Summary
Contents
Subject index
Bridging an understanding of Statistics and SPSS.
“The text is written in a user-friendly language and illustrates concepts that would otherwise be confusing to beginning students and those with limited computer skills.”
-Justice Mbizo, University of West Florida
This unique text helps students develop a conceptual understanding of a variety of statistical tests by linking the ideas learned in a statistics class from a traditional statistics textbook with the computational steps and output from SPSS. Each chapter begins with a student-friendly explanation of the concept behind each statistical test and how the test relates to that concept. The authors then walk through the steps to compute the test in SPSS and the output, clearly linking how the SPSS procedure and output connect back to the conceptual underpinnings of the test. By drawing clear connections between the theoretical and computational aspects of statistics, this engaging text aids students' understanding of theoretical concepts by teaching them in a practical context.
One-Way ANOVA
One-Way ANOVA
Chapter Outline
- Behind the Scenes: Conceptual Background of the Analysis of Variance (ANOVA)
- Computing the One-Way ANOVA Using SPSS
- Interpreting the ANOVA Output
- A Closer Look: Custom Contrasts in One-Way ANOVA
- Making the Most of Syntax: Custom Contrasts Using Syntax
- Connections: On the Equivalence of One-Way ANOVA and t-Tests
- Plotting the Results of the One-Way ANOVA
- A Closer Look: Testing Assumptions in One-Way ANOVA
Behind the Scenes: Conceptual Background of the Analysis of Variance (ANOVA)
Analysis of variance (known as “ANOVA”) is nearly identical to the t-test. Just like the t-test, the heart of the analysis of variance is a signal-to-noise ratio. The ANOVA produces a single number, F, akin to t, which indicates how much “signal” relative to how much “noise” there is in the data. Also like the t-test, the ...
- Loading...