# AP Statistics

What do genetics, weather forecasting, emergency preparedness, political campaigns, and medical studies all have in common? The answer is statistics. Statistics is the mathematical science of gathering, grouping, and interpreting numerical data. And in this day and age, there’s a lot of data to make sense of. We’re going to help you get the statistical know-how to turn an intimidating Everest-sized mountain of numerical data points into a simple answer. Students are required to have access to a graphing scientific calculator. RECOMMENDED PREREQUISITE: Successful completion of Algebra I required. Algebra II is recommended. Concurrent enrollment in Algebra II is acceptable.

Basic and On Demand are always open for registration.

Plus courses are created upon request.

## SEMESTER 1

**Unit 1: Describing Distributions**

- Pie Charts and Bar Charts
- Describing Graphs
- Dotplots
- Stemplots
- Comparing Graphs
- Histograms
- Ogives
- Calculator Lesson: Graphing Univariate Graphs
- Measures of Center
- Measures of Spread Part 1
- Measures of Spread Part 2
- Outliers
- Box and Whisker Plots
- Comparing Distributions Again
- Boxplot/Histogram Exploration

**Unit 2: Density Curves and Normal Distributions**

- Uniform Density Curves
- Funky Figures
- Mean vs Median
- Standardization (z-scores)
- What is a Normal Curve?
- Empirical Rule
- z-scores Revisited
- More Normal Distribution
- Is the Data Normal?
- Calculator Lesson: normalcdf and invNorm

**Unit 3: Linear Regression**

- Scatterplots
- Correlation
- What is an LSRL?
- Interpreting Slope and y-intercept
- Finding and Interpreting the Correlation Coefficient (r)
- More Ways to Find the LSRL
- More Ways to Find the LSRL Part 2
- Predicting and Residuals
- Coefficient of Determination (r^2)
- Linear Regression: Putting It Together
- Residual Plots
- Exponential Data
- Power Data
- Residual Plots Revisited

**Unit 4: Sampling and Experiments**

- Bad Samples
- Types of Bias
- Good Samples = Random Samples
- Using Random Numbers for Sampling
- Key Terms in Experimental Design
- Completely Randomized Design
- Block Design
- Matched Pairs

**Unit 5: Probability**

- Simulation
- Simulation Practice
- Key Terms and Ideas
- Formulas on the AP Exam
- Disjoint Events
- Independent Events
- Venn Diagrams
- Two Way Tables
- Conditional Probability
- Independence Revisited

**Unit 6: Discrete Random Variables**

- Probability Distributions for Random Variables
- Mean and Standard Deviation of Discrete Random Variables
- Rules for Means
- Rules for Variances
- Binomial Distribution Part 1
- Binomial Distribution Part 2
- Mean and Standard Deviation of Binomial Distributions
- Geometric Distribution Part 1
- Geometric Distribution Part 2
- Mean of Geometric Distributions
- Binomial, Geometric and Normal Exploration

## SEMESTER 2

**Unit 7: Sampling Distributions**

- Introduction
- Funky Figures Revisited
- Normal Distribution Review
- Overview of Sampling Distributions
- Sampling Distribution for x-bar
- Central Limit Theorem
- Sampling Distribution for p-hat
- Conditions for Inference - Proportions
- Review

**Unit 8: Confidence Intervals for 1-Sample Data**

- Introduction
- Structure of a Confidence Interval
- Confidence Interval for a Single Mean (z-interval)
- Practice with Confidence Intervals for a Single Mean (z-interval)
- What is a t-distribution?
- Confidence Interval for a Single Mean (t-interval)
- Matched Pairs t-interval
- Calculator Lesson: t-interval
- Confidence Interval for Single Proportion (1-proportion z-interval)
- Calculator Lesson: 1-proportion z-interval
- Confidence Level and Finding n
- Review

**Unit 9: Significance Test for 1-Sample Data**

- Introduction
- Structure of a Test Part 1
- Structure of a Test Part 2
- One Sample t-test for Means (The Mechanics)
- One Sample t-test for Means (Complete Test)
- Calculator Lesson: One Sample t-test for Means
- One Sample t-test for Means (Matched Pairs)
- One Sample z-test for Proportions (The Mechanics)
- One Sample z-test for Proportions (Complete Test)
- Calculator Lesson: One Sample z-test for Proportions
- Significance Level and Overview of Errors
- Type I and Type II Errors
- Power
- Review
- Hypothesis Tests and Confidence Intervals

**Unit 10: Inference for 2-Sample Data**

- Introduction
- Two-Sample t-interval for Means
- Calculator Lesson: Two-sample t-interval
- Two-Sample t-test for Means
- Calculator Lesson: Two-Sample t-test for Means
- Two-Sample z-interval for Proportions
- Calculator Lesson: Two-Sample z-interval for Proportions
- Two-Sample z-test for Proportions
- Calculator Lesson: Two-Sample z-test for Proportions
- Review

**Unit 11: Chi-Square Distribution**

- Introduction
- Chi-Square Goodness of Fit Test - The Components
- Chi-Square Goodness of Fit Test - The Complete Test
- Calculator Lesson: Chi-Square Goodness of Fit Test
- Review of Two-Way Tables
- Chi-Square Test for Independence - The Components
- Chi-Square Test for Independence - The Complete Test
- Calculator Lesson: Chi-Square Test for Independence
- Review

**Unit 12: Inference for Regression**

- Introduction
- Review of Linear Regression
- Conditions for Inference for Slope
- Linear Regression t-interval
- Calculator Lesson: Linear Regression t-interval
- Linear Regression t-test for a Slope - The Components
- Linear Regression t-test for a Slope - The Complete Test
- Calculator Lesson: Linear Regression t-test for a Slope
- Review