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Statistics for the Behavioral Sciences

ISBN-10: 141296931X
ISBN-13: 9781412969314
Edition: 2012
List price: $79.00 Buy it from $8.75
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Book details

List price: $79.00
Copyright year: 2012
Publisher: SAGE Publications, Incorporated
Publication date: 11/3/2011
Binding: Hardcover
Pages: 736
Size: 8.00" wide x 10.00" long x 1.00" tall
Weight: 3.630
Language: English

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.

SPSS Prefix: General Overview and Guide for Using SPSS
Overview of SPSS: What are you looking at?
Preview of SPSS in Focus
Introduction to Statistics
Descriptive and inferential statistics
Statistics in research
Scales of measurement
Types of data
Research in Focus: Types of data and scales of measurement
SPSS in Focus: Entering and defining variables
Summarizing Data: Tables, Graphs, and Distributions
Why summarize data?
Frequency distributions for grouped data
SPSS in Focus: Frequency distributions for quantitative data
Frequency distributions for ungrouped data
Research in Focus: Summarizing demographic information
SPSS in Focus: Frequency distributions for categorical data
Pictorial frequency distributions
Graphing distributions: Continuous data
Graphing distributions: Discrete and categorical data
Research in Focus: Frequencies and percents
SPSS in Focus: Histograms, bar charts, and pie charts
Summarizing Data: Central Tendency
Introduction to central tendency
Measures of central tendency
Characteristics of the mean
Choosing an appropriate measure of central tendency
Research in Focus: Describing central tendency
SPSS in Focus: Mean, median, and mode
Summarizing Data: Variability
Measuring variability
Range and midrange
Research in Focus: Reporting the range
Measures of variability: Quartiles and interquartiles
Research in Focus: The �ǣmidrange of behavior�Ǡ
The variance
Explaining variance for populations and samples
The computational formula for variance
The Standard deviation
What does the standard deviation tell us?
Characteristics of the standard deviation
SPSS in Focus: Range, variance, and standard deviation
Probability
Introduction to probability
Calculating probability
Probability and relative frequency
The relationship between multiple outcomes
Conditional probabilities and Bayes��� Theorem
SPSS in Focus: Probability tables
Probability distributions
The mean of a probability distribution and expected value
Research in Focus: When are risks worth taking?
The variance and standard deviation of a probability distribution
Expected value and the binomial distribution
a final thought on the likelihood of random behavioral outcomes
Probability and Normal Distributions
The normal distribution in behavioral science
Characteristics of the normal distribution
Research in Focus: The statistical norm
The standard normal distribution
The unit normal table: a brief introduction
Locating proportions
Locating scores
SPSS in Focus: Converting raw scores to standard z-scores
Going from binomial to normal
The normal approximation to the binomial distribution
Probability and Sampling Distributions
Selecting samples from populations
Selecting a sample: Who���s in and who���s out?
Sampling distributions: The mean
Sampling distributions: The variance
The standard error of the mean
Factors that decrease standard error
SPSS in Focus: Estimating the standard error of the mean
APA in Focus: Reporting the standard error
Standard normal transformations with sampling distributions
Introduction to Hypothesis Testing
Inferential Statistics and hypothesis testing
Four steps to hypothesis testing
Hypothesis testing and sampling distributions
Making a decision: Types of error
Testing a research hypothesis: Examples using the z-test
Research in Focus: Directional versus non-directional tests
Measuring the size of an effect: Cohen���s d
Effect size, power, and sample size
Additional factors that increase power
SPSS in Focus: a preview for Chapters 9 to 18
APA in Focus: Reporting the test statistic and effect size
Testing Means: Independent Sample t-Tests
Going from z to t
The degrees of freedom
Reading the t-table
One-independent sample t-test
Effect size for the one-independent sample t-test
SPSS in Focus: One-independent sample t-test
Two-independent sample t-test
Effect size for the two-independent sample t-test
SPSS in Focus: Two-independent sample t-test
APA in Focus: Reporting the t-statistic and effect size
Testing Means: Related Samples t-Test
Related and independent samples
Introduction to the related samples t-test
Related samples t-test: Repeated measures design
SPSS in Focus: The related samples t-test
Related samples t-test: Matched pairs design
Measuring effect size for the related samples t-test
Advantages for selecting related samples
APA in Focus: Reporting the t-statistic and effect size for related samples
Estimation and Confidence Intervals
Point estimation and interval estimation
The process of estimation
Estimation for the one-independent sample z-test
Estimation for the one-independent sample t-test
SPSS in Focus: Confidence intervals for the one-independent t-test
Estimation for the two-independent sample t-test
SPSS in Focus: Confidence intervals for the two-independent t-test
Estimation for the related samples t-test
SPSS in Focus: Confidence intervals for the related samples t-test
Characteristics of estimation: Precisions and certainty
APA in Focus: Reporting confidence intervals
Analysis of Variance: One-Way Between-Subjects Design
Increasing k: a shift to analyzing variance
An introduction to analysis of variance
Sources of variation and the test statistic
Degrees of freedom
The one-way between-subjects ANOVA
What is the next step?
Post hoc comparisons
SPSS in Focus: The one-way between-subjects ANOVA
Measuring effect size
APA in Focus: Reporting the F-statistic, significance, and effect size
Analysis of Variance: One-Way Within-Subjects Design
Observing the same participants across treatments
Sources of variation and the test statistic
Degrees of freedom
The one-way within-subjects ANOVA
Post hoc comparison: Bonferroni procedure
SPSS in Focus: The one-way within-subjects ANOVA
Measuring effect size
The within-subjects design: Consistency and power
APA in Focus: Reporting the F-statistic, significance, and effect size
Analysis of Variance: Two-Way Between-Subjects Factorial Design
Observing two factors at the same time
New terminology and notation
Designs for the two-way ANOVA
Describing variability: Main effects and interactions
The two-way between-subjects ANOVA
Analyzing main effects and interactions
Measuring effect size
SPSS in Focus: The two-way between-subjects ANOVA
APA in Focus: Reporting main effects, interactions, and effect size
Correlation
Treating factors as dependent measures
Describing a correlation
Pearson correlation coefficient
SPSS in Focus: Pearson correlation coefficient
Assumptions of tests for linear correlations
Limitations in interpretation: Causality, outliers, and restriction of range
Alternative to Pearson r: Spearman correlation coefficient
SPSS in Focus: Spearman correlation coefficient
Alternative to Pearson r: Point-biserial correlation coefficient
SPSS in Focus: Point-biserial correlation coefficient
Alternative to Pearson r: Phi correlation coefficient
SPSS in Focus: Phi correlation coefficient
APA in Focus: Reporting correlations
Linear Regression
From relationships to predictions
Fundamentals of linear regression
What makes the regression line the best fitting line?
The slope and y-intercept of a straight line
Using the method of least squares to find the best fit
Using analysis of regression to measure significance
SPSS in Focus: Analysis of regression
Using the standard error of estimate to measure accuracy
Multiple regression
APA in Focus: Reporting regression analysis
Nonparametric Tests: Chi-Square Tests
Tests for nominal data
The chi-square goodness-of-fit test
SPSS in Focus: The chi-square goodness-of-fit test
Interpreting the chi-square goodness-of-fit test
Independent observations and expected frequency size
The chi-square test for independence
The relationship between chi-square and the phi coefficient
Using the phi coefficient as a measure for effect size
SPSS in Focus: The chi-square test for independence
APA in Focus: Reporting the chi-square test
Nonparametric Tests: Tests For Ordinal Data
Tests for ordinal data
The sign test
SPSS in Focus: The related samples sign test
The Wilcoxon signed-ranks T test
SPSS in Focus: The Wilcoxon signed-ranks T test
The Mann-Whitney U test
SPSS in Focus: The Mann-Whitney U test
The Kruskal-Wallis H test
SPSS in Focus: The Kruskal-Wallis H test
The Friedman test
SPSS in Focus: The Friedman test
APA in Focus: Reporting nonparametric tests
Mathematics in Statistics
Positive and negative numbers
Addition
Subtraction
Multiplication
Division
Fractions
Decimals and percents
Exponents and roots
Order of computation
Equations: Solving for x
Summation notation
Statistical Tables
Unit Normal Table
The t Table
The F Table
Studentized Range Statistic Table
The Pearson Correlation Table
The Spearman Correlation Table
The Chi-square Table
Binomial Probability Distribution Table
The Wilcoxon T Table
The Mann-Whitney U Table
Chapter Solutions For Even Numbered Problems

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