Essential Statistics
Published on 25. July 2004
Book
Paperback/Softback
368 pages
978-0-13-099422-6 (ISBN)
Description
For undergraduate psychology statistics courses. This book presents all statistics essential to a student through a conversational style approach, focusing on reducing anxiety about statistics, making statistics relevant and interesting, and incorporating SPSS to show students how to analyze data efficiently. To encourage students enthusiasm of statistics and hold their interest, this book includes only those analyses that are necessary to build skills or will likely be used by them in their future.
More details
Language
English
Place of publication
Upper Saddle River
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 231 mm
Width: 178 mm
Thickness: 13 mm
Weight
508 gr
ISBN-13
978-0-13-099422-6 (9780130994226)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Person
Janie Wilson began her adventure in teaching during graduate school and continued in a full-time teaching position at Columbia College before receiving her Ph.D. in Experimental Psychology from the University of South Carolina in 1994. Since that time, she has been teaching and conducting research at Georgia Southern University. Her teaching includes courses in statistics, research methods, large sections of introductory psychology, and physiological psychology. Teaching and research merged when she was awarded a National Science Foundation grant as principal investigator for a physiological teaching laboratory, and a recent grant from the National Institute of Mental Health continues to fund her research program. She works with both undergraduates and graduate students on research projects involving social buffering of stress responses in rats and human adults and children. Dr. Wilson also conducts research on student evaluations of instructor immediacy and their ability to predict students' attitudes, motivation, and grades. She was honored with the College of Liberal Arts and Social Sciences Award for Excellence in 1997, the Award of Distinction in Teaching in 2003, and the Georgia Southern University Award for Excellence in Contributions to Instruction in 2004.
Content
PART I: INTRODUCTION. Chapter 1. Welcome to Statistics. Building competence. Rationale for learning statistics. Math. Proportion and percent. Rounding. Symbols. APA style. Conducting research. Experiments. Correlations. The usefulness of correlations. How to pick a sample. Analyzing data using SPSS. Preview of Chapter 2. Conceptual Items. Application Items. PART II: DESCRIPTIVE STATISTICS. Chapter 2. Variables and Graphing. Measurement scales. Nominal variables. Ordinal variables. Interval variables. Ratio variables. Special case of rating scales. Qualitative vs. quantitative variables. Discrete vs. continuous variables. Picturing data: Simple frequency tables and graphs. Nominal and ordinal data. Discrete interval and ratio data. Continuous interval and ratio data. Grouped frequency distributions. Shapes of distributions. Normal distributions. Skewed distributions. Kurtosis. Bimodal and trimodal distributions. Preview of Chapter 3. Conceptual Items. Application Items. Chapter 3. Measures of Central Tendency. Summarizing data. Mode. Median. Mean. Mean vs. median. Introduction to SPSS. Measures of central tendency on SPSS. Summarizing experiments using means. Graphing means. Graphing means on SPSS. Preview of Chapter 4. Conceptual Items. Application Items. Computational formula in this chapter. Chapter 4: Measures of Variability. Spread of scores. Range. Sample variance. Sample standard deviation. Estimated population standard deviation. Estimated population variance. Measures of variability on SPSS. Graphing sample standard deviation. Graphs of standard deviation on SPSS. Preview of Chapter 5. Conceptual Items. Application Items. Computational formulas in this chapter. Chapter 5. Descriptive z-scores. Standardized scores. Comparing values from different samples. Standardized distribution. Proportion and percent. Evaluations based on z-scores. Comparing two values and probability. Percentile. Logical limits. Preview of Chapter 6. Conceptual Items. Application Items. Computational formula in this chapter. PART III: INFERENTIAL STATISTICS: EXPERIMENTS AND QUASI-EXPERIMENTS. Chapter 6. Inferential z-scores and probability. Probability. Sampling distribution of means. Creating a sampling distribution of means for your research. Standardizing the sampling distribution of means. Critical value and critical region. Manipulating a sample. Not different from normal. Higher than normal. Lower than normal. Decreasing the critical region. Preview of Chapter 7. Conceptual Items. Application Items. Computational formulas in this chapter. References. Chapter 7. Hypothesis Testing. Formalizing the inferential z. Lay out expectations. Null hypothesis. Alternate hypothesis. Two-tailed z-test. A rather than. Choose a statistic. Sketch the normal distribution. Collect data. Calculate a statistic. Significance. APA style. Reject or fail to reject the null hypothesis. Inferential wording. Effect size. Plain English. Confidence intervals. One-tailed test in the positive direction. One-tailed test in the negative direction. Hypothesis testing, truth, and power. Preview of Chapter 8. Conceptual Items. Application Items. Conceptual formulas in this chapter. Chapter 8. Three t-tests. z-test vs. t-test. The single-sample t-test. Hypothesis testing using the single-sample t-test. The related-samples t-test. The sampling distribution of mean differences. Hypothesis testing using the related-samples t-test. Related-samples t-test on SPSS. APA-style results section. Independent-samples t-test. The sampling distribution of differences between means. Hypothesis testing using the independent-samples t-test. Independent-samples t-test on SPSS. APA-style results section. Preview of Chapter 9. Conceptual Items. Application Items. Computational formulas in this chapter. References. Chapter 9: ANOVA. One-Way, Between-Groups. t-test vs. ANOVA. Logic of ANOVA: Hypothesis testing. One-way, between-groups ANOVA: Equal n. Organizing ANOVA results. APA style. Effect size. Post-hoc testing: Tukey's HSD. Plain English. Confidence intervals. One-way, between-groups ANOVA: Unequal n. Summary table. Effect size. Post-hoc testing: Fisher's protected t-tests. Plain English. Confidence intervals. One-way, between-groups ANOVA on SPSS. APA-style results section. Preview of Chapter 10. Conceptual Items. Application Items. Computational formulas in this chapter. References. Chapter 10. ANOVA: Two-Way, Between-Groups. One-way vs. two-way ANOVA. Logic of the two-way, between-groups ANOVA. Two-way ANOVA effects. Calculating the two-way, between-groups ANOVA. Stot. SSBG. and SSWG. Separating SSBG into three portions. F-tests for each effect. Hypothesis testing and ANOVA results. First main effect. Second main effect. Interaction effect. Post-hoc testing. Post hoc for a significant main effect. Post hoc for a significant interaction effect. Plain English. Applying results. Two-way, between-groups ANOVA on SPSS. APA-style results section. Graphing the two-way ANOVA. Preview of Chapter 11. Conceptual Items. Application Items. Computational formulas in this chapter. References. PART IV: INFERENTIAL STATISTICS: CORRELATIONAL RESEARCH. Chapter 11. Correlational Data. Relationships between variables. Logic of Pearson's r. Perfect relationships. Less-than-perfect relationships. Pearson's r calculations. Inferential correlations: Hypothesis testing. Correlations on SPSS. Scatterplot on SPSS. Pearson's r on SPSS. APA-style results section. Inaccurate correlations. Artificially low correlations. Artificially high correlations. Preview of Chapter 12. Conceptual Items. Application Items. Computational formula in this chapter. References. Chapter 12: Linear Regression. Correlation before prediction. Linear regression theory. Prediction. Error in predictions. Calculating the regression equation. Graphing the regression line. Standard error of the estimate. Standard error calculations. Prediction on SPSS. Correlation on SPSS. Linear regression on SPSS. APA-style results section. Preview of Chapter 13. Conceptual Items. Application Items. Computational formulas in this chapter. References. Chapter 13. Chi-square Analyses. Simple frequency counts. One-way x 2: Goodness-of-fit test. Null and alternate hypotheses. Chosen statistic. Sampling distribution for X 2. X 2 obt above zero. APA style. Plain English. Inferring back to the population. Goodness of fit for three levels. Goodness of fit with unequal expectations. One-way X 2 on SPSS. APA-style results section. Two-way X 2: Test of independence. Null and alternate hypotheses. Chosen statistic. Sampling distribution. Significantly related. APA style. Strength of effect. Plain English. Inference to the real population. Two-way X 2 in SPSS. APA-style results section. Conceptual Items. Application Items. Computational formulas in this chapter. References. PART V: APPENDICES. Appendix A. ANOVA: One-Way, Repeated-Measures Using SPSS. Testing the same participants. One-way, repeated-measures ANOVA on SPSS. Post-hoc testing. APA-style results section. Conceptual Items. Application Items. Computational formula in this appendix. Appendix B. Multiple Regression. More than one predictor variable. Multiple regression on SPSS. APA-style results section. Summary of multiple regression. Conceptual Items. Application Items. z-table. t-table. F-table. q-table. Correlation table. X table. Answers to odd-numbered items.