Question 1:

a) How do you evolve research design for exploratory research? Briefly analyze.

b) Briefly explain Independent, dependent and extraneous variables in a research design.

Answer:

a) Research design for exploratory research:

Research simply means a search for facts – answers to questions and solutions to problems. It is a purposive investigation. It is an organized inquiry. It seeks to find explanations to unexplained phenomenon to clarify the doubtful facts and to correct the misconceived facts. Although any typology of research is inevitably arbitrary, Research may be classified crudely according to its major intent or the methods.

It is also known as formulating research. It is preliminary study of an unfamiliar problem about which the researcher has little or no knowledge. It is ill-structured and much less focused on pre-determined objectives. It usually takes the form of a pilot study. The purpose of this research may be to generate new ideas, or to increase the researcher’s familiarity with the problem or to make a precise formulation of the problem or to gather information for clarifying concepts or to determine whether it is feasible to attempt the study. Katz conceptualizes two levels of exploratory studies. “At the first level is the discovery of the significant variable in the situations; at the second, the discovery of relationships between variables.”

b) Independent and dependent and extraneous variables in a research design:

The research designer understandably cannot hold all his decisions in his head. Even if he could, he would have difficulty in understanding how these are inter-related. Therefore, he records his decisions on paper or record disc by using relevant symbols or concepts. Such a symbolic construction may be called the research design or model. A research design is a logical and systematic plan prepared for directing a research study.

Dependent and Independent variables:

A magnitude that varies is known as a variable. The concept may assume different quantitative values, like height, weight, income, etc. Qualitative variables are not quantifiable in the strictest sense of objectivity. However, the qualitative phenomena may also be quantified in terms of the presence or absence of the attribute considered. Phenomena that assume different values quantitatively even in decimal points are known as „continuous variables. But, all variables need not be continuous. Values that can be expressed only in integer values are called non-continuous variables. In statistical term, they are also known as discrete variable. For example, age is a continuous variable; whereas the number of children is a non-continuous variable. When changes in one variable depends upon the changes in one or more other variables, it is known as a dependent or endogenous variable, and the variables that cause the changes in the dependent variable are known as the independent or explanatory or exogenous variables. For example, if demand depends upon price, then demand is a dependent variable, while price is the independent variable.

And if, more variables determine demand, like income and prices of substitute commodity, then demand also depends upon them in addition to the own price. Then, demand is a dependent variable which is determined by the independent variables like own price, income and price of substitute.

Extraneous variable:

The independent variables which are not directly related to the purpose of the study but affect the dependent variable are known as extraneous variables. For instance, assume that a researcher wants to test the hypothesis that there is relationship between children’s school performance and their self-concepts, in which case the latter is an independent variable and the former, the dependent variable. In this context, intelligence may also influence the school performance. However, since it is not directly related to the purpose of the study undertaken by the researcher, it would be known as an extraneous variable. The influence caused by the extraneous variable on the dependent variable is technically called as an „experimental error‟. Therefore, a research study should always be framed in such a manner that the dependent variable completely influences the change in the independent variable and any other extraneous variable or variables.

Question 2:

a) Differentiate between ‘Census survey’ and ‘ Sample Survey’

b) Analyse multi-stage and sequential sampling.

Answer:

a) Difference between Census survey and Sample Survey

Census Survey	Sample Survey
A census measures absolutely everyone in the whole country. This obviously means that a census survey is a much bigger exercise in nature and procedures	A part of the population is known as sample
Census survey also is a very time consuming exercise as information needs to be collected from each and every individual from the population.	On the other hand, sample survey is easier as a representative sample is taken from the population and the results obtained are extrapolated to fit the entire population.
There are times and requirements where governments have to indulge in census survey even if it is time consuming and very expensive as it needs to formulate policies and welfare programs for the population. For example, when a government has to count heads of the population	Sample surveys cannot count the number of people in the country but when government is planning on a welfare program for cancer patients, it can conduct a sample survey of some of the cancer patients and then extrapolate the results on the section of the population that is undergoing treatment for cancer.
Census survey is more accurate.	there is margin for error in sample survey

b) Analyse multi-stage and sequential sampling:

Multi-stage sampling:

In multi-stage sampling method, sampling is carried out in two or more stages. The population is regarded as being composed of a number of second stage units and so forth. That is, at each stage, a sampling unit is a cluster of the sampling units of the subsequent stage. First, a sample of the first stage sampling units is drawn, then from each of the selected first stage sampling unit, a sample of the second stage sampling units is drawn. The procedure continues down to the final sampling units or population elements. Appropriate random sampling method is adopted at each stage. It is appropriate where the population is scattered over a wider geographical area and no frame or list is available for sampling. It is also useful when a survey has to be made within a limited time and cost budget. The major disadvantage is that the procedure of estimating sampling error and cost advantage is complicated.

Sequential sampling:

Sequential sampling is a non-probability sampling technique wherein the researcher picks a single or a group of subjects in a given time interval, conducts his study, analyses the results then picks another group of subjects if needed and so on. This sampling technique gives the researcher limitless chances of fine tuning his research methods and gaining a vital insight into the study that he is currently pursuing. There is very little effort in the part of the researcher when performing this sampling technique. It is not expensive, not time consuming and not workforce extensive.

This sampling method is hardly representative of the entire population. Its only hope of approaching representativeness is when the researcher chose to use a very large sample size significant enough to represent a big fraction of the entire population. Due to the aforementioned disadvantages, results from this sampling technique cannot be used to create conclusions and interpretations pertaining to the entire population.

Question 3:

List down various measures of central tendency and

explain the difference between them?

Answer:

Measures of Central Tendency:

The term central tendency refers to the "middle" value or perhaps a typical value of the data, and is measured using the mean, median, or mode. Each of these measures is calculated differently, and the one that is best to use depends upon the situation.

Analysis of data involves understanding of the characteristics of the data. The following are the important characteristics of a statistical data:

*Central tendency, *Dispersion, *Skew ness, *Kurtosis

In a data distribution, the individual items may have a tendency to come to a central position or an average value. For instance, in a mark distribution, the individual students may score marks between zero and hundred. In this distribution, many students may score marks, which are near to the average marks, i.e. 50. Such a tendency of the data to concentrate to the central position of the distribution is called central tendency. Central tendency of the data is measured by statistical averages. Averages are classified into two groups.

1. Mathematical averages

2. Positional averages

Statistical Averages

Mathematical averages Positional averages

Arithmetic mean Median

Geometric mean Mode

Harmonic mean

Arithmetic mean, geometric mean and harmonic mean are mathematical averages. Median and mode are positional averages. These statistical measures try to understand how individual values in a distribution concentrate to a central value like average. If the values of distribution approximately come near to the average value, we conclude that the distribution has central tendency.

Difference between Mean and Median:

Mean (Mathematical averages)	Median (Positional averages)
When the sample size is large and does not include outliers, the mean score usually provides a better measure of central tendency.	The median may be a better indicator of the most typical value if a set of scores has an outlier. An outlier is an extreme value that differs greatly from other values.
The mean is the most commonly-used measure of central tendency. When we talk about an "average", we usually are referring to the mean	The median often is used when there are a few extreme values that could greatly influence the mean and distort what might be considered typical.
The mean is simply the sum of the values divided by the total number of items in the set	The median is determined by sorting the data set from lowest to highest values and taking the data point in the middle of the sequence

Question 4:

What is questionnaire? Discuss the main points that you will take into account while drafting a questionnaire?

Answer:

A questionnaire is a research instrument consisting of a series of questions and other prompts for the purpose of gathering information from respondents. Although they are often designed for statistical analysis of the responses, this is not always the case. The questionnaire was invented by Sir Francis Galton.

Questionnaires have advantages over some other types of surveys in that they are cheap, do not require as much effort from the questioner as verbal or telephone surveys, and often have standardized answers that make it simple to compile data. However, such standardized answers may frustrate users. Questionnaires are also sharply limited by the fact that respondents must be able to read the questions and respond to them. Thus, for some demographic groups conducting a survey by questionnaire may not be practical.

As a type of survey, questionnaires also have many of the same problems relating to question construction and wording that exist in other types of opinion polls.

Questionnaires may be classified as:

Structured/ Standardized Questionnaire:

Structured questionnaires are those in which there are definite, concrete and preordained questions with additional questions limited to those necessary to clarify inadequate answers or to elicit more detailed responses. The questions are presented with exactly the same wording and in the same order to all the respondents.

Unstructured Questionnaire:

In unstructured questionnaires the respondent is given the opportunity to answer in his own terms and in his own frame of reference.

Points to take into account while drafting a questionnaire:

Writing an effective questionnaire is not a task for novices. At the very least it requires an understanding of four basics. These are:

*Considering the differences that exist when writing a questionnaire that respondent’s will fill out themselves as opposed to when a professional interviewer administers the questionnaire to the respondent.

*Knowing what questions should be asked early on in the questionnaire, in the middle or toward the end.

*Understanding how to phrase questions.

*Being sensitive to questionnaire length.

There are some basic differences in how the questionnaire should be constructed if it is to be filled out personally by the respondent or if an interviewer is going to administer it. These are:

*Self-administered questionnaires should be simple, straightforward and logical. Question 2 should follow question 1. Question 3 should follow question 2, and so forth. Further, the going-in assumption with self-administered questionnaires should be that respondents will not complete a questionnaire when there are complex skip patterns, when pages are crowded or hard to read or when instructions for completion are overly complex.

It has been estimated that as many as 50% of respondents who start a self-administered questionnaire will not complete it because they become irritated and annoyed at the way it is constructed. When writing a self-administered questionnaire, then, every care must be taken to ensure that it is easy to complete in that it almost answers itself.

*Self-administered questionnaires should be written with an eighth grade mentality in mind while interviewer-administered questionnaire can be quite complex. Because interviewers are trained in the flow of the questionnaires they administer and will conduct a number of practice interviews prior to confronting a respondent, developing a complex questionnaire that is interviewer-administered does not present a problem for the respondent.

*Keep the respondent in one mind-set at a time. If at all possible, complete all your questions about one topic before moving on to the next. For example, don’t ask about a favorite place to shop, then about brands used and then go back to additional questioning on favorite place to shop.

*Save sensitive questions for the end. Again, this might not always be possible, but when it doesn’t matter, be aware that sensitive questions such as race or income can alienate respondents and turn them off to the entire interview process. If asked at the end, respondents are more likely to answer as they are wholly invested in the questionnaire.

*Biased question: What do you like about the last airline flight you took? Assumption here is that respondent liked something and the question tends to push for a positive response.

*Unbiased question. What, if anything, do you like the last airline flight you took? By simply using if anything as part of the question phrasing, the respondent is not put on the spot to find something to like.

*When conducting telephone interviews, it’s relatively easy to keep respondents on the phone and answering questions for 15, 20 or 25 minutes if the questionnaire has a good flow and is thoughtfully written. But try keeping a respondent on the phone for 3 minutes with a questionnaire that is the least bit confusing, seems redundant or is insensitive to sensitive issues.

Question 5:

What do you mean by primary data? What are the various methods of collecting primary data?

Answer:

Primary Date is data that has not been previously published, i.e. the data is derived from a new or original research study and collected at the source, e.g., in marketing, it is information that is obtained directly from first-hand sources by means of surveys, observation or experimentation.

Data observed or collected directly from first-hand experience. Published data and the data collected in the past or other parties are called secondary data. Primary data are directly collected by the researcher from their original sources. In this case, the researcher can collect the required date precisely according to his research needs, he can collect them when he wants them and in the form he needs them. But the collection of primary data is costly and time consuming. Yet, for several types of social science research required data are not available from secondary sources and they have to be directly gathered from the primary sources.

In such cases where the available data are inappropriate, inadequate or obsolete, primary data have to be gathered. They include: socio economic surveys, social anthropological studies of rural communities and tribal communities, sociological studies of social problems and social institutions. Marketing research, leadership studies, opinion polls, attitudinal surveys, readership, radio listening and T.V. viewing surveys, knowledge-awareness practice (KAP) studies, farm managements studies, business management studies etc.

Primary data are always collected from the source. It is collected either by the investigator himself or through his agents. There are different methods of collecting primary data. Each method has its relative merits and demerits. The investigator has to choose a particular method to collect the information. The choice to a large extent depends on the preliminaries to data collection some of the commonly used methods are discussed below.

1) Direct Personal observation:

This is a very general method of collecting primary data. Here the investigator directly contacts the informants, solicits their cooperation and enumerates the data. The information are collected by direct personal interviews.

The novelty of this method is its simplicity. It is neither difficult for the enumerator nor the informants because both are present at the spot of data collection. This method provides most accurate information as the investigator collects them personally. But as the investigator alone is involved in the process, his personal bias may influence the accuracy of the data. So it is necessary that the investigator should be honest, unbiased and experienced. In such cases the data collected may be fairly accurate. However, the method is quite costly and time-consuming. So the method should be used when the scope of enquiry is small.

2) Indirect Oral Interviews:

This is an indirect method of collecting primary data. Here information is not collected directly from the source but by interviewing persons closely related with the problem. This method is applied to apprehend culprits in case of theft, murder etc. The information relating to one's personal life or which the informant hesitates to reveal are better collected by this method. Here the investigator prepares 'a small list of questions relating to the enquiry. The answers (information) are collected by interviewing persons well connected with the incident. The investigator should cross-examine the informants to get correct information.

This method is time saving and involves relatively less cost. The accuracy of the information largely depends upon the integrity of the investigator. It is desirable that the investigator should be experienced and capable enough to inspire and create confidence in the informant to collect accurate data.

3) Mailed Questionnaire method:

This is a very commonly used method of collecting primary data. Here information is collected through a set of questionnaire. A questionnaire is a document prepared by the investigator containing a set of questions. These questions relate to the problem of enquiry directly or indirectly. Here first the questionnaires are mailed to the informants with a formal request to answer the question and send them back. For better response the investigator should bear the postal charges. The questionnaire should carry a polite note explaining the aims and objective of the enquiry, definition of various terms and concepts used there. Besides this the investigator should ensure the secrecy of the information as well as the name of the informants, if required.

Success of this method greatly depends upon the way in which the questionnaire is drafted. So the investigator must be very careful while framing the questions. The questions should be:

*Short and clear

*Few in number

*Simple and intelligible

*Corroboratory in nature or there should be provision for cross check

*Impersonal, non-aggressive type

*Simple alternative, multiple-choice or open-end type

a) In the simple alternative question type, the respondent has to choose between alternatives such as ‘Yes or No’, ‘right or wrong’ etc.

For example: Is Adam Smith called father of Statistics? Yes/No

b) In the multiple choice type, the respondent has to answer from any of the given alternatives.

Example: To which sector do you belong?

*Primary Sector

*Secondary Sector

*Tertiary or Service Sector

c) In the Open-end or free answer questions the respondents are given complete freedom in answering the questions. The questions are like –

What are the defects of our educational system?

The questionnaire method is very economical in terms of time, energy and money. The method is widely used when the scope of enquiry is large. Data collected by this method are not affected by the personal bias of the investigator. However the accuracy of the information depends on the cooperation and honesty of the informants. This method can be used only if the informants are cooperative, conscious and educated. This limits the scope of the method.