# Alignment: OpenStax • Introductory Statistics

Use Nagwa in conjunction with your preferred textbook. The recommended lessons from Nagwa for each section of this textbook are provided below. This alignment is not affiliated with, sponsored by, or endorsed by the publisher of the referenced textbook. Nagwa is a registered trademark of Nagwa Limited. All other trademarks and registered trademarks are the property of their respective owners.

• Chapter 1 Sampling and Data
• 1.1 Definitions of Statistics, Probability, and Key Terms
• 1.2 Data, Sampling, and Variation in Data and Sampling
• 1.3 Frequency, Frequency Tables, and Levels of Measurement
• 1.4 Experimental Design and Ethics
• 1.5 Data Collection Experiment
• 1.6 Sampling Experiment
• Chapter 2 Descriptive Statistics
• 2.1 Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs
• 2.2 Histograms, Frequency Polygons, and Time Series Graphs
• 2.3 Measures of the Location of the Data
• 2.4 Box Plots
• 2.5 Measures of the Center of the Data
• 2.6 Skewness and the Mean, Median, and Mode
• 2.7 Measures of the Spread of the Data
• 2.8 Descriptive Statistics
• Chapter 3 Probability Topics
• 3.1 Terminology
• 3.2 Independent and Mutually Exclusive Events
• 3.3 Two Basic Rules of Probability
• 3.4 Contingency Tables
• 3.5 Tree and Venn Diagrams
• 3.6 Probability Topics
• Chapter 4 Discrete Random Variables
• 4.1 Probability Distribution Function (PDF) for a Discrete Random Variable
• 4.2 Mean or Expected Value and Standard Deviation
• 4.3 Binomial Distribution
• 4.4 Geometric Distribution
• 4.5 Hypergeometric Distribution
• 4.6 Poisson Distribution
• 4.7 Discrete Distribution (Playing Card Experiment)
• 4.8 Discrete Distribution (Lucky Dice Experiment)
• Chapter 5 Continuous Random Variables
• 5.1 Continuous Probability Functions
• 5.2 The Uniform Distribution
• 5.3 The Exponential Distribution
• 5.4 Continuous Distribution
• Chapter 6 The Normal Distribution
• 6.1 The Standard Normal Distribution
• 6.2 Using the Normal Distribution
• 6.3 Normal Distribution (Lap Times)
• 6.4 Normal Distribution (Pinkie Length)
• Chapter 7 The Central Limit Theorem
• 7.1 The Central Limit Theorem for Sample Means (Averages)
• 7.2 The Central Limit Theorem for Sums
• 7.3 Using the Central Limit Theorem
• 7.4 Central Limit Theorem (Pocket Change)
• 7.5 Central Limit Theorem (Cookie Recipes)
• Chapter 8 Confidence Intervals
• 8.1 A Single Population Mean Using the Normal Distribution
• 8.2 A Single Population Mean Using the Student t Distribution
• 8.3 A Population Proportion
• 8.4 Confidence Interval (Home Costs)
• 8.5 Confidence Interval (Place of Birth)
• 8.6 Confidence Interval (Women’s Heights)
• Chapter 9 Hypothesis Testing with One Sample
• 9.1 Null and Alternative Hypotheses
• 9.2 Outcomes and the Type I and Type II Errors
• 9.3 Distribution Needed for Hypothesis Testing
• 9.4 Rare Events, the Sample, Decision and Conclusion
• 9.5 Additional Information and Full Hypothesis Test Examples
• 9.6 Hypothesis Testing of a Single Mean and Single Proportion
• Chapter 10 Hypothesis Testing with Two Samples
• 10.1 Two Population Means with Unknown Standard Deviations
• 10.2 Two Population Means with Known Standard Deviations
• 10.3 Comparing Two Independent Population Proportions
• 10.4 Matched or Paired Samples
• 10.5 Hypothesis Testing for Two Means and Two Proportions
• Chapter 11 The Chi-Square Distribution
• 11.1 Facts about the Chi-Square Distribution
• 11.2 Goodness-of-Fit Test
• 11.3 Test of Independence
• 11.4 Test for Homogeneity
• 11.5 Comparison of the Chi-Square Tests
• 11.6 Test of a Single Variance
• 11.7 Lab 1: Chi-Square Goodness-of-Fit
• 11.8 Lab 2: Chi-Square Test of Independence
• Chapter 12 Linear Regression and Correlation
• 12.1 Linear Equations
• 12.2 Scatter Plots
• 12.3 The Regression Equation
• 12.4 Testing the Significance of the Correlation Coefficient
• 12.5 Prediction
• 12.6 Outliers
• 12.7 Regression (Distance from School)
• 12.8 Regression (Textbook Cost)
• 12.9 Regression (Fuel Efficiency)
• Chapter 13 F Distribution and One-Way ANOVA
• 13.1 One-Way ANOVA
• 13.2 The F Distribution and the F-Ratio
• 13.3 Facts about the F Distribution
• 13.4 Test of Two Variances
• 13.5 Lab: One-Way ANOVA