Module 1: Types of Statistical Studies and Producing Data
Module 1: Types of Statistical Studies and Producing Data
Module 2: Summarizing Data Graphically and Numerically
Module 2: Summarizing Data Graphically and Numerically
Module 2: Summarizing Data Graphically and Numerically
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 3: Examining Relationships: Quantitative Data
Module 4: Nonlinear Models
Module 5: Relationships in Categorical Data with Intro to Probability
Module 5: Relationships in Categorical Data with Intro to Probability
Module 5: Relationships in Categorical Data with Intro to Probability
Module 5: Relationships in Categorical Data with Intro to Probability
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 6: Probability and Probability Distributions
Module 7: Linking Probability to Statistical Inference
Module 7: Linking Probability to Statistical Inference
Module 7: Linking Probability to Statistical Inference
Module 7: Linking Probability to Statistical Inference
Module 7: Linking Probability to Statistical Inference
Module 7: Linking Probability to Statistical Inference
Module 8: Inference for One Proportion
Module 8: Inference for One Proportion
Module 8: Inference for One Proportion
Module 8: Inference for One Proportion
Module 8: Inference for One Proportion
Module 8: Inference for One Proportion
Module 8: Inference for One Proportion
Module 8: Inference for One Proportion
Module 9: Inference for Two Proportions
Module 9: Inference for Two Proportions
Module 9: Inference for Two Proportions
Module 9: Inference for Two Proportions
Module 9: Inference for Two Proportions
Module 9: Inference for Two Proportions
Module 9: Inference for Two Proportions
Module 9: Inference for Two Proportions
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 10: Inference for Means
Module 11: Chi-Square Tests
Module 11: Chi-Square Tests
Module 11: Chi-Square Tests
Resources: Course Assignments
Resources: Course Assignments
« Previous
Reading progress:
132%
Next »
Module 9: Inference for Two Proportions
Module 9: Inference for Two Proportions
Introduction to Hypothesis Test for Difference in Two Population Proportions
Introduction to Hypothesis Test for Difference in Two Population Proportions
What you’ll learn to do: Construct and interpret an appropriate hypothesis test to compare two population/treatment group proportions.
In this section we will learn to conduct a hypothesis test for comparing two population proportions or two treatments, under the appropriate conditions, and state a conclusion in context. We can use this to analyze real world examples such as insurance coverage as well as teen depression rates. We will also interpret the P-value as a conditional probability. Then we will then identify type I and type II errors and select an appropriate significance level based on an analysis of the consequences of each type of error.
- Concepts in Statistics. Provided by: Open Learning Initiative. Located at: http://oli.cmu.edu. License: CC BY: Attribution