Statistical Analysis for Education and Psychology Researchers Tools for Researchers in Education and Psychology 1st edition by Ian Peers 9781135717513 1135717516
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Authors:Ian Peers , Series:Psychology [48] , Tags:Education; General; Research; Mathematics; Probability & Statistics; Psychology; Research & Methodology , Author sort:Peers, Ian , Ids:9781135717520 , Languages:Languages:eng , Published:Published:Feb 2006 , Publisher:Routledge , Comments:Comments:Basic statistical concepts such as probability, estimation and inference, and their role in research design and analysis are presented in this volume. The author demonstrates which statistical test to use in given circumstances and how to use it, drawing on data from psychology and education.; Written for those without a strong mathematical background, the book’s examples can be worked using a pocket calculator. “Real life” data are analyzed using statistical software (SAS), output is interpreted, and a decision chart is presented which summarizes considerations when choosing a statistical test.
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ISBN 10:1135717516
ISBN 13:9781135717513
Author:Ian Peers
Basic statistical concepts such as probability, estimation and inference, and their role in research design and analysis are presented in this volume. The author demonstrates which statistical test to use in given circumstances and how to use it, drawing on data from psychology and education.; Written for those without a strong mathematical background, the book’s examples can be worked using a pocket calculator. “Real life” data are analyzed using statistical software (SAS), output is interpreted, and a decision chart is presented which summarizes considerations when choosing a statistical test.
Statistical Analysis for Education and Psychology Researchers Tools for Researchers in Education and Psychology 1st Table of contents:
Chapter 1: Statistics and Research Design
1.1. Why Consider Research Design In a Text About Statistics?
1.2. Surveys
1.3. Experimental Research
Summary
Chapter 2: Measurement Issues
2.1. Measurement In Educational Research
2.2. Properties of Measurement Scales
2.3. Practical Decisions About Measurement
2.4. Psychological Tests and Scales
Summary
Chapter 3: Initial Data Analysis
3.1. Data Processing
3.2. Data Cleaning
3.3. Describing Distributions
3.4. Descriptive Statistics
3.5. Statistics As Estimators
3.6. Statistical Models
Summary
Case Study
Task
Chapter 4: Probability and Inference
4.1. Research Process
4.2. Statistical Probability
4.3. Sampling Distributions
4.4. Discrete Random Variables
4.5. From Sample to Population
4.6. Continuous Random Variables
4.7. Hypothesis Testing
4.8. Errors In Decision Making
4.9. Statistical Inference In Context
Summary
Chapter 5: Choosing a Statistical Test
5.1. General Considerations
5.2. From IDA to Inferential Analysis
5.3. Choosing a Statistical Test
5.4. Statistical Power
5.5. Checking for Normality
Summary
Chapter 6: Inferences Involving Binomial and Nominal Count Data
Introduction
6.1. Chi-Square Tests for Contingency Tables
6.2. Binomial Test
6.3. Fisher’s Exact Test
6.4. Proportions Test (Or Difference In Percentages)
6.5. Sign Test (Matched Pairs)
6.6. r×k Chi-Square Test
6.7. Cochran’s Q Test
6.8. Summary
Chapter 7: Inferences Involving Rank Data
Introduction
7.1. Correlation an Overview
7.2. Spearman’s Rho (Rank Order Correlation Coefficient)
7.3. One-Sample Runs Test for Randomness
7.4. Wilcoxon Mann-Whitney Test (Also Called Wilcoxon’s Rank Sum Test)
7.5. Wilcoxon Signed Ranks Test (For Related Data)
7.6. Kruskal-Wallis One-Way ANOVA
7.7. Friedman’s ANOVA By Ranks (For Related Data)
Summary
Chapter 8: Inferences Involving Continuous Data
Introduction
8.1. Introduction to Regression and Correlation
8.2. Linear Regression Analysis
8.3. Pearson’s Correlation r
8.4. Independent t-test (Unrelated Two Sample Procedure)
8.5. Paired t-test (Related)
8.6. Introduction to Analysis of Variance (ANOVA)
8.7. One-Way ANOVA F-Test (Unrelated)
8.8. One-Way ANOVA F-Test (Related)
8.9. Two-Way ANOVA 2×2 Factorial (Unrelated) Two Factors With Two Levels for Each Factor
8.10. Split-Plot ANOVA
8.11. What Can Be Done When Assumptions of Homogeneity of Variance and Normality of Residuals Are Not Met?
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