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!

Logistic Regression

The right choices over time greatly improve your odds of a long and healthy life.

—Tom Rath

Learning Objectives

Upon completing this chapter, you will be able to do the following:

  • Determine when it is appropriate to run a logistic regression analysis.
  • Verify that the data meet the criteria for logistic regression processing: sample size, normality, and multicollinearity.
  • Order a logistic regression test.
  • Comprehend the logistic regression R2 statistic.
  • Label and derive results from the Variables in the Equation table.
  • Selectively process findings to respond to a variety of research questions.
  • Understand the rationale for recoding categorical variables.
  • Resolve the hypotheses.
  • Write an appropriate abstract.

When to Use This Statistic

Guidelines for Selecting the Logistic Regression Test

Overview: This statistic indicates which variables predict a dichotomous (two-category) outcome.

Variables: This statistic can accommodate multiple continuous and categorical ...

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