Statistical Methods

4th Edition - April 16, 2021
Authors: Donna L. Mohr, William J. Wilson, Rudolf J. Freund
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 2 3 0 4 3 - 5
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 8 9 9 8 8 - 8

Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathem… Read more

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Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results.

Cover image
Title page
Table of Contents
Copyright
Preface
Guiding Principles
New to this Edition
Using this Book
Acknowledgments
Chapter 1. Data and Statistics
1.1 Introduction
1.2 Observations and Variables
1.3 Types of Measurements for Variables
1.4 Distributions
1.5 Numerical Descriptive Statistics
1.6 Exploratory Data Analysis
1.7 Bivariate Data
1.8 Populations, Samples, and Statistical Inference — A Preview
1.9 Data Collection
1.10 Chapter Summary
Summary
1.11 Chapter Exercises
Chapter 2. Probability and Sampling Distributions
2.1 Introduction
2.2 Probability
2.3 Discrete Probability Distributions
2.4 Continuous Probability Distributions
2.5 Sampling Distributions
2.6 Other Sampling Distributions
2.7 Chapter Summary
2.8 Chapter Exercises
Chapter 3. Principles of Inference
3.1 Introduction
3.2 Hypothesis Testing
3.3 Estimation
3.4 Sample Size
3.5 Assumptions
3.6 Chapter Summary
3.7 Chapter Exercises
Exercises
Chapter 4. Inferences on a Single Population
4.1 Introduction
4.2 Inferences on the Population Mean
4.3 Inferences on a Proportion for Large Samples
4.4 Inferences on the Variance of One Population
4.5 Assumptions
4.6 Chapter Summary
4.7 Chapter Exercises
Chapter 5. Inferences for Two Populations
5.1 Introduction
5.2 Inferences on the Difference between Means Using Independent Samples
5.3 Inferences on Variances
5.4 Inferences on Means for Dependent Samples
5.5 Inferences on Proportions for Large Samples
5.6 Assumptions and Remedial Methods
5.7 Chapter Summary
5.8 Chapter Exercises
Chapter 6. Inferences for Two or More Means
6.1 Introduction
6.2 The Analysis of Variance
6.3 The Linear Model
6.4 Assumptions
6.5 Specific Comparisons
6.6 Random Models
6.7 Analysis of Means
6.8 Chapter Summary
6.9 Chapter Exercises
Projects
Chapter 7. Linear Regression
7.1 Introduction
7.2 The Regression Model
7.3 Estimation of Parameters β0 and β1
7.4 Estimation of σ2 and the Partitioning of Sums of Squares
7.5 Inferences for Regression
7.6 Using Statistical Software
7.7 Correlation
7.8 Regression Diagnostics
7.9 Chapter Summary
7.10 Chapter Exercises
Chapter 8. Multiple Regression
8.1 The Multiple Regression Model
8.2 Estimation of Coefficients
8.3 Inferential Procedures
8.4 Correlations
8.5 Using Statistical Software
8.6 Special Models
8.7 Multicollinearity
8.8 Variable Selection
8.9 Detection of Outliers, Row Diagnostics
8.10 Chapter Summary
8.11 Chapter Exercises
Chapter 9. Factorial Experiments
9.1 Introduction
9.2 Concepts and Definitions
9.3 The Two-Factor Factorial Experiment
9.4 Specific Comparisons
9.5 Quantitative Factors
9.6 No Replications
9.7 Three or More Factors
9.8 Chapter Summary
9.9 Chapter Exercises
Chapter 10. Design of Experiments
10.1 Introduction
10.2 The Randomized Block Design
10.3 Randomized Blocks with Sampling
10.4 Other Designs
10.5 Repeated Measures Designs
10.6 Chapter Summary
10.7 Chapter Exercises
Chapter 11. Other Linear Models
11.1 Introduction
11.2 The Dummy Variable Model
11.3 Unbalanced Data
11.4 Statistical Software’s Implementation of the Dummy Variable Model
11.5 Models with Dummy and Interval Variables
11.6 Extensions to Other Models
11.7 Estimating Linear Combinations of Regression Parameters
11.8 Weighted Least Squares
11.9 Correlated Errors
11.10 Chapter Summary
11.11 Chapter Exercises
Chapter 12. Categorical Data
12.1 Introduction
12.2 Hypothesis Tests for a Multinomial Population
12.3 Goodness of Fit Using the χ2 Test
12.4 Contingency Tables
12.5 Specific Comparisons in Contingency Tables
12.6 Chapter Summary
12.7 Chapter Exercises
Chapter 13. Special Types of Regression
13.1 Introduction
13.2 Logistic Regression
13.3 Poisson Regression
13.4 Nonlinear Least-Squares Regression
13.5 Chapter Summary
13.6 Chapter Exercises
Chapter 14. Nonparametric Methods
14.1 Introduction
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
Appendix A. Tables of Distributions
Appendix B
Appendix B. A Brief Introduction to Matrices
B.1 Matrix Algebra
B.2 Solving Linear Equations
Appendix C. Descriptions of Data Sets
C.1 Florida Lake Data
C.2 State Education Data
C.3 National Atmospheric Deposition Program (NADP) Data
C.4 Florida County Data
C.5 Cowpea Data
C.6 Jax House Prices Data
C.7 Gainesville, FL, Weather Data
C.8 General Social Survey (GSS) 2016 Data
Hints for Selected Exercises
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
Chapter 14
References
Index

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health

Statistical Methods

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Donna L. Mohr

William J. Wilson

Rudolf J. Freund

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