Describe four examples of the application of discriminant analysis.
> 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?
> Explain what is meant by an eigenvalue.
> 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.
> 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.
> What are the main uses of regression analysis?
> Demonstrate the equivalence of regression with dummy variables to one-way ANOVA.
> What are some of the measures used to assess the relative importance of predictors in multiple regression?
> Describe the cross-validation procedure. Describe double cross-validation.
> What is multicollinearity? What problems can arise because of multicollinearity?
> Explain the stepwise regression approach. What is its purpose?
> What is gained by an examination of residuals?
> What is the product moment correlation coefficient? Does a product moment correlation of zero between two variables imply that the variables are not related to each other?
> How is the relative importance of factors measured in a balanced design?
> What is the null hypothesis in one-way ANOVA? What basic statistic is used to test the null hypothesis in one-way ANOVA? How is this statistic computed?
> What interrelated events occur in the environmental context of a research problem?
> What is total variation? How is it decomposed in a one-way analysis of variance?
> What is the relationship between analysis of variance and the t test?
> What is multivariate analysis of variance? When is it appropriate?
> Describe two tests used for examining differences in central tendencies in non-metric ANOVA.
> What are the differences between metric and non-metric analyses of variance?
> What is meant by repeated measures ANOVA? Describe the decomposition of variation in repeated measures ANOVA.
> Discuss the similarities and differences between analysis of variance and analysis of covariance.
> What is the general rule for computing percentages in cross-tabulations?
> What is the major difference between cross-tabulation and frequency distribution?
> What is a skewed distribution? What does it mean?
> Describe some of the reasons why management are often not clear about the ‘real’ research problem that needs to be addressed.
> How is the relative flatness or peakedness of a distribution measured?
> What measures of location are commonly computed?
> Describe the general procedure for conducting a t test.
> Present a classification of hypothesis testing procedures.
> Discuss the reasons for the frequent use of cross-tabulations. What are some of the limitations?
> Describe the procedure for computing frequencies.
> What options are available for the treatment of missing data?
> What kinds of consistency checks are made in cleaning the data?
> What does transcribing the data involve?
> Describe the guidelines for the coding of unstructured questions.
> What is the significance of the ‘background’ section of a research brief and research proposal?
> What is the difference between pre-coding and post-coding?
> How are unsatisfactory responses that are discovered in editing treated?
> What is meant by editing a questionnaire?
> What activities are involved in the preliminary checking of questionnaires that have been returned from the field?
