Explain what is meant by an eigenvalue.
> What do you see as the key advantages and challenges of conducting qualitative research online?
> Describe the key elements to be balanced in the application of action research.
> What does ‘listening’ mean for the qualitative researcher? How may researchers ‘listen’ to consumers?
> Is it possible for researchers to be objective?
> What stages are involved in the application of a grounded theory approach?
> Describe and illustrate two research techniques that may be utilised in ethnographic research.
> What criticisms do qualitative researchers make of the approaches adopted by quantitative researchers, and vice versa?
> Describe the steps in the marketing-research process.
> How may the data from web analytics support the practice of marketing research?
> How may data from customer relationship management systems support the practice of marketing research?
> What is a geodemographic classification of consumers?
> Why may the characteristics of consumers differ, based upon where they live?
> Describe the benefits to the researcher of being able to capture data that identify characteristics of consumers and their shopping behaviour in a store.
> Describe the benefits to the marketing decision maker of being able to capture data that identify characteristics of consumers and their shopping behaviour in a store.
> What other sources, beyond electronic scanner devices, electronically observe customer behaviour?
> What kinds of data can be gathered through electronic scanner devices?
> What might be the limitations of using Google Analytics as a source of data for marketing research projects?
> What is big data? What are the core dimensions of big data (the four Vs)?
> Explain one way to classify marketing research suppliers and services.
> How does the compilation of different types of data help to build a strong ‘picture’ of consumer characteristics?
> How may ‘operational data’ held in organisations help to build up an understanding of customer behaviour?
> What criteria would you look for when examining the design and specifications of secondary data? Why is it important to examine these criteria?
> By what criteria may secondary data be evaluated?
> How can intranets help in the location and dissemination of secondary data?
> What is the difference between internal and external secondary data?
> How may secondary data be used to validate qualitative research findings?
> Why is it important to locate and analyse secondary data before progressing to primary data?
> At what stages of the marketing research process can secondary data be used?
> What are the relative advantages and disadvantages of secondary data?
> What challenges exist in trying to quantify the size and growth of the marketing research industry on a global basis?
> What is an audit? Describe the uses, advantages and disadvantages of audits.
> Explain what an online panel is, giving examples of different types of panel. What are the advantages and disadvantages of online panels?
> List and describe the main types of syndicated sources of secondary data.
> Evaluate the desirability of using multiple sources of secondary data and intelligence.
> If you had two sources of secondary data for a project, the first being dependable but out of date, the second not dependable but up to date, which would you prefer?
> To what extent should you use a secondary data source if you cannot see any explicit objectives attached to that research?
> What are the differences between primary data, secondary data and marketing intelligence?
> Discuss the advantages and disadvantages of access panels.
> What are the major purposes for which descriptive research is conducted?
> Describe how quantitative techniques may be used in exploratory research.
> How may the effective problem-identification research enhance the practice of problem-solving research?
> What are the major purposes for which exploratory research is conducted?
> Differentiate between exploratory and conclusive research.
> How does formulating a research design differ from developing an approach to a problem?
> How does the subject of a study, as seen by potential research participants, affect research design?
> What expectations do marketing decision makers have of research designs?
> Why is it important to minimise total error rather than any particular source of error?
> What potential sources of error can affect a research design?
> Describe a line chart. What kind of information is commonly displayed using such charts?
> Define discriminant scores.
> What is the main distinction between two-group and multiple discriminant analysis?
> What is a classification matrix?
> Explain the meaning of standardised regression coefficients.
> What is the difference between ordinal and disordinal interaction?
> What is the relationship between exploratory, descriptive and causal research?
> What is the most common use of the covariate in ANCOVA?
> How is the total variation decomposed in n-way analysis of variance?
> How does n-way analysis of variance differ from the one-way procedure?
> What is the most powerful test for making a posteriori contrasts? Which test is the most conservative?
> What is an a priori contrast?
> What is meant by a suppressed association? How is it revealed?
> Define a spurious correlation.
> What measures of variability are commonly computed?
> Which non-parametric tests are the counterparts of the two-independent samples t test for parametric data?
> Which non-parametric tests are the counterparts of the paired samples t test for parametric data?
> What is a causal research design? What is its purpose?
> Describe the major sources of error related to survey fieldwork.
> What is the major difference between parametric and non-parametric tests?
> How can the researcher ensure that the generated confidence interval will be no larger than the desired interval when estimating a population proportion?
> What are the circumstances under which a researcher would use a mobile app rather than a mobile web browser?
> Why do researchers need to be careful when carrying out telephone research with mobile devices?
> How is the sample size affected when the degree of confidence with which a population mean is estimated increases from 95% to 99%?
> How is the sample size affected when the absolute precision with which a population mean is estimated is doubled?
> Why do researchers need to be careful when using mobile-based image or video functionality as part of a mystery shopping exercise?
> What are the advantages to the researcher of having an app for their MROC?
> Evaluate the factors that have led to the growth of social media research.
> Describe cohort analysis. Why is it of special interest?
> What do you see as the major challenges for researchers that emerge from the ESOMAR definition of marketing research?
> What are the advantages of a ratio scale over an interval scale? Are these advantages significant?
> What is the procedure for constructing a confidence interval around a mean?
> What is the standard error of the mean?
> What is Wilks’ λ? For what purpose is it used?
> How should the total sample be split for estimation and validation purposes?
> What are the steps involved in conducting discriminant analysis?
> Describe the relationship of discriminant analysis to regression and ANOVA.
> Describe four examples of the application of discriminant analysis.
> How does the stepwise discriminant procedure differ from the direct method?
> When the groups are of equal size, how is the accuracy of chance classification determined?
> Compare and contrast cross-sectional and longitudinal designs.
> Describe a common procedure for determining the validity of discriminant analysis.
> How is the statistical significance of discriminant analysis determined?
> Explain the concept of structure correlations.
> What are the objectives of discriminant analysis?
> State the null hypothesis in testing the significance of the overall multiple regression equation. How is this null hypothesis tested?
> Explain the meaning of a partial regression coefficient. Why is it called that?
> What is multiple regression? How is it different from bivariate regression?
> What is meant by prediction accuracy? What is the standard error of the estimate?
> How is the strength of association measured in bivariate regression? In multiple regression?
> What is the least squares procedure?
> Define research design in your own words.
