Statistics for the Behavioral Sciences

ISBN-10: 0534569250
ISBN-13: 9780534569259
Edition: 4th 2002 (Revised)
List price: $234.95
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Description: 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  More...

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Book details

List price: $234.95
Edition: 4th
Copyright year: 2002
Publisher: Wadsworth
Publication date: 10/29/2001
Binding: Hardcover
Pages: 688
Size: 7.50" wide x 9.25" long x 1.25" tall
Weight: 2.970
Language: English

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).

Monsignor Michael A. Becker is pastor of St. John the Evangelist Church in Altoona, Pennsylvania, and serves as sacramental minister at the Altoona Campus of Penn State University. He currently teaches homiletics at St. Vincent Seminary in Latrobe.

Preface
To the Student
Statistical Preliminaries
Introduction and Mathematical Preliminaries
The Study of Statistics
Research in the Behavioral Sciences
Variables
Measurement
Discrete and Continuous Variables
Populations and Samples
Biased Sampling
Descriptive and Inferential Statistics
The Concept of Probability
Mathematical Preliminaries: A Review
Statistics and Computers
Summary
Frequency and Probability Distributions
Frequency Distributions for Quantitative Variables: Ungrouped Scores
Frequency Distributions for Quantitative Variables: Grouped Scores
Frequency Distributions for Qualitative Variables
Outliers
Frequency Graphs
Misleading Graphs
Graphs of Relative Frequencies, Percentages, Cumulative Frequencies, and Cumulative Relative Frequencies
Probability Distributions
Empirical and Theoretical Distributions
Method of Presentation
Examples from the Literature
Summary
Measures of Central Tendency and Variability
Measures of Central Tendency for Quantitative Variables
Measures of Variability for Quantitative Variables
Computational Formula for the Sum of Squares
Relationship Between Central Tendency and Variability
Graphs of Central Tendency and Variability
Measures of Central Tendency and Variability for Qualitative Variables
Skewness and Kurtosis
Sample Versus Population Notation
Method of Presentation
Example from the Literature
Summary
Percentiles, Percentile Ranks, Standard Scores, and the Normal Distribution
Percentiles and Percentile Ranks
Standard Scores
Standard Scores and the Normal Distribution
Standard Scores and the Shape of the Distribution
Method of Presentation
Summary
The Normal Distribution Formula
Pearson Correlation and Regression: Descriptive Aspects
Use of Pearson Correlation
The Linear Model
The Pearson Correlation Coefficient
Correlation and Causation
Interpreting the Magnitude of a Correlation Coefficient
Regression
Additional Issues Associated with the Use of Correlation and Regression
Summary
Probability
Probabilities of Simple Events
Conditional Probabilities
Joint Probabilities
Adding Probabilities
Relationships Among Probabilities
Sampling with Versus Without Replacement
Beliefs and Probability Theory
Counting Rules
The Binomial Expression
Summary
Estimation and Sampling Distributions
Finite Versus Infinite Populations
Estimation of the Population Mean
Estimation of the Population Variance and Standard Deviation
Degrees of Freedom
Sampling Distribution of the Mean and the Central Limit Theorem
Polls and Random Samples
Types of Sampling Distributions
Summary
Hypothesis Testing: Inferences About a Single Mean
A Simple Analogy for Principles of Hypothesis Testing
Statistical Inference and the Normal Distribution: The One-Sample z Test
Defining Expected and Unexpected Results
Failing to Reject Versus Accepting the Null Hypothesis
Type I and Type II Errors
Effects of Alpha and Sample Size on the Power of Statistical Tests
Statistical and Real-World Significance
Directional Versus Nondirectional Tests
Statistical Inference Using Estimated Standard Errors: The One-Sample t Test
Confidence Intervals
Method of Presentation
Examples from the Literature
Summary
The Analysis of Bivariate Relationships
Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships
Principles of Research Design: Statistical Implications
Confounding and Disturbance Variables
Selecting the Appropriate Statistical Test to Analyze a Relationship: A Preview
Summary
Independent Groups t Test
Use of the Independent Groups t Test
Inference of a Relationship Using the Independent Groups t Test
Strength of the Relationship
Nature of the Relationship
Methodological Considerations
Numerical Example
Planning an Investigation Using the Independent Groups t Test
Method of Presentation
Examples from the Literature
Summary
Correlated Groups t Test
Use of the Correlated Groups t Test
Inference of a Relationship Using the Correlated Groups t Test
Strength of the Relationship
Nature of the Relationship
Methodological Considerations
Power of Correlated Groups Versus Independent Groups t Tests
Numerical Example
Planning an Investigation Using the Correlated Groups t Test
Method of Presentation
Examples from the Literature
Summary
Computational Procedures for the Nullified Score Approach
One-Way Between-Subjects Analysis of Variance
Use of One-Way Between-Subjects Analysis of Variance
Inference of a Relationship Using One-Way Between-Subjects Analysis of Variance
Relationship of the F Test to the t Test
Strength of the Relationship
Nature of the Relationship
Unstandardized Effect Sizes and Confidence Intervals
Methodological Considerations
Numerical Example
Planning an Investigation Using One-Way Between-Subjects Analysis of Variance
Method of Presentation
Examples from the Literature
Summary
Rationale for the Degrees of Freedom
One-Way Repeated Measures Analysis of Variance
Use of One-Way Repeated Measures Analysis of Variance
Inference of a Relationship Using One-Way Repeated Measures Analysis of Variance
Strength of the Relationship
Nature of the Relationship
Unstandardized Effect Size and Confidence Intervals
Methodological Considerations
Numerical Example
Planning an Investigation Using One-Way Repeated Measures Analysis of Variance
Method of Presentation
Examples from the Literature
Summary
Determining the Nature of the Relationship Under Sphericity Violations
Pearson Correlation and Regression: Inferential Aspects
Use of Pearson Correlation
Inference of a Relationship Using Pearson Correlation
Strength of the Relationship
Confidence Intervals for the Correlation Coefficient
Nature of the Relationship
Planning an Investigation Using Pearson Correlation
Method of Presentation for Pearson Correlation
Examples from the Literature
Regression
Numerical Example
Method of Presentation for Regression
Summary
Testing Null Hypotheses Other Than [rho] = 0
Confidence Intervals for the Correlation Coefficient
Chi-Square Test
Use of the Chi-Square Test
Two-Way Contingency Tables
Chi-Square Tests of Independence and Homogeneity
Inference of a Relationship Using the Chi-Square Test
2 x 2 Tables
Strength of the Relationship
Nature of the Relationship
Methodological Considerations
Numerical Example
Use of Quantitative Variables in the Chi-Square Test
Planning an Investigation Using the Chi-Square Test
Method of Presentation
Examples from the Literature
Chi-Square Goodness-of-Fit Test
Summary
Determining the Nature of the Relationship Using a Modified Bonferroni Procedure
Nonparametric Statistics
Rank Scores
Nonparametric Statistics and Outliers
Analysis of Ranked Data Using Parametric Formulas
Rank Tests for Two Independent Groups
Rank Test for Two Correlated Groups
Rank Test for Three or More Independent Groups
Rank Test for Three or More Correlated Groups
Rank Test for Correlation
Examples from the Literature
Summary
Corrections for Ties for Nonparametric Rank Tests
Additional Topics
Two-Way Between-Subjects Analysis of Variance
Factorial Designs
Use of Two-Way Between-Subjects Analysis of Variance
The Concepts of Main Effects and Interactions
Inference of Relationships Using Two-Way Between-Subjects Analysis of Variance
Strength of the Relationships
Nature of the Relationships
Methodological Considerations
Numerical Example
Unequal Sample Sizes
Planning an Investigation Using Two-Way Between-Subjects Analysis of Variance
Method of Presentation
Examples from the Literature
Summary
Overview and Extension: Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships and Procedures for More Complex Designs
Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships
Case I: The Relationship Between Two Qualitative Variables
Case II: The Relationship Between a Qualitative Independent Variable and a Quantitative Dependent Variable
Case III: The Relationship Between a Quantitative Independent Variable and a Qualitative Dependent Variable
Case IV: The Relationship Between Two Quantitative Variables
Procedures for More Complex Designs
Alternative Approaches to Null Hypothesis Testing
Summary
Table of Random Numbers
Proportions of Scores in a Normal Distribution
Factorials
Critical Values for the t Distribution
Power and Sample Size
Critical Values for the F Distribution
Studentized Range Values (q)
Critical Values for Pearson r
Fisher's Transformation of Pearson r(r')
Critical Values for the Chi-Square Distribution
Critical Values for the Mann-Whitney U Test
Critical Values for the Wilcoxon Signed-Rank Test
Critical Values for Spearman r
Formulas for Unbiased Estimators of Proportion of Explained Variance
Answers to Selected Exercises
Glossary of Major Symbols
References
Index
Credits

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