 # Discovering Statistics and Data + Integrated Review

by James S. Hawkes

Discovering Statistics and Data Plus Integrated Review pays homage to the technology-driven data explosion by introducing students to what data is, how we measure and visualize it, and what kinds of career opportunities involve its analysis and processing. It includes foundational concepts for just-in-time supplementation and support of curricular material.

Discovering Statistics and Data Plus Integrated Review is ideal for corequisite courses and is designed to provide all developmental math content needed to support statistics learners.

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, Discovering Statistics and Data Textbook, eBook, Guided Notebook

Product ISBN
Software + eBook 978-1-64277-040-7
Software + eBook + Integrated Review Guided Notebook 978-1-64277-042-1
Software + eBook + Discovering Statistics and Data Textbook 978-1-64277-041-4

1. 0: Strategies for Academic Success
1. 0.1 How to Read a Math Textbook
2. 0.2 Tips for Success in a Math Course
3. 0.3 Tips for Improving Math Test Scores
4. 0.4 Practice, Patience, and Persistence!
5. 0.5 Note Taking
6. 0.6 Do I Need a Math Tutor?
7. 0.7 Tips for Improving Your Memory
8. 0.8 Overcoming Anxiety
9. 0.9 Online Resources
10. 0.10 Preparing for a Final Math Exam
11. 0.11 Managing Your Time Effectively
2. Chapter 1R: Integrated Review
1. 1.R.1 Problem Solving with Whole Numbers
2. 1.R.2 Introduction to Decimal Numbers
3. 1.R.3 Exponents and Order of Operations
3. Chapter 1: Statistics and Problem Solving
1. 1.1 The Meaning of Data
2. 1.2 Statistics as a Career
3. 1.3 The Data Explosion
4. 1.4 The Fusion of Data, Computing, and Statistics
5. 1.5 Big Data
6. 1.6 Introduction to Statistical Thinking
7. 1.7 Descriptive vs. Inferential Statistics
8. 1.8 The Consequences of Statistical Illiteracy
4. Chapter 2R: Integrated Review
1. 2.R.1 Introduction to Fractions and Mixed Numbers
2. 2.R.2 Decimal Numbers and Fractions
3. 2.R.3 Decimals and Percents
4. 2.R.4 Comparisons and Order of Operations with Fractions
5. 2.R.5 Estimating and Order of Operations with Decimal Numbers
6. 2.R.6 Fractions and Percents
5. Chapter 2: Data, Reality, and Problem Solving
1. 2.1 The Lords of Data
2. 2.2 Data Classification
3. 2.3 Time Series Data vs. Cross-Sectional Data
6. Chapter 3R. Integrated Review
2. 3.R.2 Constructing Graphs from a Database
3. 3.R.3 The Real Number Line and Absolute Value
7. Chapter 3: Visualizing Data
1. 3.1 Frequency Distributions
2. 3.2 Displaying Qualitative Data Graphically
3. 3.3 Constructing Frequency Distributions for Quantitative Data
4. 3.4 Histograms and Other Graphical Displays of Quantitative Data
5. 3.5 Analyzing Graphs
8. Chapter 4R: Integrated Review
1. 4.R.1 Addition with Real Numbers
2. 4.R.2 Subtraction with Real Numbers
3. 4.R.3 Multiplication and Division with Real Numbers
4. 4.R.4 Simplifying and Evaluating Algebraic Expressions
9. 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
10. Chapter 5R: Integrated Review
1. 5.R.1 The Cartesian Coordinate System
2. 5.R.2 Graphing Linear Equations in Two Variables
3. 5.R.3 Slope-Intercept Form
4. 5.R.4 Point-Slope Form
11. 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
12. Chapter 6R: Integrated Review
1. 6.R.1 Multiplication with Fractions
2. 6.R.2 Division with Fractions
3. 6.R.3 Least Common Multiple (LCM)
4. 6.R.4 Addition and Subtraction with Fractions
5. 6.R.5 Addition and Subtraction with Mixed Numbers
6. 6.R.6 Union and Intersection of Sets
13. 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
14. Chapter 7R: Integrated Review
1. 7.R.1 Order of Operations with Real Numbers
2. 7.R.2 Solving Linear Inequalities in One Variable
3. 7.R.3 Compound Inequalities
15. Chapter 7: Discrete Probability Distributions
1. 7.1 Types of Random Variables
2. 7.2 Discrete Random Variables
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
16. Chapter 8R: Integrated Review
1. 8.R.1 Area
2. 8.R.2 Solving Linear Equations: ax + b = c
3. 8.R.3 Working with Formulas
17. 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
18. Chapter 9: Samples and Sampling Distributions
1. 9.1 Random Samples
2. 9.2 Introduction to Sampling Distributions
3. 9.3 The Distribution of the Sample Mean and the
4. Central Limit Theorem
5. 9.4 The Distribution of the Sample Proportion
6. 9.5 Other Forms of Sampling
19. Chapter 10R: Integrated Review
1. 10.R.1 Absolute Value Equations
2. 10.R.2 Absolute Value Inequalities
20. Chapter 10: Estimation: Single Samples
1. 10.1 Point Estimation of the Population Mean
2. 10.2 Interval Estimation of the Population Mean
3. 10.3 Estimating the Population Proportion
4. 10.4 Estimating the Population Standard Deviation
5. or Variance
21. Chapter 11R: Integrated Review
1. 11.R.1 Translating English Phrases and Algebraic Expressions
2. 11.R.2 Applications: Scientific Notation
22. Chapter 11: Hypothesis Testing: Single Samples
1. 11.1 Introduction to Hypothesis Testing
2. 11.2 Testing a Hypothesis about a Population Mean with σ Known and Unknown
3. 11.3 The Relationship Between Confidence Interval Estimation and Hypothesis Testing
4. 11.4 Testing a Hypothesis about a Population Proportion
5. 11.5 Testing a Hypothesis about a Population Standard Deviation or Variance
6. 11.6 Practical Significance vs. Statistical Significance
23. Chapter 12: Inferences about Two Samples
1. 12.1 Inference about Two Means: Independent Samples
2. 12.2 Inference about Two Means: Dependent Samples (Paired Difference)
3. 12.3 Inference about Two Population Proportions
24. 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
25. Chapter 14: Multiple Regression
1. 14.1 The Multiple Regression Model
2. 14.2 The Coefficient of Determination and Adjusted R2
3. 14.3 Interpreting the Coefficients of the Multiple Regression Model
4. 14.4 Inference Concerning the Multiple Regression Model and Its Coefficients
5. 14.5 Inference Concerning the Model’s Prediction
6. 14.6 Multiple Regression Models with Qualitative Independent Variables
26. Chapter 15: Analysis of Variance (ANOVA)
1. 15.1 One-Way ANOVA
2. 15.2 Two-Way ANOVA: The Randomized Block Design
3. 15.3 Two-Way ANOVA: The Factorial Design
27. 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
28. 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
29. Appendix
1. A.1 Name that Distribution
2. A.2 Direct Mail
3. A.3 Type II Errors
4. A.4 Games of Chance
5. A.5 Comparing Two Population Variances
6. A.6 Statistical Process Control