Essential Statistics for the Behavioral Sciences 1st Edition Privitera Solutions Manual

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Product details:

• ISBN-10 ‏ : ‎ 9781483353005
• ISBN-13 ‏ : ‎ 978-1483353005
• Author: Gregory J. Privitera

Employing the hallmark pedagogical support of his successful comprehensive text, award-winning author, teacher, and advisor Gregory J. Privitera offers a brief and engaging introduction to the field with Essential Statistics for the Behavioral Sciences. Practical examples, integrated SPSS® coverage and screenshots, and numerous learning tools make intimidating concepts accessible. Students will welcome Privitera′s clear instruction, conversational voice, and application of statistics to current, real-life research problems.

Table of contents:

Part I: Introduction and Descriptive Statistics
Chapter 1: Introduction to Statistics
The Use of Statistics in Science
Descriptive and Inferential Statistics
Research Methods and Statistics
Scales of Measurement
Types of Variables for Which Data are Measured
Research in Focus: Evaluating Data and Scales of Measurement
SPSS in Focus: Entering and Defining Variables
Chapter 2: Summarizing Data: Frequency Distributions in Tables and Graphs
Why Summarize Data?
Frequency Distributions for Grouped Data
Identifying Percentile Points and Percentile Ranks
SPSS in Focus: Frequency Distributions for Quantitative Data
Frequency Distributions for Ungrouped Data
Research in Focus: Summarizing Demographic Information
SPSS in Focus: Frequency Distribution for Categorical Data
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
Chapter 3: 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
Chapter 4: Summarizing Data: Variability
Measuring Variability
Range and Interquartile Range
Research in Focus: Reporting the Range
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
Part II: Probability and the Foundations of Inferential Statistics
Chapter 5: Probability, Normal Distribution, and z Scores
Introduction to Probability
Calculating Probability
Probability and the Normal Distribution
Characteristics of the Normal Distribution
Research in Focus: The Statistical Norm
The Standard Normal Distribution and z Scores
A Brief Introduction to the Unit Normal Table
Locating Proportions
Locating Scores
SPSS in Focus: Converting Raw Scores to Standard z Scores
Chapter 6: Characteristics of the Sample Mean
Selecting Samples From Populations
Selecting a Sample: Who’s In and Who’s Out?
Sampling Distributions: The Mean
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
Chapter 7: Hypothesis Testing: Significance, Effect Size, and Power
Inferential Statistics and Hypothesis Testing
Four Steps to Hypothesis Testing
Hypothesis Testing and Sampling Distributions
Making a Decision: Types of Error
Testing Significance: Examples Using the z Test
Research in Focus: Directional Versus Nondirectional 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 8 to 14
APA in Focus: Reporting the Test Statistic and Effect Size
Part III: Making Inferences About One or Two Means
Chapter 8: Testing Means: One-Sample t Test With Confidence Intervals
Going From z to t
The Degrees of Freedom
Reading the t Table
Computing the One–Sample t Test
Effect Size for the One-Sample t Test
Confidence Intervals for the One-Sample t Test
Inferring Significance and Effect Size From a Confidence Interval
SPSS in Focus: One–Sample t Test and Confidence Intervals
APA in Focus: Reporting the t Statistic and Confidence Intervals
Chapter 9: Testing Means: Two-Independent-Sample t Test With Confidence Intervals
Introduction to the Between-Subjects Design
Selecting Samples for Comparing Two Groups
Variability and Comparing Differences Between Two Groups
Computing the Two-Independent–Sample t Test
Effect Size for the Two-Independent-Sample t Test
Confidence Intervals for the Two-Independent-Sample t Test
Inferring Significance and Effect Size From a Confidence Interval
SPSS in Focus: Two-Independent–Sample t Test and Confidence Intervals
APA in Focus: Reporting the t Statistic and Confidence Intervals
Chapter 10: Testing Means: Related-Samples t Test With Confidence Intervals
Related Samples Design
Introduction to the Related-Samples t Test
Computing the Related-Samples t Test
Measuring Effect Size for the Related-Samples t Test
Confidence Intervals for the Related-Samples t Test
Inferring Significance and Effect Size From a Confidence Interval
SPSS in Focus: Related-Samples t Test and Confidence Intervals
APA in Focus: Reporting the t Statistic and Confidence Intervals
Part IV: Making Inferences About The Variability of Two or More Means
Chapter 11: One-Way Analysis of Variance: Between-Subjects and Within-Subjects (Repeated-Measures) Designs
An Introduction to Analysis of Variance
The Between-Subjects Design for Analysis of Variance
Computing the One-Way Between-Subjects ANOVA
Post Hoc Tests: An Example Using Tukey’s HSD
SPSS in Focus: The One-Way Between-Subjects ANOVA
The Within-Subjects Design for Analysis of Variance
Computing the One-Way Within-Subjects ANOVA
Post Hoc Tests for the Within-Subjects Design
SPSS in Focus: The One-Way Within-Subjects ANOVA
A Comparison of Within-Subjects and Between-Subjects Designs for ANOVA: Implications for Power
APA in Focus: Reporting the Results of the One-Way ANOVAs
Chapter 12: Two-Way Analysis of Variance: Between-Subjects Factorial Design
Introduction to Factorial Designs
Structure and Notation for the Two-Way ANOVA
Describing Variability: Main Effects and Interactions
Computing the Two-Way Between-Subjects ANOVA
Analyzing Main Effects and Interactions
Measuring Effect Size for Main Effects and the Interaction
SPSS in Focus: The Two-Way Between-Subjects ANOVA
APA in Focus: Reporting the Results of the Two-Way ANOVAs
Part V: Making Inferences About Patterns, Prediction, and Nonparametric Tests
Chapter 13: Correlation and Linear Regression
The Structure of Data Used for Identifying Patterns and Making Predictions
Fundamentals of the Correlation
The Pearson Correlation Coefficient
SPSS in Focus: Pearson Correlation Coefficient
Assumptions and Limitations for Linear Correlations
Alternatives to Pearson: Spearman, Point-Biserial, and Phi
SPSS in Focus; Computing the Alternatives to Pearson
Fundamentals of Linear Regression
Using the Method of Least Squares to Find the Regression Line
Using Analysis of Regression to Determine Significance
SPSS in Focus: Analysis of Regression
A Look Ahead to Multiple Regression
APA in Focus: Reporting Correlations and Linear Regression
Chapter 14: Chi-Square Tests: Goodness-of-Fit and the Test for Independence
Distinguishing Parametric and Nonparametric Tests
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
The Chi-Square Test for Independence
Measures of Effect Size for the Chi-Square Test for Independence
SPSS in Focus: The Chi-Square Test for Independence
APA in Focus: Reporting the Chi-Square Tests
Appendix A: Basic Math Review and Summation Notation
Appendix B: Statistical Tables
Appendix C: Chapter Solutions for Even-Numbered Problems

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