Module 4

This course is a part of Algebra II (Eureka Math/EngageNY), a 4-course Topic series from Khan Academy.

"Students build a formal understanding of probability, considering complex events such as unions, intersections, and complements as well as the concept of independence and conditional probability. The idea of using a smooth curve to model a data distribution is introduced along with using tables and technology to find areas under a normal curve. Students make inferences and justify conclusions from sample surveys, experiments, and observational studies. Data is used from random samples to estimate a population mean or proportion. Students calculate margin of error and interpret it in context. Given data from a statistical experiment, students use simulation to create a randomization distribution and use it to determine if there is a significant difference between two treatments." Eureka Math/EngageNY (c) 2015 GreatMinds.org

This course contains 15 segments:

Topic A: Lesson 1: Chance experiments, sample spaces, and events

Topic A: Lessons 2-4: Two-way tables, conditional probability, and independence

Topic A: Lessons 5-7: Venn diagrams and probability rules

Topic B: Lesson 8: Distributions—Center, shape, and spread

Topic B: Lesson 9: Using a curve to model a data distribution

Topic B: Lessons 10-11: Normal distributions

Topic C: Lesson 12: Types of statistical studies

Topic C: Lesson 13: Using sample data to estimate a population characteristic

Topic C: Lessons 14-17: Sample proportions, sampling variability, margin of error

Topic C: Lessons 18-19: Sampling variability in the sample mean

Topic C: Lessons 20-22: Margin of error with sample means; evaluating reports with sample data

Topic D: Lesson 23: Experiments and the role of random assignment

Topic D: Lessons 24-27: Ruling out differences due to random assignment

Topic D: Lessons 28-29: Drawing a conclusion from an experiment

Topic D: Lesson 30: Evaluating reports based on data from an experiment