Basic Statistics for the Behavioral Sciences

ISBN-10: 061852813X

ISBN-13: 9780618528134

Edition: 5th 2006

Authors: Gary W. Heiman
List price: $203.95 Buy it from $3.00
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Description: "Basic Statistics for the Behavioral Sciences "demystifies and fully explains statistics without leaving out relevant topics or simply presenting formulas, in a format that is non-threatening and inviting to students. Gary Heiman has written a textbook--clearly, patiently, and with an occasional touch of humor--that teaches students not only "how "to compute an answer on demand, but also "why "they should perform the procedure or what their answer reveals about the data. Heiman has achieved five objectives in writing this text: to take a conceptual-intuitive approach, to present statistics within an understandable research context, to deal directly and positively with student weaknesses in mathematics, to introduce new terms and concepts in an integrated way, and to create a text that students will enjoy as well as learn from!Appendix B explains the basics of how to use SPSS to analyze data. Tips on using SPSS are integrated throughout the text and now have a specific index to guide students."A Quick Review" features contain a simple review of previous concepts, additional examples, and study questions.A section on "Statistics in Published Research" helps students gain a perspective on how researchers use statistics and relates what students have learned in the chapter to what they will see (and won't see) when reading published research. (Includes using the APA format for stats.)Additional pedagogical features include a "Getting Started" section at the beginning of each chapter, "Statistical Notation" sections, "Remember" callout sections, computation formulas, "Putting It All Together" sections, chapter summaries, and summaries of formulas.

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Book details

List price: $203.95
Edition: 5th
Copyright year: 2006
Publisher: Wadsworth
Publication date: 7/8/2005
Binding: Hardcover
Pages: 528
Size: 8.00" wide x 10.00" long x 1.00" tall
Weight: 2.794
Language: English

Introduction to Statistics
Why Is It Important to Learn
Statistics (and How Do You Do That?)
Review of Mathematics Used in Statistics
Statistics and the Research Process
The Logic of Research
Samples and Populations
Applying Descriptive and Inferential Statistics
Understanding Experiments and Correlational Studies
The Characteristics of Scores
Statistics in Published Research
Using Statistical Terms
Frequency Distributions and Percentiles
New Statistical Notation
Why Is It Important to Know about Frequency Distributions?
Simple Frequency Distributions
Types of Frequency Distributions
Relative Frequency and the Normal Curve
Computing Cumulative Frequency and Percentile
Statistics in Published Research: APA Publication Rules
A Word about Grouped Frequency Distributions
Measures of Central Tendency
The Mean, Median, and Mode New Statistical Notation
Why Is It Important to Know about Central Tendency?
What Is Central Tendency?
The Mode
The Median The Mean
Transformations and the Mean Deviations around the Mean
Describing the Population Mean
Summarizing an Experiment
Statistics in Published Research: Using the Mean
Measures of Variability: Range, Variance, and Standard Deviation
New Statistical Notation
Why Is It Important to Know about Measures of Variability?
The Range
Understanding the Variance and Standard Deviation
Computing the Sample Variance
Sample Standard Deviation
The Population Variance and the Population
Standard Deviation
Summary of the Variance and Standard Deviation
Applying the Variance and Standard Deviation to Research
Statistics in Published Research
Reporting Variability
z-Scores and the Normal Curve Model
New Statistical Notation
Why Is It Important to Know about z-Scores?
Understanding z-Scores
Interpreting z-Scores
Using the z-Distribution
Using z-Scores to Compare
Different Variables
Using z-Scores to Determine the Relative
Frequency of Raw Scores
Statistics in Published Research: Using z-Scores
Using z-Scores to Describe Sample Means
The Correlation Coefficient
New Statistical Notation
Why Is It Important to Know about Correlation Coefficients?
Understanding Correlational Research
Types of Relationships
Strength of the Relationship
The Pearson Correlation Coefficient
The Restriction of Range
Problem Correlations in the Population
Statistics in Published Research
Correlation Coefficients
Linear Regression
New Statistical Notation
Why Is It Important to Know about Linear Regression?
Understanding Linear Regression
The Linear Regression Equation
Describing the Errors in Prediction
Computing the Proportion of Variance Accounted For
A Word About Multiple Correlation
Regression Statistics in Published Research
Linear Regression
Using Probability to Make Decisions about Data
New Statistical Notation
Why Is It Important
Know about Probability?
The Logic of Probability
Computing Probability
Obtaining Probability from the Standard
Normal Curve Random Sampling
Sampling Error Deciding
Whether a Sample Represents a Population
Introduction to Hypothesis Testing
New Statistical Notation
Why Is It Important to Know about the z-Tests?
The Role of Inferential
Statistics in Research
Setting Up Inferential Procedures
Performing the z-Test
Interpreting Significant Results
Interpreting Nonsignificant
Results Summary of the z-Test
Statistics in Published Research
Reporting Significance Tests
The One-Tailed Test
Errors in Statistical Decision Making
Performing the One-Sample t-Test
Testing Correlation Coefficients
New Statistical Notation
Why Is It Important to Know about t-Tests?
Performing the One-Sample t-Test Estimating
Computing a Confidence Interval
Statistics in Published Research
Reporting the t-Test
Significance Tests for Correlation Coefficients
Maximizing the Power of Statistical Tests
The Two-Sample t-Test
New Statistical Notation
Why Is It Important to Know about the Two-Sample t-Test?
Understanding the Two-Sample Experiment
The Independent-Samples t-Test
Summary of the Independent-Samples t-Test
The Related-Samples t-Test
Summary of the Related-Samples t-Test
Describing the Relationship in a Two-Sample Experiment
Statistics in Published Research: The Two-Sample Experiment
The One-Way Analysis of Variance
New Statistical Notation
Why Is It Important to Know about ANOVA?
An Overview of ANOVA
Components of the ANOVA
Performing the ANOVA
Performing Post
Hoc Comparisons
Summary of Steps in Performing a One-Way ANOVA
Additional Procedures in the One-Way ANOVA
Statistics in Published Research: Reporting ANOVA
The Two-Way Analysis of Variance
New Statistical Notation
Why Is It Important to Know about the Two-Way ANOVA?
Understanding the Two-Way Design
Overview of the Two-Way
Between-Subjects ANOVA Computing the Two-Way
ANOVA Interpreting the Two-Way Experiment
Summary of the Steps in Performing a Two-Way ANOVA
Statistics in Published Research: Reporting ANOVA
Chi Square and Other Nonparametric Procedures
New Statistical Notation
Why Is It Important to Know about Nonparametric Procedures?
Chi Square Procedures
One-Way Chi Square
The Two-Way Chi Square
Statistics in Published Research
Reporting Chi Square Nonparametric
Procedures for Ranked Data
Appendices
Additional Statistical Formulas
Using SPSS
Statistical Tables
Answers to Odd-Numbered Questions
Table of Contents provided by Publisher. All Rights Reserved.
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