Course Summary
Learn how to use statistical hypothesis testing to make informed public health decisions. This course covers the basics of hypothesis testing, including null and alternative hypotheses, p-values, and statistical power.Key Learning Points
- Understand the basics of statistical hypothesis testing
- Learn how to formulate null and alternative hypotheses
- Explore the concept of p-values and statistical power
- Apply hypothesis testing to real-world public health scenarios
Related Topics for further study
Learning Outcomes
- Understand the basics of hypothesis testing
- Apply hypothesis testing to real-world public health scenarios
- Evaluate the significance of results using p-values and statistical power
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of statistics
- Familiarity with public health concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Biostatistics in Public Health
- Epidemiology in Public Health Practice
Related Education Paths
Related Books
Description
Biostatistics is an essential skill for every public health researcher because it provides a set of precise methods for extracting meaningful conclusions from data. In this second course of the Biostatistics in Public Health Specialization, you'll learn to evaluate sample variability and apply statistical hypothesis testing methods. Along the way, you'll perform calculations and interpret real-world data from the published scientific literature. Topics include sample statistics, the central limit theorem, confidence intervals, hypothesis testing, and p values.
Knowledge
- Use statistical methods to analyze sampling distribution
- Estimate and interpret 95% confidence intervals for single samples
- Estimate and interpret 95% confidence intervals for two populations
- Estimate and interpret p values for hypothesis testing
Outline
- Sampling Distributions and Standard Errors
- Introduction
- Sampling Distribution Definition
- Examples: Sampling Distribution for a Single Mean
- Examples: Sampling Distribution for a Single Proportion, Incidence Rate
- Estimating Sampling Distribution Characteristics from Single Samples of Data
- Additional Examples
- Formative Quiz 1 Solutions
- Practice Quiz
- Sampling Distributions and Standard Errors
- Confidence Intervals for Single Population Parameters
- Introduction
- Confidence Intervals for Single Population Parameters
- Confidence Intervals for Population Proportions and Incidence Rates
- So What Is a Confidence Interval, and How Should It Be Interpreted?
- A Note on Confidence Intervals for Population Quantities Based on Small Samples
- Additional Examples
- Formative Quiz 2 Solutions
- Practice Quiz: Confidence Intervals for Single Population Parameters
- Quiz: Confidence Intervals for Single Population Parameters
- Confidence Intervals for Population Comparison Measures
- Introduction
- Confidence Intervals for Population Comparison Measures
- Confidence Intervals for Comparing Means of Continuous Outcomes Between Two Populations
- Confidence Intervals for Binary Comparisons: Part 1, Difference in Proportions
- Confidence Intervals for Binary Comparisons: Part 2, Ratio of Proportions and Odds Ratios
- Confidence Intervals for Incidence Rate Ratios
- A Brief Note About Ratios (Again)
- Additional Examples
- Solutions, Formative Assessment
- Practice Quiz: Confidence Intervals for Population Comparison Measures
- Confidence Intervals for Population Comparison Measures
- Two-Group Hypothesis Testing: The General Concept and Comparing Means
- Introduction
- Hypothesis Testing: The General Concept, and for Comparing Means Between Two Populations
- (Hypothesis Testing) Comparing Means Between Two Populations: The Paired Approach
- (Hypothesis Testing) Comparing Means Between Two Populations: The Unpaired Approach
- Debriefing on the p-Value, Part 1
- Additional Examples
- Solutions, Formative Asessment
- Two-Group Hypothesis Testing: The General Concept and Comparing Means, and Earlier Course Material
- Hypothesis Testing (Comparing Proportions and Incidence Rates Between Two Populations) & Extended Hypothesis Testing
- Introduction
- (Hypothesis Testing) Comparing Proportions Between Two Populations: The “z-Test” Approach
- (Hypothesis Testing) Comparing Proportions Between Two Populations: Chi-Square and Fisher’s Exact Test Approaches
- Hypothesis Tests for Comparing Incidence Rates Between Two Populations
- Debriefing on the p-Value and Hypothesis Testing, Part 2
- Additional Examples
- Introduction
- (Hypothesis Testing) Comparing Means Between More Than Two Populations: Analysis of Variance (ANOVA)
- (Hypothesis Testing) Comparing Proportions Between More Than Two Populations: Chi-Square Tests
- Hypothesis Testing) Comparing Survival Curves Between More Than Two Populations: Log-Rank Tests
- Several Issues to Consider
- Practice Quiz
- Hypothesis Testing (Comparing Proportions and Incidence Rates Between Two Populations) & Extended Hypothesis Testing
- Project
- Biostatistical Consulting Project
- Course Project Quiz
John McGready, PhD, MS
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