Statistics for the Behavioral Sciences

Erscheinungsjahr 2011
ISBN: 978-1-4129-6931-4
Verlag: SAGE Publications

Buch, Englisch, 736 Seiten, Format (B × H): 203 mm x 254 mm

An engaging introduction to statistics, the text provides readers with a tool for learning about behaviour without requiring a strong background in research methods. This comprehensive, yet conversational, text includes making sense sections to help relate and explain material that is often difficult for students to comprehend. The book provides instructions for using SPSS statistical software in each chapter with helpful examples and over 100 screen shots. Gregory Privitera takes a user-friendly approach while balancing statistical theory, computation, and application with the technical instruction needed for students to succeed in the modern era of data collection, analysis, and statistical interpretation.


Key Features



- 'making sense' sections break down the most difficult concepts in statistics for students, review important material, and basically “make sense” of the most challenging material. These sections are aimed at easing student stress, and making statistics more approachable.
- 'research in focus' sections in Chapters 1 through 7 provide context by reviewing pertinent, current research that makes sense of or illustrates important statistical concepts discussed in the chapter. This feature prepares students to read research articles by providing examples on how a particular statistical method is reported.
-“SPSS in focus” sections provide step-by-step, classroom-tested instruction using practical research examples for how the concepts taught in each chapter can be applied using SPSS. Students are supported with screen shot figures and explanations for how to read SPSS output.
- numerous opportunities for practice are found in the 32-38 problems at the ends of each chapter. These are divided into different kinds of problems (factual problems, concept and application problems, and problems in research) categorized for easier identification and flexibility of assessment by instructors.

Autoren/Hrsg.

Privitera, Gregory J.

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Sozialwissenschaften Psychologie Psychologie / Allgemeines & Theorie Psychologische Forschungsmethoden

Inhaltsverzeichnis

SPSS Prefix: General Overview and Guide for Using SPSS
Overview of SPSS: What are you looking at?
Preview of SPSS in Focus
Chapter 1—Introduction to Statistics
1.1 Descriptive and inferential statistics
1.2 Statistics in research
1.3 Scales of measurement
1.4 Types of data
1.5 Research in Focus: Types of data and scales of measurement
1.6 SPSS in Focus: Entering and defining variables
Chapter 2—Summarizing Data: Tables, Graphs, and Distributions
2.1 Why summarize data?
2.2 Frequency distributions for grouped data
2.3 SPSS in Focus: Frequency distributions for quantitative data
2.4 Frequency distributions for ungrouped data
2.5 Research in Focus: Summarizing demographic information
2.6 SPSS in Focus: Frequency distributions for categorical data
2.7 Pictorial frequency distributions
2.8 Graphing distributions: Continuous data
2.9 Graphing distributions: Discrete and categorical data
2.10 Research in Focus: Frequencies and percents
2.11 SPSS in Focus: Histograms, bar charts, and pie charts
Chapter 3—Summarizing Data: Central Tendency
3.1 Introduction to central tendency
3.2 Measures of central tendency
3.3 Characteristics of the mean
3.4 Choosing an appropriate measure of central tendency
3.5 Research in Focus: Describing central tendency
3.6 SPSS in Focus: Mean, median, and mode
Chapter 4— Summarizing Data: Variability
4.1 Measuring variability
4.2 Range and midrange
4.3 Research in Focus: Reporting the range
4.4 Measures of variability: Quartiles and interquartiles
4.5 Research in Focus: The “midrange of behavior”
4.6 The variance
4.7 Explaining variance for populations and samples
4.8 The computational formula for variance
4.9 The Standard deviation
4.10 What does the standard deviation tell us?
4.11 Characteristics of the standard deviation
4.12 SPSS in Focus: Range, variance, and standard deviation
Chapter 5— Probability
5.1 Introduction to probability
5.2 Calculating probability
5.3 Probability and relative frequency
5.4 The relationship between multiple outcomes
5.5 Conditional probabilities and Bayes’ Theorem
5.6 SPSS in Focus: Probability tables
5.7 Probability distributions
5.8 The mean of a probability distribution and expected value
5.9 Research in Focus: When are risks worth taking?
5.10 The variance and standard deviation of a probability distribution
5.11 Expected value and the binomial distribution
5.12 A final thought on the likelihood of random behavioral outcomes
Chapter 6— Probability and Normal Distributions
6.1 The normal distribution in behavioral science
6.2 Characteristics of the normal distribution
6.3 Research in Focus: The statistical norm
6.4 The standard normal distribution
6.5 The unit normal table: A brief introduction
6.6 Locating proportions
6.7 Locating scores
6.8 SPSS in Focus: Converting raw scores to standard z-scores
6.9 Going from binomial to normal
6.10 The normal approximation to the binomial distribution
Chapter 7— Probability and Sampling Distributions
7.1 Selecting samples from populations
7.2 Selecting a sample: Who’s in and who’s out?
7.3 Sampling distributions: The mean
7.4 Sampling distributions: The variance
7.5 The standard error of the mean
7.6 Factors that decrease standard error
7.7 SPSS in Focus: Estimating the standard error of the mean
7.8 APA in Focus: Reporting the standard error
7.9 Standard normal transformations with sampling distributions
Chapter 8— Introduction to Hypothesis Testing
8.1 Inferential Statistics and hypothesis testing
8.2 Four steps to hypothesis testing
8.3 Hypothesis testing and sampling distributions
8.4 Making a decision: Types of error
8.5 Testing a research hypothesis: Examples using the z-test
8.6 Research in Focus: Directional versus non-directional tests
8.7 Measuring the size of an effect: Cohen’s d
8.8 Effect size, power, and sample size
8.9 Additional factors that increase power
8.10 SPSS in Focus: A preview for Chapters 9 to 18
8.11 APA in Focus: Reporting the test statistic and effect size
Chapter 9—Testing Means: Independent Sample t-Tests
9.1 Going from z to t
9.2 The degrees of freedom
9.3 Reading the t-table
9.4 One-independent sample t-test
9.5 Effect size for the one-independent sample t-test
9.6 SPSS in Focus: One-independent sample t-test
9.7 Two-independent sample t-test
9.8 Effect size for the two-independent sample t-test
9.9 SPSS in Focus: Two-independent sample t-test
9.10 APA in Focus: Reporting the t-statistic and effect size
Chapter 10—Testing Means: Related Samples t-Test
10.1 Related and independent samples
10.2 Introduction to the related samples t-test
10.3 Related samples t-test: Repeated measures design
10.4 SPSS in Focus: The related samples t-test
10.5 Related samples t-test: Matched pairs design
10.6 Measuring effect size for the related samples t-test
10.7 Advantages for selecting related samples
10.8 APA in Focus: Reporting the t-statistic and effect size for related samples
Chapter 11—Estimation and Confidence Intervals
11.1 Point estimation and interval estimation
11.2 The process of estimation
11.3 Estimation for the one-independent sample z-test
11.4 Estimation for the one-independent sample t-test
11.5 SPSS in Focus: Confidence intervals for the one-independent t-test
11.6 Estimation for the two-independent sample t-test
11.7 SPSS in Focus: Confidence intervals for the two-independent t-test
11.8 Estimation for the related samples t-test
11.9 SPSS in Focus: Confidence intervals for the related samples t-test
11.10 Characteristics of estimation: Precisions and certainty
11.11 APA in Focus: Reporting confidence intervals
Chapter 12—Analysis of Variance: One-Way Between-Subjects Design
12.1 Increasing k: A shift to analyzing variance
12.2 An introduction to analysis of variance
12.3 Sources of variation and the test statistic
12.4 Degrees of freedom
12.5 The one-way between-subjects ANOVA
12.6 What is the next step?
12.7 Post hoc comparisons
12.8 SPSS in Focus: The one-way between-subjects ANOVA
12.9 Measuring effect size
12.10 APA in Focus: Reporting the F-statistic, significance, and effect size
Chapter 13—Analysis of Variance: One-Way Within-Subjects Design
13.1 Observing the same participants across treatments
13.2 Sources of variation and the test statistic
13.3 Degrees of freedom
13.4 The one-way within-subjects ANOVA
13.5 Post hoc comparison: Bonferroni procedure
13.6 SPSS in Focus: The one-way within-subjects ANOVA
13.7 Measuring effect size
13.8 The within-subjects design: Consistency and power
13.9 APA in Focus: Reporting the F-statistic, significance, and effect size
Chapter 14—Analysis of Variance: Two-Way Between-Subjects Factorial Design
14.1 Observing two factors at the same time
14.2 New terminology and notation
14.3 Designs for the two-way ANOVA
14.4 Describing variability: Main effects and interactions
14.5 The two-way between-subjects ANOVA
14.6 Analyzing main effects and interactions
14.7 Measuring effect size
14.8 SPSS in Focus: The two-way between-subjects ANOVA
14.9 APA in Focus: Reporting main effects, interactions, and effect size
Chapter 15—Correlation
15.1 Treating factors as dependent measures
15.2 Describing a correlation
15.3 Pearson correlation coefficient
15.4 SPSS in Focus: Pearson correlation coefficient
15.5 Assumptions of tests for linear correlations
15.6 Limitations in interpretation: Causality, outliers, and restriction of range
15.7 Alternative to Pearson r: Spearman correlation coefficient
15.8 SPSS in Focus: Spearman correlation coefficient
15.9 Alternative to Pearson r: Point-biserial correlation coefficient
15.10 SPSS in Focus: Point-biserial correlation coefficient
15.11 Alternative to Pearson r: Phi correlation coefficient
15.12 SPSS in Focus: Phi correlation coefficient
15.13 APA in Focus: Reporting correlations
Chapter 16—Linear Regression
16.1 From relationships to predictions
16.2 Fundamentals of linear regression
16.3 What makes the regression line the best fitting line?
16.4 The slope and y-intercept of a straight line
16.5 Using the method of least squares to find the best fit
16.6 Using analysis of regression to measure significance
16.7 SPSS in Focus: Analysis of regression
16.8 Using the standard error of estimate to measure accuracy
16.9 Multiple regression
16.10 APA in Focus: Reporting regression analysis
Chapter 17—Nonparametric Tests: Chi-Square Tests
17.1 Tests for nominal data
17.2 The chi-square goodness-of-fit test
17.3 SPSS in Focus: The chi-square goodness-of-fit test
17.4 Interpreting the chi-square goodness-of-fit test
17.5 Independent observations and expected frequency size
17.6 The chi-square test for independence
17.7 The relationship between chi-square and the phi coefficient
17.8 Using the phi coefficient as a measure for effect size
17.9 SPSS in Focus: The chi-square test for independence
17.10 APA in Focus: Reporting the chi-square test
Chapter 18—Nonparametric Tests: Tests For Ordinal Data
18.1 Tests for ordinal data
18.2 The sign test
18.3 SPSS in Focus: The related samples sign test
18.4. The Wilcoxon signed-ranks T test
18.5 SPSS in Focus: The Wilcoxon signed-ranks T test
18.6 The Mann-Whitney U test
18.7 SPSS in Focus: The Mann-Whitney U test
18.8 The Kruskal-Wallis H test
18.9 SPSS in Focus: The Kruskal-Wallis H test
18.10 The Friedman test
18.11 SPSS in Focus: The Friedman test
18.12 APA in Focus: Reporting nonparametric tests
Appendix A—Mathematics in Statistics
A.1 Positive and negative numbers
A.2 Addition
A.3 Subtraction
A.4 Multiplication
A.5 Division
A.6 Fractions
A.7 Decimals and percents
A.8 Exponents and roots
A.9 Order of computation
A.10 Equations: Solving for x
A.11 Summation notation
Appendix B—Statistical Tables
Table B.1 Unit Normal Table
Table B.2 The t Table
Table B.3 The F Table
Table B.4 Studentized Range Statistic Table
Table B.5 The Pearson Correlation Table
Table B.6 The Spearman Correlation Table
Table B.7 The Chi-square Table
Table B.8 Binomial Probability Distribution Table
Table B.9 The Wilcoxon T Table
Table B.10 The Mann-Whitney U Table
Appendix C—Chapter Solutions For Even Numbered Problems

Über Autor(innen)

Privitera, Gregory J.
Gregory J. Privitera is an Associate Professor of Psychology at St. Bonaventure University. He received his Ph.D. in Behavioral Neuroscience at the University at Buffalo and went on to complete post-doctoral research at Arizona State University before coming to St. Bonaventure. A veteran of the U.S. Marines, he is also the author of more than two dozen peer-reviewed articles and books on the role of social cognition and learning on eating behavior and health. His work has been recognized in a variety of ways, including university awards for teaching and research. He oversees a variety of undergraduate research projects at St. Bonaventure University with more than a dozen undergraduate student research projects leading to publication in peer-reviewed journals. In the community, Dr. Privitera is a member of the Board of Trustees for a local elementary and high school where his children attend the elementary school.