 # Statistics

Data, data, everywhere you go! Information has gone from scarce to superabundant thanks to the powers of the internet and computing. But all this data means nothing without the ability to transform it in into something useful. Enter statistics. Everyone from crime analysts to journalists, Fortune 500 CEOs to insurance agents rely on statistics to analyze the information they need to make the best decisions. This class will give you the methods and know-how you need to discern probabilities, understand variables, and accurately measure and display data. In-depth labs and activities will help you soak up the entire statistical process including design, analysis, and conclusions.

RECOMMENDED PREREQUISITE: Algebra II

Basic and On Demand are always open for registration.

Plus courses are created upon request.

## SEMESTER 1

Unit 1: Sampling

• Intro to Sampling and Experiments
• Note-taking Suggestions for Sampling
• 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 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

## SEMESTER 2

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