by James Jaccard and Michael A. Becke
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Now your students can become intelligent consumers of scientific research, without being overwhelmed by the statistics! Jaccard and Becker's text teaches students the basic skills for analyzing data and helps them become intelligent consumers of scientific information. Praised for its real-life applications, the text tells students when to use a particular statistic, why they should use it, and how the statistic should be computed and interpreted. Because many students, given a set of data, cannot determine where to begin in answering relevant research questions, the authors explicate the issues involved in selecting a statistical test. Each statistical technique is introduced by giving instances where the test is most typically applied followed by an interesting research example (each example is taken from psychology literature).
Benefits:
Author Bio
Jaccard, James : State University of New York, Albany
Becke, Michael A. : Pennsylvania State University, Harrisburg
PART I: STATISTICAL PRELIMINARIES.
1. Introduction and Mathematical Preliminaries.
2. Frequency and Probability Distributions.
3. Measures of Central Tendency and Variability.
4. Percentiles, Percentile Ranks, Standard Scores, and the Normal Distribution.
5. Pearson Correlation and Regression: Descriptive Aspects.
6. Probability.
7. Estimation and Sampling Distributions.
8. Hypothesis Testing: Inferences About a Single Mean.
PART II: THE ANALYSIS OF BIVARIATE RELATIONSHIPS.
9. Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships.
10. Independent Groups t Test.
11. Correlated Groups t Test.
12. One-Way Between-Subjects Analysis of Variance.
13. One-Way Repeated Measures Analysis of Variance.
14. Pearson Correlation and Regression: Inferential Aspects.
15. Chi-Square Test.
16. Nonparametric Statistics.
PART III: ADDITIONAL TOPICS.
17. Two-Way Between-Subjects Analysis of Variance.
18. Overview and Extension: Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships and Procedures for More Complex Designs.
James Jaccard and Michael A. Becke
ISBN13: 978-0534569259Now your students can become intelligent consumers of scientific research, without being overwhelmed by the statistics! Jaccard and Becker's text teaches students the basic skills for analyzing data and helps them become intelligent consumers of scientific information. Praised for its real-life applications, the text tells students when to use a particular statistic, why they should use it, and how the statistic should be computed and interpreted. Because many students, given a set of data, cannot determine where to begin in answering relevant research questions, the authors explicate the issues involved in selecting a statistical test. Each statistical technique is introduced by giving instances where the test is most typically applied followed by an interesting research example (each example is taken from psychology literature).
Benefits:
Author Bio
Jaccard, James : State University of New York, Albany
Becke, Michael A. : Pennsylvania State University, Harrisburg
Table of Contents
PART I: STATISTICAL PRELIMINARIES.
1. Introduction and Mathematical Preliminaries.
2. Frequency and Probability Distributions.
3. Measures of Central Tendency and Variability.
4. Percentiles, Percentile Ranks, Standard Scores, and the Normal Distribution.
5. Pearson Correlation and Regression: Descriptive Aspects.
6. Probability.
7. Estimation and Sampling Distributions.
8. Hypothesis Testing: Inferences About a Single Mean.
PART II: THE ANALYSIS OF BIVARIATE RELATIONSHIPS.
9. Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships.
10. Independent Groups t Test.
11. Correlated Groups t Test.
12. One-Way Between-Subjects Analysis of Variance.
13. One-Way Repeated Measures Analysis of Variance.
14. Pearson Correlation and Regression: Inferential Aspects.
15. Chi-Square Test.
16. Nonparametric Statistics.
PART III: ADDITIONAL TOPICS.
17. Two-Way Between-Subjects Analysis of Variance.
18. Overview and Extension: Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships and Procedures for More Complex Designs.