2.99 See Answer

Question: Which scale transformation procedure is most


Which scale transformation procedure is most commonly used? Briefly describe this procedure.



> 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?

> What considerations are involved in selecting a data analysis strategy?

> Explain why scale transformations are made.

> What are dummy variables? Why are such variables created?

> Describe the weighting process. What are the reasons for weighting?

> What kinds of statistical adjustments are sometimes made to the data?

> How may a researcher be creative in interpreting a research brief and developing a research proposal?

> Describe the data integrity process. Why is this process needed?

> What are wearables? How could they be used in marketing research?

> What is passive data? Give some examples of types of passive data collection that can be carried out with mobile devices.

> What does ‘mobile first’ mean for research designs?

> What kind of research activity is SMS-based research appropriate for?

> What do we mean by ‘mobile devices’? Where does the boundary lie between mobile and non-mobile devices?

> Discuss the key challenges relating to accessing social media data for research.

> Why is analysing image data on social media important?

> What is an MROC? How does use of an MROC differ from passive approaches to research?

> What is gamification and how can gamification techniques be used to improve research?

> What are the components of a marketing research proposal?

> What is crowdsourcing? What are the advantages and disadvantages of this method?

> What are the key differences between active and passive forms of social media research?

> What is the difference between social media and social networks?

> What is sentiment analysis? Why can automated sentiment analysis of social media be so difficult?

> Describe the nature of social media research.

> How should the survey fieldworker conclude an interview?

> How should the answers to unstructured questions be recorded?

> Outline the advantages and disadvantages of the interviewer developing a rapport with participants.

> Evaluate what may be done to help interviewers probe correctly and consistently.

> Describe and illustrate the differences between probing in a survey and in an in-depth interview.

> What are the components of a marketing research brief?

> What are the guidelines for asking questions?

> What qualifications should survey fieldworkers possess?

> Describe the survey fieldwork/data-collection process.

> Comment on the following field situations, making recommendations for corrective action: a. One of the interviewers has an excessive rate of refusals in face-to-face home interviews. b. In a CATI situation, many phone numbers are giving a busy signal du

> Describe the criteria that should be used for evaluating survey fieldworkers.

> What is validation of survey fieldwork? How is this done?

> How can participant selection problems be controlled?

> What aspects are involved in the supervision of survey fieldworkers?

> Why do researchers need to use survey fieldworkers?

> Describe the procedure for determining the sample size necessary to estimate a population mean, given the degree of precision and confidence but where the population variance is unknown. After the sample is selected, how is the confidence interval genera

> What is the role of the researcher in the problem definition process?

> Describe the procedure for determining the sample size necessary to estimate a population mean, given the degree of precision and confidence and a known population variance. After the sample is selected, how is the confidence interval generated?

> How do the degree of confidence and the degree of precision differ?

> Describe the difference between absolute precision and relative precision when estimating a population mean.

> What strategies are available for adjusting for non-response?

> Define incidence rate and completion rate. How do these rates affect the determination of the final sample size?

> When several parameters are being estimated, what is the procedure for determining the sample size?

> Describe the procedure for determining the sample size necessary to estimate a population proportion given the degree of precision and confidence. After the sample is selected, how is the confidence interval generated?

> Define what is meant by absolute precision and relative precision when estimating a population proportion.

> Define: a. the sampling distribution b. finite population correction c. confidence intervals.

> What is the major difference between judgemental and convenience sampling? Give examples of where each of these techniques may be successfully applied.

> Why is it vital to define the marketing research problem correctly?

> What kinds of decisions are made by marketing managers? How does marketing research help in supporting these decisions?

> What is the least expensive and least time-consuming of all sampling techniques? What are the major limitations of this technique?

2.99

See Answer