| Description |
1 online resource |
| Series |
Coursesmart |
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Coursesmart
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| Contents |
880-01 Introduction to psychological statistics -- Frequency tables, graphs, and distributions -- Measures of central tendency and variability -- Standardized scores and the normal distribution -- Introduction to hypothesis testing: The one-sample z test -- Interval estimation and the t distribution -- The t test for two independent sample means -- Statistical power and effect size -- Linear correlation -- Linear regression -- The matched t test -- One-way independent ANOVA -- Multiple comparisons -- Two-way ANOVA -- Repeated measures ANOVA -- Two-way mixed design ANOVA -- Multiple regression -- The regression approach to ANOVA -- The binomial distribution -- Chi-square tests |
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880-01/(S Contents note continued: Step 1 State the Hypotheses -- Step 2 Select the Statistical Test and the Significance Level -- Step 3 Select the Samples and Collect the Data -- Step 4 Find the Regions of Rejection -- Step 5 Calculate the Test Statistics -- Step 6 Make the Statistical Decisions -- Interpreting the Results -- Alternative Breakdown of the SS Components of a Mixed-Design ANOVA -- Estimating Effect Sizes for a Mixed Design -- Publishing the Results of a Mixed ANOVA -- Assumptions of the Mixed-Design ANOVA -- A Special Case: The Before-After Mixed Design -- Post Hoc Comparisons -- An Excerpt From the Psychological Literature -- Interactions Involving Trends -- Removing Error Variance From Counterbalanced Designs -- Summary -- Exercises -- C. Analysis by SPSS -- Performing a Two-Way Mixed-Design ANOVA -- Plots -- Post Hoc Tests -- Options: Homogeneity Tests -- Simple Main Effects -- Exercises -- Key Formulas -- pt. Six Multiple Regression and Its Connection to ANOVA -- ch. 17 Multiple Regression -- A. Conceptual Foundation -- Uncorrelated Predictors -- The Standardized Regression Equation -- More Than Two Mutually Uncorrelated Predictors -- The Sign of Correlations -- Two Correlated Predictors -- The Beta Weights -- Completely Redundant Predictors -- Partial Regression Slopes -- Degrees of Freedom -- Semipartial Correlations -- Calculating the Semipartial Correlation -- Suppressor Variables -- Complementary Variables -- The Raw-Score Prediction Formula -- Partial Correlation -- Finding the Best Prediction Equation -- Hierarchical (Theory-Based) Regression -- Summary -- Exercises -- B. Basic Statistical Procedures -- The Significance Test for Multiple R -- Tests for the Significance of Individual Predictors -- Methods for Variable Selection -- Problems Associated With Having Many Predictors -- Too Few Predictors -- Minimal Sample Size -- Basic Assumptions of Multiple Regression -- Regression With Dichotomous Predictors -- Multiple Regression as a Research Tool: Variable Ordering -- Publishing the Results of Multiple Regression -- Summary -- Exercises -- Optional Exercise -- Advanced Material -- C. Analysis by SPSS -- Performing a Multiple Regression Analysis -- Statistics, Plots, Save, and Options -- Stepwise Regression -- Hierarchical Regression -- Exercises -- Key Formulas -- ch. 18 The Regression Approach to ANOVA -- A. Conceptual Foundation -- Dummy Coding -- The Regression Plane -- Effect Coding -- The General Linear Model -- Equivalence of Testing ANOVA and R2 -- Two-Way ANOVA as Regression -- The GLM for Higher-Order ANOVA -- Analyzing Unbalanced Designs -- Methods for Controlling Error Variance -- Summary -- Exercises -- B. Basic Statistical Procedures -- Simple ANCOVA as Multiple Regression -- The Linear Regression Approach to ANCOVA -- Post Hoc Comparisons -- Performing ANCOVA by Multiple Regression -- Power and Effect Size -- The Assumptions of ANCOVA -- Additional Considerations -- Factorial ANCOVA -- Using Two or More Covariates -- Alternatives to ANCOVA -- Using ANCOVA With Intact Groups -- Summary -- Exercises -- C. Analysis by SPSS -- Dummy Coding -- Effect Coding -- Two-Way ANOVA by Regression -- Analysis of Covariance -- Analysis of Covariance by Multiple Regression -- Exercises -- Key Formulas -- pt. Seven Nonparametric Statistics -- ch. 19 The Binomial Distribution -- A. Conceptual Foundation -- The Origin of the Binomial Distribution -- The Binomial Distribution With N = 4 -- The Binomial Distribution With N = 12 -- When the Binomial Distribution Is Not Symmetrical -- The z Test for Proportions -- The Classical Approach to Probability -- The Rules of Probability Applied to Discrete Variables -- The Empirical Approach to Probability -- Summary -- Exercises -- B. Basic Statistical Procedures -- Step 1 State the Hypotheses -- Step 2 Select the Statistical Test and the Significance Level -- Step 3 Select the Samples and Collect the Data -- Step 4 Find the Region of Rejection -- Step 5 Calculate the Test Statistic -- Step 6 Make the Statistical Decision -- Interpreting the Results -- Assumptions of the Sign Test -- The Gambler's Fallacy -- When to Use the Binomial Distribution for Null Hypothesis Testing -- Summary -- Exercises -- Advanced Material: Permutations and Combinations -- Constructing the Binomial Distribution -- C. Analysis by SPSS -- Performing a Binomial Test -- Options for the Binomial Test -- The Sign Test -- Exercises -- Key Formulas -- ch. 20 Chi-Square Tests -- A. Conceptual Foundation -- The Multinomial Distribution -- The Chi-Square Distribution -- Expected and Observed Frequencies -- The Chi-Square Statistic -- Critical Values of Chi-Square -- Tails of the Chi-Square Distribution -- Expected Frequencies Based on No Preference -- The Varieties of One-Way Chi-Square Tests -- Summary -- Exercises -- B. Basic Statistical Procedures -- Two-Variable Contingency Tables -- Pearson's Chi-Square Test of Association -- An Example of Hypothesis Testing With Categorical Data -- The Simplest Case: 2 [×] 2 Tables -- Measuring Strength of Association -- Assumptions of the Chi-Square Test -- Some Uses for the Chi-Square Test for Independence -- Publishing the Results of a Chi-Square Test -- Summary -- Exercises -- Advanced Material -- C. Analysis by SPSS -- Performing a One-Way Chi-Square Test -- Performing a Two-Way Chi-Square Test -- Exercises -- Key Formulas -- Appendix A Statistical Tables -- A.1. Areas Under the Standard Normal Distribution -- A.2. Critical Values of the t Distribution -- A.3. Power as a Function of δ and Significance Criterion (α) -- A.4. δ as a Function of Significance Criterion (α) and Power -- A.5. Critical Values of Pearson's r (df = N -- 2) -- A.6. Table of Fisher's Transformation of r to Z -- A.7. Critical Values of the F Distribution for α = .05 -- A.8. Critical Values of the F Distribution for α = .025 -- A.9. Critical Values of the F Distribution for α = .01 -- A.10. Power of ANOVA (α = .05) -- A.11. Critical Values of the Studentized Range Statistic (q) for α = .05 -- A.12. Orthogonal Polynomial Trend Coefficients -- A.13. Probabilities of the Binomial Distribution for P = .5 -- A.14. Critical Values of the Χx2 Distribution -- Appendix B Answers to Selected Exercises in Sections A and B -- Appendix C Data From Ihno's Experiment |
| Summary |
"Now in its 4th edition, this popular and comprehensive graduate-level statistics text offers students an easy to grasp and non-intimidating approach to statistics for the non-mathematician. The text provides practical coverage of SPSS in every chapter, including screen shots, procedures, exercises, and direction on how to interpret SPSS output. The use of common data sets throughout the book aid in student comprehension. Now with a new chapter showing students how to apply the right test in the right way to come out with the most accurate and true result, the new edition continues to offer students a lively and engaging introduction to the field"-- Provided by publisher |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record and CIP data provided by publisher |
| Subject |
Psychometrics.
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Psychology -- Mathematical models.
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Statistics -- Study and teaching (Higher)
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Models, Psychological
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Psychometrics -- education
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Psychometrics
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PSYCHOLOGY -- Statistics.
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Psychology -- Mathematical models.
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Psychometrics.
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Statistics -- Study and teaching (Higher)
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Statistik
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Psychologie
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| Form |
Electronic book
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| LC no. |
2013030468 |
| ISBN |
9781118652145 |
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1118652142 |
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9781118652244 |
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111865224X |
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9781118259504 |
|
1118259505 |
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9781118234853 |
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1118234855 |
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9781118221105 |
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1118221109 |
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