Preparation for College Mathematics and Software

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Discovering Statistics and Data, 4th Edition

by James S. Hawkes

Discovering Statistics and Data is intended for an introductory statistics course and is written in a relaxed, conversational style, with occasional remarks that are intended to both engage and bring a smile to the reader. The fourth edition of Discovering Statistics and Data by James Hawkes presents important concepts and techniques in a straightforward, step-by-step manner. Used on its own, or with the following supplementary materials, this text provides a solid foundation in statistics for both STEM and non-STEM majors.

Companion Website

A curated list of resources for this title is available at stat.hawkeslearning.com. This companion website features:

  • Free, real-world data sets

  • Step-by-step instructions for TI calculators, Excel, Minitab®, SPSS, JMP, and Rguroo

  • Chapter projects that apply lessons to real-life scenarios

  • Links to data visualization resources

  • External videos explaining key topics

Bundling options include Minitab®, SPSS, JMP, and Rguroo.

Formats: Software, Textbook, eBook

Product ISBN
Software + eBook 978‑1‑64277‑715‑4
Software + eBook + Textbook 978‑1‑64277‑888‑5

Table of Contents

  1. Chapter 1: Statistics: Thinking with Data
    1. 1.1 Introduction to Statistical Thinking
    2. 1.2 Basic Statistical Concepts
    3. 1.3 Descriptive versus Inferential Statistics
    4. 1.4 The Value of Statistical Literacy
    5. 1.5 Statistics and Related Fields as a Career
  2. Chapter 2: Foundations of Data Analysis
    1. 2.1 The Evolution of Data
    2. 2.2 Empirical Foundations: Measurement and Scales
    3. 2.3 Empiricism at Work: Data Collection and The Scientific Method
    4. 2.4 Data Classification
    5. 2.5 Time Series Data versus Cross-Sectional Data
  3. Chapter 3: Visualizing Data
    1. 3.1 Frequency Distributions
    2. 3.2 Displaying Qualitative Data Graphically
    3. 3.3 Displaying Quantitative Data Graphically
    4. 3.4 Analyzing Graphs
  4. Chapter 4: Describing and Summarizing Data from One Variable
    1. 4.1 Measures of Location
    2. 4.2 Measures of Dispersion
    3. 4.3 Measures of Relative Position, Box Plots, and Outliers
    4. 4.4 Data Subsetting
    5. 4.5 Analyzing Grouped Data
    6. 4.6 Proportions and Percentages
  5. Chapter 5: Discovering Relationships
    1. 5.1 Scatterplots and Correlation
    2. 5.2 Fitting a Linear Model
    3. 5.3 Evaluating the Fit of a Linear Model
    4. 5.4 Fitting a Linear Time Trend
    5. 5.5 Scatterplots for More Than Two Variables
  6. Chapter 6: Probability, Randomness, and Uncertainty
    1. 6.1 Introduction to Probability
    2. 6.2 Addition Rules for Probability
    3. 6.3 Multiplication Rules for Probability
    4. 6.4 Combinations and Permutations
    5. 6.5 Bayes' Theorem
  7. Chapter 7: Discrete Probability Distributions
    1. 7.1 Types of Random Variables and Probability Distributions
    2. 7.2 Expected Value and Variance
    3. 7.3 The Discrete Uniform Distribution
    4. 7.4 The Binomial Distribution
    5. 7.5 The Poisson Distribution
    6. 7.6 The Hypergeometric Distribution
  8. Chapter 8: Continuous Probability Distributions
    1. 8.1 The Uniform Distribution
    2. 8.2 The Normal Distribution
    3. 8.3 The Standard Normal Distribution
    4. 8.4 Applications of the Normal Distribution
    5. 8.5 Assessing Normality
    6. 8.6 Approximation to the Binomial Distribution
  9. Chapter 9: Samples and Sampling Distributions
    1. 9.1 Random Samples and Sampling Distributions
    2. 9.2 The Distribution of the Sample Mean and the Central Limit Theorem
    3. 9.3 The Distribution of the Sample Proportion
    4. 9.4 Other Forms of Sampling
  10. Chapter 10: Estimation: Single Samples
    1. 10.1 Point Estimation of Population Parameters
    2. 10.2 Estimating the Population Mean, σ Known
    3. 10.3 Estimating the Population Mean, σ Unknown
    4. 10.4 Estimating the Population Proportion
    5. 10.5 Estimating the Population Standard Deviation or Variance
  11. Chapter 11: Hypothesis Testing: Single Samples
    1. 11.1 Introduction to Hypothesis Testing
    2. 11.2 Testing a Hypothesis about a Population Mean, σ Known
    3. 11.3 Testing a Hypothesis about a Population Mean, σ Unknown
    4. 11.4 The Relationship Between Confidence Interval Estimation and Hypothesis Testing
    5. 11.5 Testing a Hypothesis about a Population Proportion
    6. 11.6 Testing a Hypothesis about a Population Standard Deviation or Variance
  12. Chapter 12: Inferences about Two Samples
    1. 12.1 Inferences about Two Population Means: Independent Samples, σ1 and σ2 Known
    2. 12.2 Inferences about Two Population Means: Independent Samples, σ1 and σ2 Unknown
    3. 12.3 Inference about Two Population Means: Dependent Samples (Paired Difference)
    4. 12.4 Inference about Two Population Proportions
    5. 12.5 Inference about Two Population Variances
  13. Chapter 13: Regression, Inference, and Model Building
    1. 13.1 Assumptions of the Simple Linear Model
    2. 13.2 Inference Concerning β1
    3. 13.3 Inference Concerning the Model's Prediction
  14. Chapter 14: Multiple Regression
    1. 14.1 The Multiple Regression Model
    2. 14.2 The Coefficient of Determination and Adjusted R2
    3. 14.3 Inference Concerning the Multiple Regression Model and Its Coefficients
    4. 14.4 Inference Concerning the Model's Prediction
    5. 14.5 Multiple Regression Models with Qualitative Independent Variables
  15. Chapter 15: Analysis of Variance (ANOVA)
    1. 15.1 One-Way ANOVA
    2. 15.2 Multiple Comparison Procedures
    3. 15.3 Two-Way ANOVA: The Randomized Block Design
    4. 15.4 Two-Way ANOVA: The Factorial Design
  16. Chapter 16: Looking for Relationships in Qualitative Data
    1. 16.1 The Chi-Square Distribution
    2. 16.2 The Chi-Square Test for Goodness of Fit
    3. 16.3 The Chi-Square Test for Association
  17. Chapter 17: Nonparametric Tests
    1. 17.1 The Sign Test
    2. 17.2 The Wilcoxon Signed-Rank Test
    3. 17.3 The Wilcoxon Rank-Sum Test
    4. 17.4 The Rank Correlation Test
    5. 17.5 The Runs Test for Randomness
    6. 17.6 The Kruskal-Wallis Test