# Statistics

## Course Summary

Learn how to transform seemingly meaningless data into useful information. Discover how crime analysts, journalists, Fortune 500 CEOs, insurance agents, and so many others rely on statistics to analyze data to help them make the best decisions. Students master the methods and know-how of statistics to discern probabilities, understand variables, and accurately measure and display data.

In this course, students participate in labs and activities that engage with the entire statistical process including design, analysis, and conclusions.

**Course Prerequisite(s):**Algebra 2

## Curriculum

This is a 2-semester course. We do not recommend taking both semesters simultaneously.

##### Unit 1: Sampling

- Intro to Sampling and Experiments
- Note-taking Suggestions for Sampling
- Bad Samples
- Types of Bias
- Good Samples
- Random Number Tables and Generators

##### Unit 2: Experiments

- Key Terms in Experimental Design
- Completely Randomized Design
- Block Design
- Matched Pairs Design
- Review of Sampling and Experiments

##### Unit 3: Describing Distributions with Graphs for Univariate Data

- Introduction to Describing Distributions
- Note-taking Suggestion for Describing Distributions
- Pie Charts and Bar Charts
- Segmented Bar Graphs
- Describing Graphs
- Dot Plots
- Stemplots
- Comparing Graphs
- Histograms

##### Unit 4: Describing Distributions with Numbers (Statistics)

- Measures of Center
- Measures of Spread Range
- Measures of Spread Standard Deviation
- Outliers
- Box and Whiskers
- Review of Describing Distributions

##### Unit 5: Probability (Simulations)

- Introduction to Probability
- Simulation Process
- Simulation Assigning Digits
- Simulation Practice

##### Unit 6: Probability (Independent and Disjoint Events)

- Key Terms and Ideas
- Probability Formulas
- Practice
- Disjoint Events
- Independent Events
- Venn Diagrams
- Practice

##### Unit 7: Probability (General Probability Rules)

- Two-Way Tables
- Conditional Probability
- Independence Revisited
- Practice
- Review of Probability

##### Unit 8: Discrete Random Variables

- Introduction to Discrete Random Variables
- Probability Distribution Function for a Discrete RV
- Mean and Standard Deviation of a Discrete RV
- Rules for Means
- Rules for Variances

##### Unit 9: Discrete Random Variables (Special Distribution)

- Binomial Distribution Definition and Formulas
- Binomial Distribution Applications
- Mean and Standard Deviation of a Binomial
- Geometric Distributions Definition and Formulas
- Geometric Distributions Applications
- Mean of a Geometric Distribution
- Binomial and Geometric Exploration
- Review of Discrete Random Variables

##### Unit 10: Density Curves

- Introduction to Density Curves
- Uniform Density Curves
- Funky Figures
- Mean vs Median

##### Unit 11: Density Curves (Normal Distribution)

- Standardization (z scores)
- What is a Normal Curve?
- Empirical Rule
- Z-Scores Revisited
- More Normal Distribution
- Calculator Lesson: Replacing the Chart
- Review of Density Curves

##### Unit 12: Linear Regression

- Introduction to Linear Regression
- Scatterplots
- Correlation (r)
- What is an LSRL
- Interpreting Slope and Y-Intercept
- Finding and Interpreting Correlation (r)
- More Ways to Find LSRL
- Predicting and Residuals
- Review of Linear Regression