Section Section Description Page Number
1 Introduction
1.1 Introduction to statistical methodology
1.2 Descriptive statistics and inferential statistics
1.3 The role of computers in statistics
1.4 Chapter summary
2 Sampling and Measurement
2.1 Variables and their measurement
2.2 Randomization
2.3 Sampling variability and potential bias
2.4 other probability sampling methods
2.4 Chapter summary
3 Descriptive statistics
3.1 Describing data with tables and graphs
3.2 Describing the center of the data
3.3 Describing variability of the data
3.4 Measure of position
3.5 Bivariate descriptive statistics
3.6 Sample statistics and population parameters
3.7 Chapter summary
4 Probability Distributions
4.1 Introduction to probability
4.2 Probablitity distributions for discrete and continuous variables
4.3 The normal probability distribution
4.4 Sampling distributions describe how statistics vary
4.5 Sampling distributions of sample means
4.6 Review: Probability, sample data, and sampling distributions
4.7 Chapter summary
5 Statistical inference: estimation
5.1 Point and interval estimation
5.2 Confidence interval for a proportion
5.3 Confidence interval for a mean
5.4 Choice of sample size
5.5 Confidence intervals for median and other parameters
5.6 Chapter summary
6 Statistical Inference: Significance Tests
6.1 Steps of a significance test
6.2 Significance test for a eman
6.3 Significance test for a proportion
6.4 Decisions and types of errors in tests
6.5 Limitations of significance tests
6.6 Calculating P (Type II error)
6.7 Small-sample test for a proportion: the binomial distribution
6.8 Chapter summary
7 Comparison of Two Groups
7.1 Preliminaries for comparing groups
7.2 Categorical data: comparing two proportions
7.3 Quantitative data: comparing two means
7.4 Comparing means with dependent samples
7.5 Other methods for comparing means
7.6 Other methods for comparing proportions
7.7 Nonparametric statistics for comparing groups
7.8 Chapter summary
8 Analyzing Association between Categorical Variables
8.1 Contingency Tables
8.2 Chi-squared test of independence
8.3 Residuals: Detecting the pattern of association
8.4 Measuring association in contingency tables
8.5 Association between ordinal variables
8.6 Inference for ordinal associations
8.7 Chapter summary
9 Linear Regression and Correlation
9.1 Linear relationships
9.2 Least squares prediction equation
9.3 The linear regression model
9.4 Measuring linear association - the correlation
9.5 Inference for the slope and correlation
9.6 Model assumptions and violations
9.7 Chapter summary
10 Introduction to multivariate Relationships
10.1 Association and causality
10.2 Controlling for other variables
10.3 Types of multivariate relationships
10.4 Inferenential issus in statistical control
10.5 Chapter summary
11 Multiple Regression and Correlation
11.1 Multiple regression model
11.2 Example with multiple regression computer output
11.3 Multiple correlation and R-squared
11.4 Inference for multiple regression and coefficients
11.5 Interaction between predictors in their effects
11.6 Comparing regression models
11.7 Partial correlation
11.8 Standardized regression coefficients
11.9 Chapter summary
12 Comparing groups: Analysis of Variance (ANOVA) methods
12.1 Comparing several means: One way analysis of variance
12.2 Multiple comparisons of means
12.3 Performing ANOVA by regression modeling
12.4 Two-way analysis
