DSC 410/510 - Multivariate Statistical Methods

Chapter 1

Suggested Solutions

5. Why is knowledge of measurement scales important to an understanding of multivariate data analysis?
   
   Knowledge and understanding of measurement scales is a must before the proper multivariate technique can be chosen. Inadequate understanding of the type of data to be used can cause the selection of an improper technique, which makes any results invalid. Measurement scales must be understood so that questionnaires can be properly designed and data adequately analyzed.
   
   
6. What are the differences between statistical and practical significance? Is one a prerequisite for the other?
   
   Statistical significance is a means of assessing whether the results are due to chance. Practical significance assesses whether the result is useful or substantial enough to warrant action. Statistical significance would be a prerequisite of practical significance.
   
   
7. What are the implications of low statistical power? How can the power be improved if it is deemed too low?
   
   The implication of low power is that the researcher may fail to find significant results when they do actually exist. Power may be improved through decreasing the alpha level or increasing the sample size.