Machine generated contents note: ch. 1 Data and Statistics -- 1.1.Introduction -- 1.1.1.Data Sources -- 1.1.2.Using the Computer -- 1.2.Observations and Variables -- 1.3.Types of Measurements for Variables -- 1.4.Distributions -- 1.4.1.Graphical Representation of Distributions -- 1.5.Numerical Descriptive Statistics -- 1.5.1.Location -- 1.5.2.Dispersion -- 1.5.3.Other Measures -- 1.5.4.Computing the Mean and Standard Deviation from a Frequency Distribution -- 1.5.5.Change of Scale -- 1.6.Exploratory Data Analysis -- 1.6.1.The Stem and Leaf Plot -- 1.6.2.The Box Plot -- 1.6.3.Comments -- 1.7.Bivariate Data -- 1.7.1.Categorical Variables -- 1.7.2.Categorical and Interval Variables -- 1.7.3.Interval Variables -- 1.8.Populations, Samples, and Statistical Inference---A Preview -- 1.9.Data Collection -- 1.10.Chapter Summary -- Summary -- 1.11.Chapter Exercises -- Concept Questions -- Practice Exercises -- Exercises -- Project -- ch. 2 Probability and Sampling Distributions --

Contents note continued: 2.1.Introduction -- 2.1.1.Chapter Preview -- 2.2.Probability -- 2.2.1.Definitions and Concepts -- 2.2.2.System Reliability -- 2.2.3.Random Variables -- 2.3.Discrete Probability Distributions -- 2.3.1.Properties of Discrete Probability Distributions -- 2.3.2.Descriptive Measures for Probability Distributions -- 2.3.3.The Discrete Uniform Distribution -- 2.3.4.The Binomial Distribution -- 2.3.5.The Poisson Distribution -- 2.4.Continuous Probability Distributions -- 2.4.1.Characteristics of a Continuous Probability Distribution -- 2.4.2.The Continuous Uniform Distribution -- 2.4.3.The Normal Distribution -- 2.4.4.Calculating Probabilities Using the Table of the Normal Distribution -- 2.5.Sampling Distributions -- 2.5.1.Sampling Distribution of the Mean -- 2.5.2.Usefulness of the Sampling Distribution -- 2.5.3.Sampling Distribution of a Proportion -- 2.6.Other Sampling Distributions -- 2.6.1.The X2 Distribution -- 2.6.2.Distribution of the Sample Variance --

Contents note continued: 2.6.3.The t Distribution -- 2.6.4.Using the t Distribution -- 2.6.5.The F Distribution -- 2.6.6.Using the F Distribution -- 2.6.7.Relationships among the Distributions -- 2.7.Chapter Summary -- 2.8.Chapter Exercises -- Concept Questions -- Practice Exercises -- Exercises -- ch. 3 Principles of Inference -- 3.1.Introduction -- 3.2.Hypothesis Testing -- 3.2.1.General Considerations -- 3.2.2.The Hypotheses -- 3.2.3.Rules for Making Decisions -- 3.2.4.Possible Errors in Hypothesis Testing -- 3.2.5.Probabilities of Making Errors -- 3.2.6.Choosing between α and β -- 3.2.7.Five-Step Procedure for Hypothesis Testing -- 3.2.8.Why Do We Focus on the Type I Error? -- 3.2.9.Choosing α -- 3.2.10.The Five Steps for Example 3.3 -- 3.2.11.p Values -- 3.2.12.The Probability of a Type II Error -- 3.2.13.Power -- 3.2.14.Uniformly Most Powerful Tests -- 3.2.15.One-Tailed Hypothesis Tests -- 3.3.Estimation -- 3.3.1.Interpreting the Confidence Coefficient --

Contents note continued: 3.3.2.Relationship between Hypothesis Testing and Confidence Intervals -- 3.4.Sample Size -- 3.5.Assumptions -- 3.5.1.Statistical Significance versus Practical Significance -- 3.6.Chapter Summary -- 3.7.Chapter Exercises -- Concept Questions -- Practice Exercises -- Multiple Choice Questions -- Exercises -- ch. 4 Inferences on a Single Population -- 4.1.Introduction -- 4.2.Inferences on the Population Mean -- 4.2.1.Hypothesis Test on μ -- 4.2.2.Estimation of μ -- 4.2.3.Sample Size -- 4.2.4.Degrees of Freedom -- 4.3.Inferences on a Proportion -- 4.3.1.Hypothesis Test on p -- 4.3.2.Estimation of p -- 4.3.3.Sample Size -- 4.4.Inferences on the Variance of One Population -- 4.4.1.Hypothesis Test on σ2 -- 4.4.2.Estimation of σ2 -- 4.5.Assumptions -- 4.5.1.Required Assumptions and Sources of Violations -- 4.5.2.Detection of Violations -- 4.5.3.Tests for Normality -- 4.5.4.If Assumptions Fail -- 4.5.5.Alternate Methodology --

Contents note continued: 4.6.Chapter Summary -- 4.7.Chapter Exercises -- Concept Questions -- Practice Exercises -- Exercises -- Project -- ch. 5 Inferences for Two Populations -- 5.1.Introduction -- 5.2.Inferences on the Difference between Means Using Independent Samples -- 5.2.1.Sampling Distribution of a Linear Function of Random Variables -- 5.2.2.The Sampling Distribution of the Difference between Two Means -- 5.2.3.Variances Known -- 5.2.4.Variances Unknown but Assumed Equal -- 5.2.5.The Pooled Variance Estimate -- 5.2.6.The "Pooled" t Test -- 5.2.7.Variances Unknown but Not Equal -- 5.3.Inferences on Variances -- 5.4.Inferences on Means for Dependent Samples -- 5.5.Inferences on Proportions -- 5.5.1.Comparing Proportions Using Independent Samples -- 5.5.2.Comparing Proportions Using Paired Samples -- 5.6.Assumptions and Remedial Methods -- 5.7.Chapter Summary -- 5.8.Chapter Exercises -- Concept Questions -- Practice Exercises -- Exercises -- Projects --

Contents note continued: ch. 6 Inferences for Two or More Means -- 6.1.Introduction -- 6.1.1.Using the Computer -- 6.2.The Analysis of Variance -- 6.2.1.Notation and Definitions -- 6.2.2.Heuristic Justification for the Analysis of Variance -- 6.2.3.Computational Formulas and the Partitioning of Sums of Squares -- 6.2.4.The Sum of Squares among Means -- 6.2.5.The Sum of Squares within Groups -- 6.2.6.The Ratio of Variances -- 6.2.7.Partitioning of the Sums of Squares -- 6.3.The Linear Model -- 6.3.1.The Linear Model for a Single Population -- 6.3.2.The Linear Model for Several Populations -- 6.3.3.The Analysis of Variance Model -- 6.3.4.Fixed and Random Effects Model -- 6.3.5.The Hypotheses -- 6.3.6.Expected Mean Squares -- 6.3.7.Notes on Exercises -- 6.4.Assumptions -- 6.4.1.Assumptions Required -- 6.4.2.Detection of Violated Assumptions -- 6.4.3.Tests for Equal Variance -- 6.4.4.Violated Assumptions -- 6.4.5.Variance Stabilizing Transformations -- 6.4.6.Notes on Exercises --

Contents note continued: 6.5.Specific Comparisons -- 6.5.1.Contrasts -- 6.5.2.Orthogonal Contrasts -- 6.5.3.Fitting Trends -- 6.5.4.Lack of Fit Test -- 6.5.5.Notes on Exercises -- 6.5.6.Post Hoc Comparisons -- 6.5.7.Comments -- 6.5.8.Confidence Intervals -- 6.6.Random Models -- 6.7.Unequal Sample Sizes -- 6.8.Analysis of Means -- 6.8.1.ANOM for Proportions -- 6.8.2.ANOM for Count Data -- 6.9.Chapter Summary -- 6.10.Chapter Exercises -- Concept Questions -- Exercises -- Projects -- ch. 7 Linear Regression -- 7.1.Introduction -- 7.1.1.Notes on Exercises -- 7.2.The Regression Model -- 7.3.Estimation of Parameters β0 and β1 -- 7.3.1.A Note on Least Squares -- 7.4.Estimation of σ2 and the Partitioning of Sums of Squares -- 7.5.Inferences for Regression -- 7.5.1.The Analysis of Variance Test for β1 -- 7.5.2.The (Equivalent) t Test for β1 -- 7.5.3.Confidence Interval for β1 -- 7.5.4.Inferences on the Response Variable -- 7.6.Using the Computer --

Contents note continued: 7.7.Correlation -- 7.8.Regression Diagnostics -- 7.9.Chapter Summary -- 7.10.Chapter Exercises -- Concept Questions -- Exercises -- Projects -- ch. 8 Multiple Regression -- 8.1.The Multiple Regression Model -- 8.1.1.The Partial Regression Coefficient -- 8.2.Estimation of Coefficients -- 8.2.1.Simple Linear Regression with Matrices -- 8.2.2.Estimating the Parameters of a Multiple Regression Model -- 8.2.3.Correcting for the Mean, an Alternative Calculating Method -- 8.3.Inferential Procedures -- 8.3.1.Estimation of σ2 and the Partitioning of the Sums of Squares -- 8.3.2.The Coefficient of Variation -- 8.3.3.Inferences for Coefficients -- 8.3.4.Tests Normally Provided by Computer Outputs -- 8.3.5.The Equivalent t Statistic for Individual Coefficients -- 8.3.6.Inferences on the Response Variable -- 8.4.Correlations -- 8.4.1.Multiple Correlation -- 8.4.2.How Useful is the R2 Statistic? -- 8.4.3.Partial Correlation -- 8.5.Using the Computer --

Contents note continued: 8.6.Special Models -- 8.6.1.The Polynomial Model -- 8.6.2.The Multiplicative Model -- 8.6.3.Nonlinear Models -- 8.7.Multicollinearity -- 8.7.1.Redefining Variables -- 8.7.2.Other Methods -- 8.8.Variable Selection -- 8.8.1.Other Selection Procedures -- 8.9.Detection of Outliers, Row Diagnostics -- 8.10.Chapter Summary -- 8.11.Chapter Exercises -- Concept Questions -- Exercises -- Projects -- ch. 9 Factorial Experiments -- 9.1.Introduction -- 9.2.Concepts and Definitions -- 9.3.The Two-Factor Factorial Experiment -- 9.3.1.The Linear Model -- 9.3.2.Notation -- 9.3.3.Computations for the Analysis of Variance -- 9.3.4.Between Cells Analysis -- 9.3.5.The Factorial Analysis -- 9.3.6.Expected Mean Squares -- 9.3.7.Unbalanced Data -- 9.3.8.Notes on Exercises -- 9.4.Specific Comparisons -- 9.4.1.Preplanned Contrasts -- 9.4.2.Basic Test Statistic for Contrasts -- 9.4.3.Multiple Comparisons -- 9.5.Quantitative Factors -- 9.5.1.Lack of Fit -- 9.6.No Replications --

Contents note continued: 9.7.Three or More Factors -- 9.7.1.Additional Considerations -- 9.8.Chapter Summary -- 9.9.Chapter Exercises -- Concept Questions -- Exercises -- Project -- ch. 10 Design of Experiments -- 10.1.Introduction -- 10.1.1.Notes on Exercises -- 10.2.The Randomized Block Design -- 10.2.1.The Linear Model -- 10.2.2.Relative Efficiency -- 10.2.3.Random Treatment Effects in the Randomized Block Design -- 10.3.Randomized Blocks with Sampling -- 10.4.Other Designs -- 10.4.1.Factorial Experiments in a Randomized Block Design -- 10.4.2.Nested Designs -- 10.5.Repeated Measures Designs -- 10.5.1.One Between-Subject and One Within-Subject Factor -- 10.5.2.Two Within-Subject Factors -- 10.5.3.Assumptions of the Repeated Measures Model -- 10.5.4.Split Plot Designs -- 10.5.5.Additional Topics -- 10.6.Chapter Summary -- 10.7.Chapter Exercises -- Concept Questions -- Exercises -- Projects -- ch. 11 Other Linear Models -- 11.1.Introduction -- 11.2.The Dummy Variable Model --

Contents note continued: 11.2.1.Factor Effects Coding -- 11.2.2.Reference Cell Coding -- 11.2.3.Comparing Coding Schemes -- 11.3.Unbalanced Data -- 11.4.Computer Implementation of the Dummy Variable Model -- 11.5.Models with Dummy and Interval Variables -- 11.5.1.Analysis of Covariance -- 11.5.2.Multiple Covariates -- 11.5.3.Unequal Slopes -- 11.5.4.Independence of Covariates and Factors -- 11.6.Extensions to Other Models -- 11.7.Estimating Linear Combinations of Regression Parameters -- 11.7.1.Covariance Matrices -- 11.7.2.Linear Combination of Regression Parameters -- 11.8.Weighted Least Squares -- 11.9.Correlated Errors -- 11.10.Chapter Summary -- 11.10.1.An Example of Extremely Unbalanced Data -- 11.11.Chapter Exercises -- Concept Questions -- Exercises -- Projects -- ch. 12 Categorical Data -- 12.1.Introduction -- 12.2.Hypothesis Tests for a Multinomial Population -- 12.3.Goodness of Fit Using the X2 Test -- 12.3.1.Test for a Discrete Distribution --

Contents note continued: 12.3.2.Test for a Continuous Distribution -- 12.4.Contingency Tables -- 12.4.1.Computing the Test Statistic -- 12.4.2.Test for Homogeneity -- 12.4.3.Test for Independence -- 12.4.4.Measures of Dependence -- 12.4.5.Likelihood Ratio Test -- 12.4.6.Fisher's Exact Test -- 12.5.Loglinear Model -- 12.6.Chapter Summary -- 12.7.Chapter Exercises -- Concept Questions -- Exercises -- Projects -- ch. 13 Special Types of Regression -- 13.1.Introduction -- 13.1.1.Maximum Likelihood and Least Squares -- 13.2.Logistic Regression -- 13.3.Poisson Regression -- 13.3.1.Choosing Between Logistic and Poisson Regression -- 13.4.Nonlinear Least-Squares Regression -- 13.4.1.Sigmoidal Shapes (S Curves) -- 13.4.2.Symmetric Unimodal Shapes -- 13.5.Chapter Summary -- 13.6.Chapter Exercises -- Concept Questions -- Exercises -- Project -- ch. 14 Nonparametric Methods -- 14.1.Introduction -- 14.1.1.Ranks -- 14.1.2.Randomization Tests --

Contents note continued: 14.1.3.Comparing Parametric and Nonparametric Procedures -- 14.2.One Sample -- 14.3.Two Independent Samples -- 14.4.More Than Two Samples -- 14.5.Randomized Block Design -- 14.6.Rank Correlation -- 14.7.The Bootstrap -- 14.8.Chapter Summary -- 14.9.Chapter Exercises -- Concept Questions -- Exercises -- Projects -- Appendix A -- A.1.The Normal Distribution---Probabilities Exceeding Z -- A.1A.Selected Probability Values for the Normal Distribution---Values of Z Exceeded with Given Probability -- A.2.The t Distribution---Values of t Exceeded with Given Probability -- A.3.The X2 Distribution---X2 Values Exceeded with Given Probability -- A.4.The F Distribution, p = 0.1 -- A.4A.The F Distribution, p = 0.05 -- A.4B.The F Distribution, p = 0.025 -- A.4C.The F Distribution, p = 0.01 -- A.4D.The F Distribution, p = 0.005 -- A.5.The Fmax Distribution---Percentage Points of Fmax =s2max/s2max --

Contents note continued: A.6.Orthogonal Polynomials (Tables of Coefficients for Polynomial Trends) -- A.7.Percentage Points of the Studentized Range -- A.8.Percentage Points of Duncan's Multiple Range Test -- A.9.Critical Values for the Wilcoxon Signed Rank Test N = 5(1)50 -- A.10.The Mann-Whitney Two-Sample Test -- A.11.Exact Critical Values for Use with the Analysis of Means -- Appendix B A Brief Introduction to Matrices -- B.1.Matrix Algebra -- B.2.Solving Linear Equations -- Appendix C -- C.1.Florida Lake Data -- C.2.State Education Data Set -- C.3.NADP Data Set -- C.4.Florida County Data Set -- C.5.Cowpea Data Set.