图书简介
A practical book that shows how both Excel® and SPSS® can be used for analyzing data for human service evaluation.
Preface \\ Acknowledgments \\ About the Author \\ Chapter 1 Why Do We Use Statistics? \\ Why We Use Statistics \\ What You Will Find in the Rest of This Chapter \\ Two Key Issues Addressed by Data Analysis—Practical Significance and Statistical Significance \\ Using Statistics to Describe Clients, Evaluate Services, and Explain Client Behavior \\ Descriptive and Inferential Statistics \\ How Do We Analyze Data the User-Friendly Way? \\ What You Will Learn From This Book \\ Quiz \\ Key Terms \\ Chapter 2 Using the Computer for Statistical Analysis of Data \\ Using Excel for Statistical Analysis \\ Using SPSS for Statistical Analysis \\ The Structure of Excel and SPSS for Data Analysis \\ Using Excel in a User-Friendly Approach to Data Analysis— An Illustration \\ Reporting Your Findings \\ Summary of How to Use Excel \\ Quiz \\ Chapter 3 Selecting a Statistic to Answer Your Research Question \\ Finding a Descriptive Statistic \\ Finding a Statistic to Test Your Hypothesis in Evaluative Research \\ The Study Hypothesis \\ Things to Do Before You Seek a Statistic for an Evaluative Hypothesis \\ Finding Your Statistic for Testing the Evaluative Research Hypothesis: One Example \\ Practice Exercise \\ Key Terms \\ Chapter 4 Using Descriptive Statistics to Describe Your Study Sample \\ Deciding What Variables to Describe \\ Deciding What Statistics to Report About Your Study Subjects \\ Some Common Descriptive Statistics \\ Variance and the Normal Distribution \\ Using the Special Excel Files for Descriptive Statistics \\ Using SPSS for Descriptive Statistics \\ Summary \\ Quiz \\ Key Terms \\ Chapter 5 Analyzing Data With Pretest and Posttest Measurements of One Group \\ Using the t Test \\ Examining Statistical Significance and Practical Significance With the t Test \\ Testing Your Hypothesis With the Paired-Samples t Test When You Have Matching Pretest and Posttest Scores \\ Testing Your Hypothesis With the One-Sample t Test When You Have Pretest and Posttest Scores That Cannot Be Matched \\ Testing Your Hypothesis With the Binomial Test When You Have Pretest and Posttest Measurements of a Dichotomous Variable \\ Using the Binomial Test for the Posttest-Only Design When You Have a Threshold Proportion for Comparison \\ Summary \\ Quiz \\ Practice Exercise \\ Key Terms \\ Chapter 6 Analyzing Data When You Are Comparing Two Groups \\ Using the Independent-Samples t Test When You Are Comparing the Gain Scores of Two Groups \\ Using Chi Square to Compare Two Groups When You Have a Dichotomous Dependent Variable \\ Quiz \\ Practice Exercise \\ Key Terms \\ Chapter 7 Analyzing Data When You Are Evaluating a Single Client \\ Using the One-Sample t Test When You Have a Single Baseline Score and Several Treatment Scores \\ Using the Standard Deviation Approach When You Have Several Baseline Scores and Several Treatment Scores \\ Using Other Single-Subject Designs With Data Measured at the Interval Level \\ Using the Binomial Test for the AB Design When Data Are Measured as a Dichotomy \\ Quiz \\ Practice Exercise \\ Key Terms \\ Chapter 8 Explaining Client Gain \\ Examining the Relationship Between Client Gain and a Variable Measured at the Nominal Level \\ Examining the Relationship Between Client Gain and a Variable Measured at the Interval or Ordinal Level \\ Using Multiple Regression Analysis to Examine the Relationship Between Client Gain Scores and More Than One Other Variable \\ Quiz \\ Practice Exercise: Youth Diversion Program \\ Key Terms \\ Chapter 9 A Synopsis of Selected Statistical Tests for Examining Nominal Data \\ Chi Square and the Binomial Test: A Review \\ Examination of the Relationship Between Two Nominal Variables With Independent Data Using Chi Square, the Phi Coefficient, and the Contingency Coefficient \\ Examination of the Relationship Between Two Nominal Variables With Related Data Using the McNemar Test \\ Using the Binomial Test to Compare the Categories of a Dichotomous Variable \\ Key Terms \\ Chapter 10 A Synopsis of Selected Statistical Tests for Examining Ordinal Data \\ Using the Spearman Rank Correlation Coefficient When You Have Two Ordinal Variables \\ Using the Mann–Whitney U Test When You Have Independent Data With One Ordinal Variable and a Dichotomous Nominal Variable \\ Using the Wilcoxon Matched-Pairs Signed Ranks Test When You Have Related Data With a Dichotomous Variable and an Ordinal Variable \\ Using the Kruskal–Wallis One-Way Analysis of Variance When You Have Independent Data With an Ordinal Variable and a Nominal Variable That Has More Than Two Categories \\ Key Terms \\ Chapter 11 Statistics for Evidence-Based Practice \\ What Is Evidence-Based Practice? \\ Levels of Evidence \\ Statistics for Review of Evidence \\ Some Tips for Reviewing the Evidence \\ Key Terms \\ Key Terms \\ Answers to Quizzes and Review Questions \\ Appendixes \\ References \\ Index
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