# Fundamental Statistics for the Behavioral Sciences, 7th Edition

**David C. Howell****ISBN-10:**0495811254**ISBN-13:**9780495811251- 672 Pages | Hardcover
- Previous Editions: 2008, 2004, 1999
- COPYRIGHT: 2011 Published

**David C. Howell****ISBN-10:**0495811254**ISBN-13:**9780495811251- 672 Pages | Hardcover
- Previous Editions: 2008, 2004, 1999
- COPYRIGHT: 2011 Published

David Howell's practical approach focuses on the context of statistics in behavioral research, with an emphasis on looking at data before jumping into a test. This provides students with an understanding of the logic behind the statistics: why and how certain methods are used rather than just doing techniques by rote. Students move beyond number crunching to discover the meaning of statistical results and how they relate to the research questions being asked. FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES contains an abundance of real data and research studies as a base and moves through an analysis of data.

- The authors' clarity of writing, clear definition of terms, and use of worked out examples helps the student understand some of the more difficult concepts in statistics.
- The text is full of applications: Real data is used in ALL examples. This puts a real life perspective on the materials for the students and allows for much greater understanding. The applications are listed on the inside front covers.
- Computer output from SPSS is included so that students can cross check their own work for accuracy.
- Formulas used in the book are definitional rather than for purposes of calculation, as Howell believes formulas are there to help students define the concepts.
- Hundreds of exercises, most of which are based on data from published research, promote student interest and provide the context of statistics in behavioral research.

1. Introduction.

The importance of Context. Basic Terminology. Selection among Statistical Procedures. Using Computers. Summary. Exercises.

2. Basic Concepts.

Scales of Measurement. Variables. Random Sampling. Notation. Summary. Exercises.

3. Displaying Data.

Plotting Data. Stem-and-Leaf Displays. Histograms. Reading Graphs. Alternative Methods of Plotting Data. Describing Distributions. Using Computer Programs to Display Data. Summary. Exercises.

4. Measures of Central Tendency.

The Mode. The Median. The Mean. Relative Advantages of the Mode, the Median, and the Mean. Obtaining Measures of Central Tendency Using SPSS. A Simple Demonstration-Seeing Statistics. Summary. Exercises.

5. Measures of Variability.

Range. Interquartile Range and Other Range Statistics. The Average Deviation. The Variance. The Standard Deviation. Computational Formulae for the Variance and the Standard eviation. The Mean and the Variance as Estimators. Boxplots: Graphical Representations of Dispersion and Extreme Scores. A Return to Trimming. Obtaining Measures of Dispersion Using SPSS. A Final Worked Example. Seeing Statistics. Summary. Exercises.

6. The Normal Distribution.

The Normal Distribution. The Standard Normal Distribution. Setting Probable Limits on an Observations. Measures Related to z. Seeing Statistics. Summary. Exercises.

7. Basic Concepts of Probability.

Probability. Basic Terminology and Rules. The Application of Probability to Controversial Issues. Writing Up the Results. Discrete versus Continuous Variables. Probability Distributions for Discrete Variables. Probability Distributions for Continuous Variables. Summary. Exercises.

8. Sampling Distributions and Hypothesis Testing.

Two Simple Examples Involving Course Evaluations and Rude Motorists. Sampling Distributions. Hypothesis Testing. The Null Hypothesis. Test Statistics and Their Sampling Distributions. Using the Normal Distribution to Test Hypotheses. Type I and Type II Errors. One- and Two-Tailed Tests. Seeing Statistics. A Final Worked Example. Back to Course Evaluations and Rude Motorists. Summary. Exercises.

9. Correlation.

Scatter Diagrams. The Relationship Between Pace of Life and Heart Disease. The Covariance. The Pearson Product-Moment Correlation Coefficient (r). Correlations with Ranked Data. Factors that Affect the Correlation. Beware Extreme Observations. Correlation and Causation. If Something Looks Too Good to Be True, Perhaps It Is. Testing the Significance of a Correlation Coefficient. Intercorrelation Matrices. Other Correlation Coefficients. Using SPSS to Obtain Correlation Coefficients. Seeing Statistics. A Final Worked Example. Summary . Exercises.

10. Regression.

The Relationship Between Stress and Health. The Basic Data. The Regression Line. The Accuracy of Prediction. The Influence of Extreme Values. Hypothesis Testing in Regression. Computer Solutions using SPSS. Seeing Statistics. Summary. Exercises.

11. Multiple Regression.

Overview. A Different Data Set. Residuals. The Visual Representation of Multiple Regression. Hypothesis Testing. Refining the Regression Equation. A Second Example: Height and Weight. A Third Example: Psychological Symptoms in Cancer Patients. Summary. Exercises.

12. Hypothesis Testing Applied to Means: One Sample.

Sampling Distribution of the Mean. Testing Hypotheses about Means When ƒã is Known. Testing a Sample Mean When ƒã is Unknown (The One-Sample t). Factors that Affect the Magnitude of t and the Decision about H0. A Second Example: The Moon Illusion. How Large is Our Effect?. Confidence Limits on the Mean. Using SPSS to Run One-Sample t tests. A Final Worked Example. Seeing Statistics. Summary. Exercises.

13. Hypothesis Tests Applied to Means: Two Related Samples.

Related Samples. Student''s t Applied to Difference Scores. A Second Example: The Moon Illusion Again. Advantages and Disadvantages of Using Related Samples. How Large an Effect Have We Found?. Confidence Limits on Changes. Using SPSS for t Tests on Related Samples. Writing Up the Results. Summary. Exercises.

14. Hypothesis Tests Applied to Means: Two Independent Samples.

Distribution of Differences Between Means. Heterogeneity of Variance. Nonnormality of Distributions. A Second Example with Two Independent Samples. Effect Sizes Again. Confidence Limits on ƒÝ1 ¡V ƒÝ2. Writing Up the Results. Use of Computer Programs for Analysis of Two Independent Sample Means. A Final Worked Example. Seeing Statistics. Summary. Exercises.

15. Power.

The Basic Concept. Factors that Affect the Power of a Test. Effect Size. Power Calculations for the One-Sample t Test. Power Calculations for Differences Between Two Independent Means. Power Calculations for the t Test for Related Samples. Power Considerations in Terms of Sample Size. You Don''t Have to Do It by Hand. Seeing Statistics. Summary. Exercises.

16. One-Way Analysis of Variance.

The General Approach. The Logic of the Analysis of Variance. Calculations for the Analysis of Variances. Unequal Sample Sizes. Multiple Comparison Procedures. Violations of Assumptions. The Size of the Effects. Writing Up the Results. The Use of SPSS for a One-Way Analysis of Variance. A Final Worked Example. Seeing Statistics. Summary. Exercises.

17. Factorial Analysis of Variance Factorial Designs. The Extension of the Eysenck Study. Interactions. Simple Effects. Measures of Association and Effect Size. Reporting the Results. Unequal Sample Sizes. A Second Example: Maternal Adaptation Revisited. Using SPSS for Factorial Analysis of Variance. Seeing Statistics. Summary. Exercises.

18. Repeated-Measures Analysis of Variance.

An Example: Depression as a Response to an Earthquake. Multiple Comparisons. Effect Size. Assumptions involved in Repeated-Measures Designs. Advantages and Disadvantages of Repeated-Measures Designs. Using SPSS to Analyze Data in a Repeated-Measures Design. Writing Up the Results. A Final Worked Example. Summary. Exercises.

19. Chi-Square.

One Classification Variable: The Chi-Square Goodness of Fit Test. Two Classification Variables: Analysis of Contingency Tables. Possible Improvements on Standard Chi-Square. Chi-Square for Larger Contingency Tables. The Problem of Small Expected Frequencies. The Use of Chi-Square as a Test of Proportions. Nonindependent Observations. SPSS Analysis of Contingency Tables. Measures of Effect Size. A Final Worked Example. Writing Up the Results. Seeing Statistics. Summary. Exercises.

20. Nonparametric and Distribution-Free Statistical Tests.

The Mann-Whitney Test. Wilcoxon''s Matched-Pairs Signed-Ranks Test. Kruskal-Wallis One-Way Analysis of Variance. Friedman''s Rank Test for k Correlated Samples. Measures of Effect Size. Writing Up the Results. Summary. Exercises.

21. Choosing the Appropriate Analysis.

Exercises and Examples.

Appendix A Arithmetic Review.

Appendix B Symbols and Notation.

Appendix C Basic Statistical Formulae.

Appendix D Dataset.

Appendix E Statistical Tables.

Glossary.

References.

Answers to Selected Exercises.

Index.

- Each chapter begins with a box suggesting terms that students will need to use in this chapter that were introduced in previous chapters. Sometimes you will see the terms come back several times in successive chapters. These tend to be the terms that students have the hardest time keeping straight.
- The questions that previously began each chapter have been turned into the first paragraph of the chapter.
- Throughout the book, but especially in earlier chapters, boxes are inserted that either pull together important terms or make a summarizing statement. These boxes highlight the stuff students need to attend to as they continue reading. For example:
- Remember that the standard error of a statistic is the standard deviation of the values that we obtain for that statistic over repeated sampling.
- Especially in the early chapters, terms are redefined when used a second, third, or fourth time. For example, "you will see that I have plotted something-or-other on the X (horizontal) axis." Or, "whether it be the mode (the most common value), the median (the middle value), or the mean, …." Or "In this case the population variance) is …" (Underlining used here only to identify definition) People often forget which is the X axis, and they need to be constantly reminded that the notation for the population variance is.

All supplements have been updated in coordination with the Main title.

Please see Main title page for new to this edition information.

Cengage Advantage Books: Fundamental Statistics for the Behavioral Sciences
(ISBN-10: 0840032978 | ISBN-13: 9780840032973)

eBank Electronic Transparency (ISBN-10: 0538793422 | ISBN-13: 9780538793421)

David Howell's practical approach focuses on the context of statistics in behavioral research, with an emphasis on looking at data before jumping into a test. This provides students with an understanding of the logic behind the statistics: why and how certain methods are used rather than just doing techniques by rote. Students move beyond number crunching to discover the meaning of statistical results and how they relate to the research questions being asked. FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES contains an abundance of real data and research studies as a base and moves through an analysis of data.

Aplia (ISBN-10: 1111303215 | ISBN-13: 9781111303211)eBank Electronic Transparency (ISBN-10: 0538793422 | ISBN-13: 9780538793421)

Cengage Advantage Books: Fundamental Statistics for the Behavioral Sciences
(ISBN-10: 0840032978 | ISBN-13: 9780840032973)

David Howell's practical approach focuses on the context of statistics in behavioral research, with an emphasis on looking at data before jumping into a test. This provides students with an understanding of the logic behind the statistics: why and how certain methods are used rather than just doing techniques by rote. Students move beyond number crunching to discover the meaning of statistical results and how they relate to the research questions being asked. FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES contains an abundance of real data and research studies as a base and moves through an analysis of data.

Aplia (ISBN-10: 1111303215 | ISBN-13: 9781111303211)

Aplia, 2 terms Instant Access (ISBN-10: 1111927758 | ISBN-13: 9781111927752)

Aplia, 2 terms Instant Access (ISBN-10: 1111927758 | ISBN-13: 9781111927752)

Succeed in your course with 2 semesters of access to Aplia's interactive learning system--featuring practice problems with immediate feedback and tools developed specifically for FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES, 7th Edition, including step-by-step explanations that help you improve your reasoning and skills, interactive assignments that help you understand difficult or counterintuitive concepts, and more. Aplia has already helped more than a million students succeed in college classes.

LMS Integrated for Aplia, 1 term Instant Access (ISBN-10: 1285312457 | ISBN-13: 9781285312453)Succeed in your behavioral sciences course with one full semester of access to Aplia's interactive learning system--featuring practice problems with immediate feedback and tools developed specifically for FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES, 7th Edition. Aplia has already helped more than a million students succeed in college classes.

Aplia, 1 term Instant Access (ISBN-10: 1428273816 | ISBN-13: 9781428273818)Succeed in your course with 1 semester of access to Aplia's interactive learning system--featuring practice problems with immediate feedback and tools developed specifically for FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES, 7th Edition, including step-by-step explanations that help you improve your reasoning and skills, interactive assignments that help you understand difficult or counterintuitive concepts, and more. Aplia has already helped more than a million students succeed in college classes.

Solutions Manual (ISBN-10: 0495911690 | ISBN-13: 9780495911692)