---
title: Introducing the Third Edition of Discovering Statistics and Data – News from the Nest
description: We're proud to announce the new edition of Discovering Statistics and Data! This new edition pays homage to modern day's technology-driven data explosion, helping students understand the context behind future statistical concepts to be learned and explaining why the study of statistics is critical. View a free sample of the new edition of Discovering Statistics and Data. The text opens by describing the necessity…
---

[News from the Nest ](https://www.hawkeslearning.com/blog)

# [Introducing the Third Edition of Discovering Statistics and Data – News from the Nest](https://www.hawkeslearning.com/blog/introducing-the-third-edition-of-discovering-statistics-and-data)

 Written by [Hawkes Learning](https://www.hawkeslearning.com/blog/author/hawkes-learning) | Jan 15, 2018 5:00:00 AM

We’re proud to announce the new edition of *Discovering Statistics and Data*!

This new edition pays homage to modern day’s technology-driven data explosion, helping students understand the context behind future statistical concepts to be learned and explaining why the study of statistics is critical.  
[View a free sample of the new edition of *Discovering Statistics and Data*.](https://downloads.hawkeslearning.com/Docs/resources/DIS3/DIS_3e_AIE_978-1-946158-82-6_1-5Sample.pdf)

The text opens by describing the necessity of understanding the data around us, introducing students to what data is, how we measure it, where it comes from, how to visualize it, and what kinds of career opportunities surround its analysis and processing. This focus makes upcoming content more meaningful for students and then challenges them to *think *with statistics. [Request an examination copy.](https://www.hawkeslearning.com/Instructors/RequestAReviewCopy.htm)

NEW features include:

- **Greater focus on data** – Introductory chapters place a strong emphasis on helping students understand where data comes from, data visualization techniques, “Big Data,” and the problems arising from having large data sets.

- **Downloadable data sets** – More real data sets are available for download, including over 15 large data sets and one giant data set.** **

- **More technology integration** – Detailed instruction using graphing calculators, Excel, Minitab, and R Statistical language are included.

- **Real-world applications** – Larger scale chapter projects challenge students and brief, relatable articles engage readers.

- **Expanded exercises and examples** – Over 60 examples and 200 exercises, including new conceptual questions, have been added.

- **Pedagogy modernization** – GAISE guidelines were carefully considered and incorporated, and the most current *P*-value significance testing recommendations published by the ASA for guidance on hypothesis testing are included.

- **Virtual simulations and games** – Students develop conceptual understanding and statistical literacy through hands-on interactives and simulations.

## Table of Contents:

### **1. Statistics and Problem Solving**

##### The Meaning of Data Statistics as a Career The Data Explosion Modern Computing, Networks, and Statistics Big Data Introduction to Statistical Thinking Descriptive vs. Inferential Statistics The Consequences of Statistical Illiteracy

### **2. Data, Reality, and Problem Solving**

##### Collecting Data Data Classification Time Series Data vs. Cross-Sectional Data Data Resources

### **3. Visualizing Data**

##### Frequency Distributions Displaying Qualitative Data Graphically Constructing Frequency Distributions for Quantitative Data Histograms and Other Graphical Displays of Quantitative Data Analyzing Graphs

### **4. Describing and Summarizing Data from One ****Variable**

##### Measures of Location Measures of Dispersion Measures of Relative Position, Box Plots, and Outliers Data Subsetting Analyzing Grouped Data Proportions and Percentages

### **5. Discovering Relationships**

##### Scatterplots and Correlation Fitting a Linear Model Evaluating the Fit of a Linear Model Fitting a Linear Time Trend Scatterplots for More Than Two Variables

### **6. Probability, Randomness, and Uncertainty**

##### Introduction to Probability Addition Rules for Probability Multiplication Rules for Probability Combinations and Permutations Combining Probability and Counting Techniques Bayes’ Theorem

### **7. Discrete Probability Distributions**

##### Types of Random Variables Discrete Random Variables The Discrete Uniform Distribution The Binomial Distribution The Poisson Distribution The Hypergeometric Distribution

### **8. Continuous Probability Distributions**

##### The Uniform Distribution The Normal Distribution The Standard Normal Distribution Applications of the Normal Distribution Assessing Normality Approximations to Other Distributions

### **9. Samples and Sampling Distributions**

##### Random Samples and Sampling Distributions The Distribution of the Sample Mean and the Central Limit Theorem The Distribution of the Sample Proportion Other Forms of Sampling

### **10. Estimation: Single Samples**

##### Point Estimation of the Population Mean Interval Estimation of the Population Mean Estimating the Population Proportion Estimating the Population Standard Deviation or Variance Confidence Intervals Based on Resampling (Bootstrapping) *(Courseware only)*

### **11. Hypothesis Testing: Single Samples**

##### Introduction to Hypothesis Testing Testing a Hypothesis about a Population Mean The Relationship between Confidence Interval Estimation and Hypothesis Testing Testing a Hypothesis about a Population Proportion Testing a Hypothesis about a Population Standard Deviation or Variance Practical Significance vs. Statistical Significance

### **12. Inferences about Two Samples**

##### Inference about Two Means: Independent Samples Inference about Two Means: Dependent Samples (Paired Difference) Inference about Two Population Proportions Inference about Two Population Standard Deviations or Variances

### **13. Regression, Inference, and Model Building**

##### Assumptions of the Simple Linear Model Inference Concerning β1 Inference Concerning the Model’s Prediction

### **14. Multiple Regression**

##### The Multiple Regression Model The Coefficient of Determination and Adjusted R2 Interpreting the Coefficients of the Multiple Regression Model Inference Concerning the Multiple Regression Model and its Coefficients Inference Concerning the Model’s Prediction Multiple Regression Models with Qualitative Independent Variables

### **15. Analysis of Variance (ANOVA)**

##### One-Way ANOVA Two-Way ANOVA: The Randomized Block Design Two-Way ANOVA: The Factorial Design

### **16. Looking for Relationships in Qualitative Data**

##### The Chi-Square Distribution The Chi-Square Test for Goodness of Fit The Chi-Square Test for Association

### **17. Nonparametric Tests**

##### The Sign Test The Wilcoxon Signed-Rank Test The Wilcoxon Rank-Sum Test The Rank Correlation Test The Runs Test for Randomness The Kruskal-Wallis Test

### **18. Statistical Process Control** *(Courseware only)*

[Request an examination copy.](https://www.hawkeslearning.com/Instructors/RequestAReviewCopy.htm)

Want to know more? Contact us at [sales@hawkeslearning.com](mailto:sales@hawkeslearning.com)!

[View full post](https://www.hawkeslearning.com/blog/introducing-the-third-edition-of-discovering-statistics-and-data)

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