Books  Data Analysis & Modelling  Data Analysis & Statistics 

Interactive Statistics for the Behavioral Sciences

TextbookOut of Print

By: Pepper Williams

Tabs, figs

Sinauer Associates

Paperback | Oct 2003 | #142858 | ISBN: 087893930X
Out of Print Details

About this book

The CD and textbook cover topics of behavioral science including: descriptive statistics, the logic of hypothesis testing, t-tests, power analysis, confidence intervals, analysis of variance, correlation/regression, and nonparametric inferential statistics.


PART 1: Introduction to Statistics - Statistics in Society and Science - Descriptive and Inferential Statistics - Populations and Samples - Statistical Notation - Chapter Summary/Review - PART 2: Looking at Data: Frequency Distributions - Organizing Data - Frequency Distribution Tables - Frequency Distribution Histograms - Describing Distributions - Chapter Summary/Review - PART 3: Describing Data: Measuring Center and Spread - The Need to Describe - Measuring Center: The Mean - Measuring Spread: The Standard Deviation - Resistant Measures of Center and Spread - Correlation - z-Scores - Chapter Summary/Review - PART 4: Preparing To Test Hypotheses - Probability - Normal Distributions - The Central Limit Theorem - Chapter Summary/Review - PART 5: From Samples to Populations: Hypothesis Testing with z - What Counts as a "Significant" Increase? - Logic of Hypothesis Testing - Hypothesis Testing with z-Scores - Directional Hypothesis Tests - Hypothesis Test Assumptions - Evaluating Evidence - Chapter Summary/Review - PART 6: Practical Hypothesis Testing with t - The Problem with z - The t Statistic - Hypothesis Testing for Single Samples with t - Assumptions for t Tests - Reporting Hypothesis Tests - When Should You Use t vs. z? - What You Can Test with t - Chapter Summary/Review - PART 7: Making and Avoiding Hypothesis Test Errors - When Hypothesis Tests Fail - Fishing for Significance - Reporting Failed Hypothesis Tests - Power - Chapter Summary/Review - PART 8: t Tests for Two Means - Two-Condition Experimental Designs - Repeated Measures - Independent Samples - Assumptions for Two-Condition t Tests - Comparing Two-Condition Designs - Chapter Summary/Review - PART 9: Confidence Intervals - Estimation - Constructing Confidence Intervals - Confidence Intervals - Chapter Summary/Review - PART 10: Inference for Three or More Means: Analysis of Variance (ANOVA) - Introduction to ANOVA - The Logic of ANOVA - Testing Hypotheses with Independent-Samples ANOVA - ANOVA for Related Samples - Further Analysis of Multicondition Datasets - F vs. t - Multiple-Factor ANOVA - Chapter Summary/Review - PART 11: Describing Relationships: Correlation and Regression - Covariability - Characteristics of Relationships - The Pearson Correlation - Linear Regression - Using Correlation and Regression in Research - Multiple Regression/Correlation - Chapter Summary/Review - PART 12: Inference for Categorical Data: Chi-Square Tests - Categorical Data - Testing One Sample: The Chi-Square Goodness-of-Fit Test - Testing Two Related Samples: The Sign Test - Testing Independent Samples: The Test for Independence - Testing Relationships between Categorical Variables - Opinion Polls and the Binomial Test - Chapter Summary/Review

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PEPPER WILLIAMS is Lecturer at Portland State University, USA.

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