Discovering Statistics

by James Hawkes and William Marsh

Discovering Statistics provides students with applications of statistics in the real world. Integrated throughout the text is TI calculator, Minitab™, and Microsoft Excel support, including Getting Started guides for Minitab™ and Excel. The included data sets are diverse and useful for multiple courses.

Formats: Software, Textbook, eBook

Product ISBN
Courseware + eBook* 978-1-941552-71-1
Courseware + eBook* + Developmental Mathematics Textbook 978-1-941552-68-1
* Included eBook can only be accessed online through the courseware

Table of Contents

  1. Chapter 1: Statistics and Problem Solving
    1. 1.1 Who Will Be Our Next President?
    2. 1.2 Statistics and Quality
    3. 1.3 Descriptive Versus Inferential Statistics
    4. 1.4 The Consequences of Statistical Illiteracy
  2. Chapter 2: Data, Reality and Problem Solving
    1. 2.1 The Lords of Data
    2. 2.2 Science and Data
    3. 2.3 Decision Making and Data
    4. 2.4 Collecting Data
    5. 2.5 Data Classifications
    6. 2.6 Levels of Measurement
    7. 2.7 Times Series Data
    8. 2.8 Cross – Sectional Data
    9. 2.9 Data Resources
    10. 2.10 Discovering Technology
  3. Chapter 3: Organizing, Displaying, and Interpreting Data
    1. 3.1 Frequency Distributions
    2. 3.2 The Value of Graphs
    3. 3.3 Displaying Qualitative Data Graphically
    4. 3.4 Constructing Frequency Distributions for Quantitative Data
    5. 3.5 Histograms
    6. 3.6 The Stem and Leaf Display
    7. 3.7 The Ordered Array
    8. 3.8 Dot Plots
    9. 3.9 Plotting Time Series Data
    10. 3.10 A Look at World Population
    11. 3.11 Discovering Technology
  4. Chapter 4: Describing Data from One Variable
    1. 4.1 Measures of Location
    2. 4.2 Selecting a Measure of Location
    3. 4.3 Measures of Dispersion
    4. 4.4 Measures of Relative Position
    5. 4.5 Using the Standard Deviation
    6. 4.6 A Second Look at the Tuition Data
    7. 4.7 Data Subsetting
    8. 4.8 The Coefficient of Variation
    9. 4.9 Analyzing Grouped Data
    10. 4.10 Proportions
    11. 4.11 Discovering Technology
  5. Chapter 5: Discovering Relationships
    1. 5.1 Bivariate Data
    2. 5.2 Looking for Patterns in the Data
    3. 5.3 Building a Model
    4. 5.4 Measuring the Degree of Linear Relationship
    5. 5.5 Avoiding Some Correlation Pitfalls
    6. 5.6 Defining a Linear Relationship – Regression Analysis
    7. 5.7 Finding the Least Squares Line
    8. 5.8 Estimating a Linear Relationship
    9. 5.9 Interpreting the Regression Equation
    10. 5.10 The Importance of Errors
    11. 5.11 Evaluating the Fit of a Model
  6. Chapter 6: Probability, Randomness, and Uncertainty
    1. 6.1 Important Definitions
    2. 6.2 Interpreting Probability: Relative Frequency
    3. 6.3 Interpreting Probability: Subjective Approach
    4. 6.4 Interpreting Probability: Classical Approach
    5. 6.5 What is Probability?
    6. 6.6 Some Laws of Probability
    7. 6.7 What’s the Connection Between Probability and Statistics?
    8. 6.8 Probability and Business
    9. 6.9 Other Probability Rules
    10. 6.10 Conditional Probability
    11. 6.11 Independence
    12. 6.12 Counting
    13. 6.13 Discovering Technology
  7. Chapter 7: Probability Distributions, Information about the Future
    1. 7.1 Types of Random Variables
    2. 7.2 Discrete Probability Distributions
    3. 7.3 Expected Value
    4. 7.4 Variance of a Discrete Random Variable
    5. 7.5 Where Do Probability Distributions Come From?
    6. 7.6 The Discrete Uniform Distribution
    7. 7.7 The Binomial Distribution
    8. 7.8 The Poisson Distribution
    9. 7.9 The Hypergeometric Distribution
    10. 7.10 Discovering Technology
  8. Continuous Random Variables
    1. 8.1 The Uniform Distribution
    2. 8.2 The Normal Distribution
    3. 8.3 The Standard Normal
    4. 8.4 z-Transformations
    5. 8.5 Approximations to Other Distributions
    6. 8.6 Discovering Technology
  9. Chapter 9: Samples and Sampling Distributions
    1. 9.1 Random Samples
    2. 9.2 Choosing a Representative Sample
    3. 9.3 Sampling Distributions
    4. 9.4 Statistics as Random Variables?
    5. 9.5 Why Calculate the Sample Mean?
    6. 9.6 The Distribution of the Sample Mean
    7. 9.7 Using the Central Limit Theorem
    8. 9.8 The Distribution of the Sample Proportion
    9. 9.9 Other Forms of Sampling
    10. 9.10 Discovering Technology
  10. Chapter 10: Estimating Means and Proportions
    1. 10.1 What is an Estimator?
    2. 10.2 Discovering the Real World
    3. 10.3 Point Estimation of the Population Mean
    4. 10.4 Interval Estimation of the Population Mean
    5. 10.5 Interval Estimation of the Population Mean for a No
    6. Population with σ Unknown
    7. 10.6 Precision and Sample Size
    8. 10.7 Estimating Population Attributes
    9. 10.8 Interval Estimation of a Population Attribute
    10. 10.9 Precision and Sample Size for Population Attributes
    11. 10.10 Discovering Technology
  11. Chapter 11: Introduction to Hypothesis Testing
    1. 11.1 Developing a Hypothesis
    2. 11.2 Reaching a Conclusion
    3. 11.3 A Procedure for Testing a Hypothesis
    4. 11.4 Testing Hypothesis about a Population Mean
    5. 11.5 Practical Significance versus Statistical Significance
    6. 11.6 Discovering Technology
  12. Chapter 12: Additional Topics with Hypothesis Testing
    1. 12.1 Testing Hypothesis about a Population Proportion
    2. 12.2 Testing Hypothesis about a Population Variance
    3. 12.3 Comparing Two Population Means
    4. 12.4 Paired Difference
    5. 12.5 Comparing Two Population Proportions
    6. 12.6 Discovering Technology
  13. Chapter 13: Regression, Inference, and Model Building
    1. 13.1 Assumptions of the Simple Linear Model
    2. 13.2 Inference – How Good is the Estimate of β1
    3. 13.3 Testing a Hypothesis Concerning β1
    4. 13.4 Inference Concerning Model’s Prediction
    5. 13.5 Multiple Regression
    6. 13.6 Interpreting the Coefficients of the Model
    7. 13.7 The F-Distribution
    8. 13.8 Inference Concerning the Coefficients of the Multiple Regression Model
    9. 13.9 Inference on the Model’s Prediction
    10. 13.10 Discovering Technology
  14. Chapter 14: Analysis of Variance (ANOVA)
    1. 14.1 Are Means from Samples Significantly Different?
    2. 14.2 Analysis of Variance (ANOVA)
    3. 14.3 Assumptions of the Test
    4. 14.4 The F-Test
    5. 14.5 Two-Way ANOVA
    6. 14.6 Discovering Technology
  15. Chapter 15: Looking for Relationships in Qualitative Data
    1. 15.1 The Chi-Square Distribution
    2. 15.2 The Chi-Square Test for Goodness of Fit
    3. 15.3 The Chi-Square Test for Association Between Two Qualitative Variables
    4. 15.4 Discovering Technology
  16. Chapter 16: Nonparametrics
    1. 16.1 The Sign Test
    2. 16.2 The Wilcoxon Signed-Rank Test
    3. 16.3 The Wilcoxon Rank-Sum Test
    4. 16.4 The Rank Correlation Test
    5. 16.5 The Runs Test for Randomness
    6. 16.6 The Kruskal-Wallis Test
    7. 16.7 Discovering Technology
  17. Chapter 17: Statistical Process Control
    1. 17.1 Basic Charts and Diagrams Used in Quality Control
    2. 17.2 Basic Concepts
    3. 17.3 Monitoring with an x Chart
    4. 17.4 Monitoring with an R Chart
    5. 17.5 Monitoring with a p Chart
    6. 17.6 Discovering Technology
  18. Appendix
    1. A.1 Statistical Tables
    2. A.2 Case Data
    3. A.3 Getting Started with Excel
    4. A.4 Getting Started with Minitab
    5. A.5 Answers to Odd Numbered Problems