1: The Nature of Probability and Statistics

1.3: Data Collection and Sampling Techniques

Describing Data Using Statistics
Polling: City
Populations and Samples

1.4: Observational and Experimental Studies

Binomial Probabilities
Geometric Probability
Independent and Dependent Events
Real-Time Histogram

2: Frequency Distributions and Graphs

2.1: Organizing Data

Box-and-Whisker Plots
Describing Data Using Statistics
Stem-and-Leaf Plots

2.2: Histograms, Frequency Polygons, and Ogives

Histograms
Real-Time Histogram
Sight vs. Sound Reactions

2.3: Other Types of Graphs

Distance-Time Graphs

3: Data Description

3.1: Measures of Central Tendency

Box-and-Whisker Plots
Describing Data Using Statistics
Mean, Median, and Mode
Reaction Time 1 (Graphs and Statistics)
Stem-and-Leaf Plots

3.2: Measures of Variation

Box-and-Whisker Plots
Describing Data Using Statistics
Real-Time Histogram

3.3: Measures of Position

Box-and-Whisker Plots

3.4: Exploratory Data Analysis

Polling: City
Real-Time Histogram

4: Probability and Counting Rules

4.1: Sample Spaces and Probability

Probability Simulations
Theoretical and Experimental Probability

4.3: The Multiplication Rules and Conditional Probability

Independent and Dependent Events

4.5: Probability and Counting Rules

Probability Simulations

5: Discrete Probability Distributions

5.1: Probability Distributions

Polling: City

5.2: Mean, Variance, Standard Deviation, and Expectation

Describing Data Using Statistics
Geometric Probability
Independent and Dependent Events
Mean, Median, and Mode
Polling: City
Populations and Samples
Probability Simulations
Real-Time Histogram
Sight vs. Sound Reactions
Stem-and-Leaf Plots
Theoretical and Experimental Probability

5.3: The Binomial Distribution

Binomial Probabilities

5.4: Other Types of Distributions (Optional)

Polling: City

6: The Normal Distribution

6.1: Normal Distributions

Polling: City
Populations and Samples
Sight vs. Sound Reactions

6.2: Applications of the Normal Distribution

Polling: City

6.3: The Central Limit Theorem

Populations and Samples

10: Correlation and Regression

10.1: Scatter Plots and Correlation

Correlation
Least-Squares Best Fit Lines
Solving Using Trend Lines
Trends in Scatter Plots

10.2: Regression

Least-Squares Best Fit Lines