Essential Statistics 4th edition by Rees ISBN 1584880074 978-1584880073

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ISBN 10: 1584880074
ISBN 13: 978-1584880073
Author: Rees

An introductory text for students taking a first course in statistics-in fields as diverse as engineering, business, chemistry, and biology-Essential Statistics: Fourth Edition thoroughly updates and enhances the hugely successful third edition. It presents new information on modern statistical techniques such as Analysis of Variance (ANOVA), and software such as MINITAB™ for WINDOWS.

An experienced former lecturer, the author communicates to students in his trademark easy-to-follow style. Keeping complex mathematical theory to a minimum, Rees presents a wealth of fully explained worked examples throughout the text. In addition, the end-of-chapter Worksheets relate to a variety of fields-enabling students to see the relevance of the numerous methods to their study areas. Essential Statistics: Fourth Edition emphasizes the principles and assumptions underlying the statistical methods, thus providing the tools needed for students to use and interpret statistical data effectively.

Essential Statistics 4th Table of contents:

Part 1: Introduction

Chapter 1: Introduction to Statistics
1.1. What is Statistics?
1.2. Types of Statistics
1.3. The Role of Statistics in Research
1.4. The Four-Step Statistical Process
1.5. Descriptive and Inferential Statistics
1.6. Population vs. Sample
1.7. Variables and Data Types
1.8. Scales of Measurement
1.9. Statistical Software and Calculators

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Part 2: Descriptive Statistics

Chapter 2: Organizing Data
2.1. Frequency Distributions
2.2. Grouped Frequency Distributions
2.3. Histograms
2.4. Frequency Polygons
2.5. Cumulative Frequency Distributions
2.6. Ogives
2.7. Stem-and-Leaf Displays
2.8. Time Series Graphs
2.9. Bar Graphs
2.10. Pie Charts

Chapter 3: Numerical Descriptive Measures
3.1. Measures of Central Tendency
3.2. Mean, Median, and Mode
3.3. Measures of Dispersion
3.4. Range
3.5. Variance and Standard Deviation
3.6. The Empirical Rule
3.7. Chebyshev’s Theorem
3.8. Z-Scores
3.9. Boxplots and Five-Number Summary
3.10. Percentiles and Quartiles

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Part 3: Probability and Distributions

Chapter 4: Probability
4.1. Introduction to Probability
4.2. The Classical Approach to Probability
4.3. The Empirical Approach to Probability
4.4. The Subjective Approach to Probability
4.5. The Law of Large Numbers
4.6. Addition Rule of Probability
4.7. Multiplication Rule of Probability
4.8. Conditional Probability
4.9. The Multiplication Rule for Independent Events
4.10. Bayes’ Theorem

Chapter 5: Discrete Probability Distributions
5.1. Introduction to Discrete Distributions
5.2. The Binomial Distribution
5.3. The Poisson Distribution
5.4. The Hypergeometric Distribution
5.5. Mean, Variance, and Standard Deviation of Discrete Distributions
5.6. The Geometric Distribution
5.7. The Negative Binomial Distribution
5.8. The Hypergeometric Distribution

Chapter 6: The Normal Distribution
6.1. Characteristics of the Normal Distribution
6.2. The Standard Normal Distribution
6.3. The 68-95-99.7 Rule
6.4. Z-Scores and Normal Probability Calculations
6.5. Finding Areas Under the Normal Curve
6.6. The Central Limit Theorem

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Part 4: Inferential Statistics

Chapter 7: Estimation
7.1. Sampling and Sampling Distributions
7.2. Point Estimators
7.3. Confidence Intervals for the Mean
7.4. Confidence Intervals for Proportions
7.5. Margin of Error
7.6. Confidence Intervals for the Difference Between Two Means
7.7. Confidence Intervals for the Difference Between Two Proportions
7.8. Using the t-Distribution
7.9. Sample Size Determination

Chapter 8: Hypothesis Testing
8.1. The Basics of Hypothesis Testing
8.2. Null and Alternative Hypotheses
8.3. Type I and Type II Errors
8.4. The Five-Step Hypothesis Testing Procedure
8.5. Hypothesis Tests for Population Means
8.6. Hypothesis Tests for Population Proportions
8.7. Two-Tailed and One-Tailed Tests
8.8. Hypothesis Tests for Two Population Means
8.9. Hypothesis Tests for Two Population Proportions

Chapter 9: Inferences About Two Samples
9.1. Confidence Intervals for Two Means
9.2. Hypothesis Tests for Two Means
9.3. Paired Sample t-Test
9.4. Comparing Two Proportions
9.5. Analysis of Variance (ANOVA)
9.6. The F-Distribution
9.7. One-Way ANOVA

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Part 5: Regression and Correlation

Chapter 10: Linear Regression and Correlation
10.1. Scatterplots and Correlation
10.2. The Least Squares Regression Line
10.3. Interpretation of the Regression Coefficients
10.4. Residuals and the Linearity Assumption
10.5. Correlation and Causality
10.6. The Coefficient of Determination (R²)
10.7. Hypothesis Testing for Regression Parameters
10.8. Prediction and Confidence Intervals

Chapter 11: Multiple Regression and Model Building
11.1. Introduction to Multiple Regression
11.2. The Multiple Regression Model
11.3. Interpreting Regression Coefficients in Multiple Regression
11.4. Collinearity and Multicollinearity
11.5. Stepwise Regression
11.6. Model Building Techniques

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Part 6: Nonparametric Statistics

Chapter 12: Nonparametric Methods
12.1. Introduction to Nonparametric Tests
12.2. The Sign Test
12.3. The Wilcoxon Signed-Rank Test
12.4. The Rank-Sum Test (Mann-Whitney U Test)
12.5. The Kruskal-Wallis Test
12.6. The Chi-Square Test for Goodness of Fit
12.7. The Chi-Square Test for Homogeneity
12.8. The Fisher Exact Test

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Appendices

• A. Probability Distributions
• B. Tables
• C. Answers to Odd-Numbered Exercises
• D. Index

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