Question paper 1997

1)What is a research design? How is it formulated? It is a framework or blueprint for conducting the marketing research project It specifies the details of the procedure necessary for obtaining the information needed to structure and/or solve marketing research problem It lays the foundation for conducting the project

Steps involved in the formulation of research design Design the exploratory, descriptive and/or causal phases of the research Define the information needed Specify the measurement & scaling procedures Construct and pretest a questionnaire or an appropriate form for data collection Specify the sampling process & sampling size Develop a plan of data analysis

2)What is meant by experimental research? It is classified under social science research It is based on experiments conducted in the laboratory Investigator creates an artificial environment under which he controls and manipulate the variable Experimental research enable the investigator to quantify the findings, to apply statistical & mathematical tools and measure the results thus quantified

3)Distinguish between null hypothesis & alternate hypothesis? An unproven proposition or supposition that tentatively explains certain facts or phenomena A proposition that is empirically testable Null hypothesis A statement about a status quo ascertaining that any change from what has been thought to be true will be due entirely at random error

Alternate hypothesis A statement indicating the opposite of the null hypothesis

4)What is meant by systematic sampling? Is this method free from bias? A probability sampling technique in which the sample is chosen by selecting a random sampling point and picking every ‘I’th element in succession from the sampling frame It is an easier and less costlier method of sampling and can be conventionally used even in case of large population

Limitations of systematic sampling systematic sampling is biased in the following cases If the sampling frame has any periodicity that parallels the sampling rates If the frame is arranged in way ascending or descending order of some attribute, then the location of the first sample element may affect the result of the study

Distinguish between experimental design and factorial design? It is a set of procedures specifying The test units & sampling procedures Independent variables Dependent variables How to control the extraneous variables

Factorial design It is used to measure the effects of two or more independent variables at various levels and to allow for interactions between variables An interaction is said to take place when the simultaneous effect of two or more variables is different from the sum of their separate effects Simple factorial design and complex factorial design are the two major categories of factorial design

Examine the relevance of pilot study in social research ? The term 'pilot studies' refers to mini versions of a full-scale study (also called 'feasibility' studies), as well as the specific pre-testing of a particular research instrument such as a questionnaire or interview schedule. Pilot studies are a crucial element of a good study design. Conducting a pilot study does not guarantee success in the main study, but it does increase the likelihood. Pilot studies fulfil a range of important functions and can provide valuable insights for other researchers. There is a need for more discussion amongst researchers of both the process and outcomes of pilot studies

Standard error The standard deviation of sampling distribution of a statistic is known as its standard error and is considered the key to sampling theory. the standard error helps in testing whether the differences between observed and expected frequencies could arise due to chance.

Standard error gives an idea about the reliability and precision of a sample. Standard error enables us to specify the limits within which the parameters of the population are expected to lie with a specified degree of confidence

Chi square as a test of goodness of fit Chi square enable us to see how well does the assumed theoretical distribution fit to the observed data. If the calculated value of chi-square is less than the table value at a certain level of significance, the fit is considered to be a good one If it is greater than the table value, the fit is not considered to be a good one

Steps in testing of hypothesis

Making formal statement Selecting a significant level Deciding the distribution to use Selecting a random sample and computing an appropriate value Calculation of the probability Comparing the probability

11. (a)What is a research problem 11.(a)What is a research problem ?Define the main aspects which would receive the attention of the researcher in formulating the research problem? Give suitable eg. A research problem refers to some kind of problem which a researcher experiences or observes in the context of either a theoretical or a practical situation

A research problem can be identified on the basis of The researchers familiarity and experience in the field of study Personal interest and aptitude in the field of study Availability of data and other information relating to a particular field of study

Factors to be considered while selecting a research problem Definition of the problem Scope of the problem Justification of the problem Feasibility of the problem Originality of the problem

Steps involved in defining a problem Stating the problem in a general way Understanding the nature of the problem Surveying the available literature Developing the ideas through discussion Rephrasing the research problem into a working proposition

Q. Define Rank Correlation ? It is a Non parametric test of statistical dependence for a random sample of paired observations. A rank correlation is the study of relationships between different rankings on the same set of items. A rank correlation coefficient measures the correspondence between two rankings and assesses its significance. Rank Correlation Coefficient is used when the population not normal. r = 1 – 6 ∑D² ÷ N (N³ – 1), where D = Difference of rank between paired items in two Series N = Number of observations