What statistical test should I use for this kind of data? How do I set up the data? What parameters should I specify when ordering the test? How do I interpret the results? Herschel Knapp’s friendly and approachable guide to real-world statistics answers these questions. Intermediate Statistics Using SPSS is not about abstract statistical theory or the derivation or memorization of statistical formulas–it is about applied statistics. With jargon-free language and clear processing instructions, this text covers the most common statistical functions–from basic to more advanced. Practical exercises at the conclusion of each chapter offer students an opportunity to process viable data sets, write cohesive abstracts in APA style, and build a thorough comprehension of the statistical process. Students will learn by doing with this truly practical approach to statistics. Free downloadable tutorial videos provide an overview of each statistical method!
What we see depends mainly on what we look for.
Upon completing this chapter, you will be able to do the following:
- Determine when it is appropriate to run a multiple regression analysis.
- Verify that the data meet the criteria for multiple regression processing: sample size, linearity, homoscedasticity, multicollinearity, and normality.
- Understand the procedure for handling polychotomous categorical variables.
- Order a multiple regression test.
- Comprehend the R2 statistic.
- Derive results from the Model Summary table.
- Resolve the hypotheses.
- Write an appropriate abstract.
When to Use This Statistic
Guidelines for Selecting the Multiple Regression Test
Overview: This statistic indicates which variables predict a continuous outcome.
Variables: This statistic can accommodate multiple continuous and categorical predictor variables with one continuous outcome variable for each record.
Results: After a group of smokers engaged in a smoking ...