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:
154%
Next »
Module 10: Inference for Means
Module 10: Inference for Means
Introduction to Hypothesis Test for a Population Mean
Introduction to Hypothesis Test for a Population Mean
What you’ll learn to do: Conduct and interpret results from a hypothesis test about a population mean.
In this section we will learn to conduct a hypothesis test about a population mean and state a conclusion in context under appropriate conditions. Matched pairs design is when there is a “before and after” situation i.e. two quantitative measurements from a single sample of individuals. We will also learn, under appropriate conditions, to conduct a hypothesis test about a mean for a matched pairs design and state a conclusion in context. We will also interpret the P-value as a conditional probability.
CC licensed content, Shared previously
- Concepts in Statistics. Provided by: Open Learning Initiative. Located at: http://oli.cmu.edu. License: CC BY: Attribution