More New and Used

from Private Sellers

# Statistics for the Behavioral Sciences

**by**Gregory J. Privitera

### 9781412969314

141296931X

Hardcover

9/7/2011

SAGE Publications, Inc

## Questions About This Book?

Why should I rent this book?

Renting is easy, fast, and cheap! Renting from eCampus.com can save you hundreds of dollars compared to the cost of new or used books each semester. At the end of the semester, simply ship the book back to us with a free UPS shipping label! No need to worry about selling it back.

How do rental returns work?

Returning books is as easy as possible. As your rental due date approaches, we will email you several courtesy reminders. When you are ready to return, you can print a free UPS shipping label from our website at any time. Then, just return the book to your UPS driver or any staffed UPS location. You can even use the same box we shipped it in!

What version or edition is this?

This is the edition with a publication date of 9/7/2011.

What is included with this book?

- The
**Used**copy of this book is not guaranteed to include any supplemental materials. Typically, only the book itself is included. - The
**Rental**copy of this book is not guaranteed to include any supplemental materials. You may receive a brand new copy, but typically, only the book itself.

## Summary

Modern Statistics in the Behavioral Sciences engages students in using statistics to summarize data and make decisions about behavior. It is designed to emphasize the ongoing spirit of discovery that emerges when using today#xE2;#xAC;"s technology to understand the application of statistics to modern-day research problems. This text exposes students to statistical applications in current research, tests their knowledge using current research examples, gives them step-by-step instruction for using SPSS, and makes them aware of how statistics is important for their generation-all through the following features.

## Table of Contents

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 âÇ£midrange of behaviorâÇ | |

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 BayesâÇÖ 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: WhoâÇÖs in and whoâÇÖs 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: CohenâÇÖs 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 | |

Table of Contents provided by Publisher. All Rights Reserved. |