success story) is an art. Like other marketing communication skills, learning how to write a case study takes time. Whats more, writing case studies without careful planning usually results in sub optimal results?

Savvy case study writers increase their chances of success by following these ten proven techniques for writing an effective case study:

Involve the customer throughout the process .Involving the customer throughout the case study development process helps ensure customer cooperation and approval, and results in an improved case study. Obtain customer permission before writing the document, solicit input during the development, and secure approval after drafting the document.

Write all customer quotes for their review. Rather than asking the customer to draft their quotes, writing them for their review usually results in more compelling material.

Case Study Writing Ideas Establish a document template. A template serves as a roadmap for the case study process, and ensures that the document looks, feels, and reads consistently. Visually, the template helps build the brand; procedurally, it simplifies the actual writing. Before beginning work, define 3-5 specific elements to include in every case study, formalize those elements, and stick to them. Start with a bang. Use action verbs and emphasize benefits in the case study title and subtitle. Include a short (less than 20-word) customer quote in larger text. Then, summarize the key points of the case study in 2-3 succinct bullet points. The goal should be to tease the reader into wanting to read more. Organize according to problem, solution, and benefits. Regardless of length, the time-tested, most effective organization for a case study follows the problem-solution benefits flow. First, describe the business and/or technical problem or issue; next, describe the solution to this problem or resolution of this issue; finally, describe how the customer benefited from the particular solution (more on this below). This natural storytelling sequence resonates with readers. Use the general-to-specific-to-general approach. In the problem section, begin with a general discussion of the issue that faces the relevant industry. Then, describe the specific problem or issue that the customer faced. In the solution section, use the opposite

sequence. First, describe how the solution solved this specific problem; then indicate how it can also help resolve this issue more broadly within the industry. Beginning more generally draws the reader into the story; offering a specific example demonstrates, in a concrete way, how the solution resolves a commonly faced issue; and concluding more generally allows the reader to understand how the solution can also address their problem. Quantify benefits when possible. No single element in a case study is more compelling than the ability to tie quantitative benefits to the solution. For example, Using Solution X saved Customer Y over $ZZZ, ZZZ after just 6 months of implementation; or, Thanks to Solution X, employees at Customer Y have realized a ZZ% increase in productivity as measured by standard performance indicators. Quantifying benefits can be challenging, but not impossible. The key is to present imaginative ideas to the customer for ways to quantify the benefits, and remain flexible during this discussion. If benefits cannot be quantified, attempt to develop a range of qualitative benefits; the latter can be quite compelling to readers as well. Use photos. Ask the customer if they can provide shots of personnel, ideally using the solution. The shots need not be professionally done; in fact, homegrown digital photos sometimes lead to surprisingly good results and often appear more genuine. Photos further personalize the story and help form a connection to readers. Reward the customer. After receiving final customer approval and finalizing the case study, provide a pdf, as well as printed copies, to the customer. Another idea is to frame a copy of the completed case study and present it to the customer in appreciation for their efforts and cooperation. Writing a case study is not easy. Even with the best plan, a case study is doomed to failure if the writer lacks the exceptional writing skills, technical savvy, and marketing experience that these documents require. In many cases, a talented writer can mean the difference between an ineffective case study and one that provides the greatest benefit. If a qualified internal writer is unavailable, consider outsourcing the task to professionals who specialize in case study writing.

Q 5. What are the differences between observation and interviewing as methods of data collection? Give two specific examples of situations where either observation or interviewing would be more appropriate. Observation means viewing or seeing. Observation may be defined as a systematic viewing of a specific phenomenon on its proper setting for the specific purpose of gathering data for a particular study. Observation is classical method of scientific study. The prerequisites of observation consist of:

Observations must be done under conditions, which will permit accurate results. The observer must be in vantage point to see clearly the objects to be observed. The distance and the light must be satisfactory. The mechanical devices used must be in good working conditions and operated by skilled persons. Observation must cover a sufficient number of representative samples of the cases. Recording should be accurate and complete. The accuracy and completeness of recorded results must be checked. A certain number of cases can be observered again by another observer/another set of mechanical devices as the case may be. If it is feasible two separate observers and set of instruments may be used in all or some of the original observations. The results could then be compared to determine their accuracy and completeness. Advantages of observation a. The main virtue of observation is its directness it makes it possible to study behavior as it occurs. The researcher needs to ask people about their behavior and interactions he can simply watch what they do and say. b. Data collected by observation may describe the observed phenomena as they occur in their natural settings. Other methods introduce elements or artificiality into the researched situation for instance in interview the respondent may not behave in a natural way. There is no such artificiality in observational studies especially when the observed persons are not aware of their being observed.

c. Observations in more suitable for studying subjects who are unable to articulate meaningfully e.g. studies of children, tribal animals, birds etc. d. Observations improve the opportunities for analyzing the contextual back ground of behavior. Furthermore verbal resorts can be validated and compared with behavior through observation. The validity of what men of position and authority say can be verified by observing what they actually do. e. Observations make it possible to capture the whole event as it occurs. For example only observation can be providing an insight into all the aspects of the process of negotiation between union and management representatives. f. Observation is less demanding of the subjects and has less biasing effect on their conduct than questioning. g. It is easier to conduct disguised observation studies than disguised questioning.

h. Mechanical devices may be used for recording data in order to secure more accurate data and also of making continuous observations over longer periods. Interviews are a crucial part of the recruitment process for all Organisations. Their purpose is to give the interviewer(s) a chance to assess your suitability for the role and for you to demonstrate your abilities and personality. As this is a two-way process, it is also a good opportunity for you to ask questions and to make sure the organisation and position are right for you.

Interview format Interviews take many different forms. It is a good idea to ask the organisation in advance what format the interview will take. Competency/criteria based interviews - These are structured to reflect the competencies or qualities that an employer is seeking for a particular job, which will usually have been detailed in the job specification or advert. The interviewer is looking for evidence of your skills and may ask such things as: Give an example of a time you worked as part of a team to achieve a common goal.

Technical interviews - If you have applied for a job or course that requires technical knowledge, it is likely that you will be asked technical questions or has a separate technical interview. Questions may focus on your final year project or on real or hypothetical technical problems. You should be prepared to prove yourself, but also to admit to what you do not know and stress that you are keen to learn. Do not worry if you do not know the exact answer - interviewers are interested in your thought process and logic.

Academic interviews - These are used for further study or research positions. Questions are likely to center on your academic history to date.

Structured interviews - The interviewer has a set list of questions, and asks all the candidates the same questions.

Formal/informal interviews - Some interviews may be very formal, while others will feel more like an informal chat about you and your interests. Be aware that you are still being assessed, however informal the discussion may seem.

Portfolio based interviews - If the role is within the arts, media or communications industries, you may be asked to bring a portfolio of your work to the interview, and to have an in-depth discussion about the pieces you have chosen to include.

Senior/case study interviews - These ranges from straightforward scenario questions (e.g. What would you do in a situation where?) to the detailed analysis of a hypothetical business problem. You will be evaluated on your analysis of the problem, how you identify the key issues, how you pursue a particular line of thinking and whether you can develop and present an appropriate framework for organising your thoughts.

Specific types of interview The Screening Interview Companies use screening tools to ensure that candidates meet minimum qualification requirements. Computer programs are among the tools used to weed out unqualified candidates. (This is why you need a digital resume that is screening-friendly. See our resume center for help.) Sometimes human professionals are the gatekeepers. Screening interviewers often have honed skills to determine whether there is anything that might

disqualify you for the position. Rememberthey does not need to know whether you are the best fit for the position, only whether you are not a match. For this reason, screeners tend to dig for dirt. Screeners will hone in on gaps in your employment history or pieces of information that look inconsistent. They also will want to know from the outset whether you will be too expensive for the company.

Some tips for maintaining confidence during screening interviews: Highlight your accomplishments and qualifications. Get into the straightforward groove. Personality is not as important to the screener as verifying your qualifications. Answer questions directly and succinctly. Save your winning personality for the person making hiring decisions! Be tactful about addressing income requirements. Give a range, and try to avoid giving specifics by replying, "I would be willing to consider your best offer." If the interview is conducted by phone, it is helpful to have note cards with your vital information sitting next to the phone. That way, whether the interviewer catches you sleeping or vacuuming the floor, you will be able to switch gears quickly.

The Informational Interview On the opposite end of the stress spectrum from screening interviews is the informational interview. A meeting that you initiate, the informational interview is underutilized by jobseekers who might otherwise consider themselves savvy to the merits of networking. Job seekers ostensibly secure informational meetings in order to seek the advice of someone in their current or desired field as well as to gain further references to people who can lend insight. Employers that like to stay apprised of available talent even when they do

not have current job openings, are often open to informational interviews, especially if they like to share their knowledge, feel flattered by your interest, or esteem the mutual friend that connected you to them. During an informational interview, the jobseeker and employer exchange information and get to know one another better without reference to a specific job opening. This takes off some of the performance pressure, but be intentional nonetheless: Come prepared with thoughtful questions about the field and the company. Gain references to other people and make sure that the interviewer would be comfortable if you contact other people and use his or her name. Give the interviewer your card, contact information and resume. Write a thank you note to the interviewer.

The Directive Style In this style of interview, the interviewer has a clear agenda that he or she follows unflinchingly. Sometimes companies use this rigid format to ensure parity between interviews; when interviewers ask each candidate the same series of questions, they can more readily compare the results. Directive interviewers rely upon their own questions and methods to tease from you what they wish to know. You might feel like you are being steam-rolled, or you might find the conversation develops naturally. Their style does not necessarily mean that they have dominance issues, although you should keep an eye open for these if the interviewer would be your supervisor. Either way, remember: Flex with the interviewer, following his or her lead. Do not relinquish complete control of the interview. If the interviewer does not ask you for information that you think is important to proving your superiority as a candidate, politely interject it.

The Meandering Style This interview type, usually used by inexperienced interviewers, relies on you to lead the discussion. It might begin with a statement like "tell me about yourself," which you can use to your advantage. The interviewer might ask you another broad, open-ended question before falling into silence. This interview style allows you tactfully to guide the

discussion in a way that best serves you. The following strategies, which are helpful for any interview, are particularly important when interviewers use a non-directive approach: Come to the interview prepared with highlights and anecdotes of your skills, qualities and experiences. Do not rely on the interviewer to spark your memory-jot down some notes that you can reference throughout the interview. Remain alert to the interviewer. Even if you feel like you can take the driver's seat and go in any direction you wish, remain respectful of the interviewer's role. If he or she becomes more directive during the interview, adjust. Ask well-placed questions. Although the open format allows you significantly to shape the interview, running with your own agenda and dominating the conversation means that you run the risk of missing important information about the company and its needs.

Q 6. Case Study: You are engaged to carry out a market survey on behalf of a leading Newspaper that is keen to increase its circulation in Bangalore City, in order to ascertain reader habits and interests. What type of research report would be most appropriate? Develop an outline of the research report with the main sections. There are four major interlinking processes in the presentation of a literature review:

1. Critiquing rather than merely listing each item a good literature review is led by your own critical thought processes - it is not simply a catalogue of what has been written. Once you have established which authors and ideas are linked, take each group in turn and really think about what you want to achieve in presenting them this way. This is your opportunity for showing that you did not take all your reading at face value, but that you have the knowledge and skills to interpret the authors' meanings and intentions in relation to each other, particularly if there are conflicting views or incompatible findings in a particular area.

Rest assured that developing a sense of critical judgment in the literature surrounding a topic is a gradual process of gaining familiarity with the concepts, language, terminology and conventions in the field. In the early stages of your research you cannot be expected to have a fully developed appreciation of the implications of all findings. As you get used to reading at this level of intensity within your field you will find it easier and more purposeful to ask questions as you read: a. What is this all about?

b. Who is saying it and what authorities do they have? c. Why is it significant? d. What is its context? e. How was it reached? f. How valid is it? g. How reliable is the evidence? h. What has been gained? i. j. What do other authors say? How does it contribute?

k. So what?

2. Structuring the fragments into a coherent body through your reading and discussions with your supervisor during the searching and organising phases of the cycle, you will eventually reach a final decision as to your own topic and research design. As you begin to group together the items you read, the direction of your literature review will emerge with greater clarity. This is a good time to finalise your concept map, grouping linked items, ideas and authors into firm categories as they relate more obviously to your own study. Now you can plan the structure of your written literature review, with your own intentions and conceptual framework in mind. Knowing what you want to convey will help you decide the most appropriate structure.

A review can take many forms; for example: a. An historical survey of theory and research in your field b. A synthesis of several paradigms c. A process of narrowing down to your own topic It is likely that your literature review will contain elements of all of these. As with all academic writing, a literature review needs: a. An introduction b. A body c. A conclusion The introduction sets the scene and lays out the various elements that are to be explored. The body takes each element in turn, usually as a series of headed sections and subsections. The first paragraph or two of each section mentions the major authors in association with their main ideas and areas of debate. The section then expands on these ideas and authors, showing how each relates to the others, and how the debate informs your understanding of the topic. A short conclusion at the end of each section presents a synthesis of these linked ideas. The final conclusion of the literature review ties together the main points from each of your sections and this is then used to build the framework for your own study. Later, when you come to write the discussion chapter of your thesis, you should be able to relate your findings in one-to-one correspondence with many of the concepts or questions that were firmed up in the conclusion of your literature review.

3. Controlling the 'voice' of your citations in the text (by selective use of direct quoting, paraphrasing and summarizing) You can treat published literature like any other data, but the difference is that it is not data you generated yourself. When you report on your own findings, you are likely to present the results with reference to their source, for example: a. Table 2 shows that sixteen of the twenty subjects responded positively.'When using published data, you would say: b. 'Positive responses were recorded for 80 per cent of the subjects (see table 2).'

c. 'From the results shown in table 2, it appears that the majority of subjects responded positively.'

In these examples your source of information is table 2. Had you found the same results on page 17 of a text by Smith published in 1988, you would naturally substitute the name, date and page number for 'table 2'. In each case it would be your voice introducing a fact or statement that had been generated somewhere else. You could see this process as building a wall: you select and place the 'bricks' and your 'voice' provides the mortar, which determines how strong the wall will be. In turn, this is significant in the assessment of the merit and rigor of your work. There are three ways to combine an idea and its source with your own voice: a. Direct quote

b. Paraphrase c. Summary In each method, the author's name and publication details must be associated with the words in the text, using an approved referencing system. If you don't do this you would be in severe breach of academic convention, and might be penalized. Your field of study has its own referencing conventions you should investigate before writing up your results. Direct quoting repeats exact wording and thus directly represents the author: 'Rain is likely when the sky becomes overcast' (Smith 1988, page 27). If the quotation is run in with your text, single quotation marks are used to enclose it, and it must be an identical copy of the original in every respect. Overuse or simple 'listing' of quotes can substantially weaken your own argument by silencing your critical view or voice. Paraphrasing is repeating an idea in your own words, with no loss of the author's intended meaning: As Smith (1988) pointed out in the late eighties, rain may well be indicated by the presence of cloud in the sky. Paraphrasing allows you to organize the ideas expressed by the authors without being rigidly constrained by the grammar, tense and vocabulary of the original. You retain a degree of flexibility as to whose voice comes through most strongly.

Summarizing means to shorten or crystallize a detailed piece of writing by restating the main points in your own words and in the order in which you found them. The original writing is 'described' as if from the outside, and it is your own voice that is predominant: Referring to the possible effects of cloudy weather, Smith (1988) predicted the likelihood of rain. Smith (1988) claims that some degree of precipitation could be expected as the result of clouds in the sky: he has clearly discounted the findings of Jones (1986).

4. Using appropriate language Your writing style represents you as a researcher, and reflects how you are dealing with the subtleties and complexities inherent in the literature. Once you have established a good structure with appropriate headings for your literature review, and once you are confident in controlling the voice in your citations, you should find that your writing becomes more lucid and fluent because you know what you want to say and how to say it. The good use of language depends on the quality of the thinking behind the writing, and on the context of the writing. You need to conform to discipline-specific requirements. However, there may still be some points of grammar and vocabulary you would like to improve. If you have doubts about your confidence to use the English language well, you can help yourself in several ways: a. Ask for feedback on your writing from friends, colleagues and academics b. Look for specific language information in reference materials c. Access programs or self-paced learning resources which may be available on your campus Grammar tips - practical and helpful The following guidance on tenses and other language tips may be useful. Which tense should I use? Use present tense: For generalizations and claims. y y y To convey ideas, especially theories, which exist for the reader at the time of For authors' statements of a theoretical nature, which can then be compared on In referring to components of your own document:

Use present perfect tense for: y Recent events or actions that are still linked in an unresolved way to the present:

Use simple past tense for: y Completed events or actions:

Use past perfect tense for: y Events which occurred before a specified past time:

Use modals (may, might, could, would, should) to: y Convey degrees of doubt

Other language tips y Convey your meaning in the simplest possible way. Don't try to use an intellectual tone for the sake of it, and do not rely on your reader to read your mind! y y Keep sentences short and simple when you wish to emphasise a point. Use compound (joined simple) sentences to write about two or more ideas which may be linked with 'and', 'but', 'because', 'whereas' etc. y Use complex sentences when you are dealing with embedded ideas or those that show the interaction of two or more complex elements. y Verbs are more dynamic than nouns, and nouns carry information more densely than verbs. y Select active or passive verbs according to whether you are highlighting the 'doer' or the 'done to' of the action. y Keep punctuation to a minimum. Use it to separate the elements of complex sentences in order to keep subject, verb and object in clear view. y Avoid densely packed strings of words, particularly nouns.

The total process The story of a research study Introduction I looked at the situation and found that I had a question to ask about it. I wanted to investigate something in particular.

Review of literature So I read everything I could find on the topic - what was already known and said and what had previously been found. I established exactly where my investigation would fit into the big picture, and began to realise at this stage how my study would be different from anything done previously.

Methodology I decided on the number and description of my subjects, and with my research question clearly in mind, designed my own investigation process, using certain known research methods (and perhaps some that are not so common). I began with the broad decision about which research paradigm I would work within (that is, qualitative/quantitative, critical/interpretive/ empiricist). Then I devised my research instrument to get the best out of what I was investigating. I knew I would have to analyse the raw data, so I made sure that the instrument and my proposed method(s) of analysis were compatible right from the start. Then I carried out the research study and recorded all the data in a methodical way according to my intended methods of analysis. As part of the analysis, I reduced the data (by means of my preferred form of classification) to manageable thematic representation (tables, graphs, categories, etc). It was then that I began to realise what I had found.

Findings/results What had I found? What did the tables/graphs/categories etc. have to say that could be pinned down? It was easy enough for me to see the salient points at a glance from these records, but in writing my report, I also spelled out what I had found truly significant to make sure my readers did not miss it. For each display of results, I wrote a corresponding summary of important observations relating only elements within my own set of results and comparing only like with like. I was careful not to let my own interpretations intrude or voice my excitement just yet. I wanted to state the facts - just the facts. I dealt correctly with all inferential statistical procedures, applying tests of significance where appropriate to ensure both reliability and validity. I knew that I wanted my results to be as watertight and squeaky clean as possible. They would carry a great deal more credibility, strength

and thereby academic 'clout' if I took no shortcuts and remained both rigorous and scholarly.

Discussion Now I was free to let the world know the significance of my findings. What did I find in the results that answered my original research question? Why was I so sure I had some answers? What about the unexplained or unexpected findings? Had I interpreted the results correctly? Could there have been any other factors involved? Were my findings supported or contested by the results of similar studies? Where did that leave mine in terms of contribution to my field? Can I actually generalise from my findings in a breakthrough of some kind, or do I simply see myself as reinforcing existing knowledge? And so what, after all? There were some obvious limitations to my study, which, even so, I'll defend to the hilt. But I won't become over-apologetic about the things left undone, or the abandoned analyses, the fascinating byways sadly left behind. I have my memories.

Conclusion We'll take a long hard look at this study from a broad perspective. How does it rate? How did I end up answering the question I first thought of? The conclusion needs to be a few clear, succinct sentences. That way, I'll know that I know what I'm talking about. I'll wrap up with whatever generalizations I can make, and whatever implications have arisen in my mind as a result of doing this thing at all. The more you find out, the more questions arise. How I wonder what you are ... how I speculate. OK, so where do we all go from here?

Three stages of research 1. Reading 2. Research design and implementation 3. Writing up the research report or thesis Use an active, cyclical writing process: draft, check, reflect, revise, redraft.

Establishing good practice 1. Keep your research question always in mind. 2. Read widely to establish a context for your research. 3. Read widely to collect information, which may relate to your topic, particularly to your hypothesis or research question. 4. Be systematic with your reading, note-taking and referencing records. 5. Train yourself to select what you do need and reject what you don't need. 6. Keep a research journal to reflect on your processes, decisions, state of mind, changes of mind, reactions to experimental outcomes etc. 7. Discuss your ideas with your supervisor and interested others. 8. Keep a systematic log of technical records of your experimental and other research data, remembering to date each entry, and noting any discrepancies or unexpected occurrences at the time you notice them. 9. Design your research approaches in detail in the early stages so that you have frameworks to fit findings into straightaway. 10. Know how you will analyse data so that your formats correspond from the start. 11. Keep going back to the whole picture. Be thoughtful and think ahead about the way you will consider and store new information as it comes to light.