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.
This course is part of the Biostatistics in Public Health Specialization
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About this Course
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
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Try Coursera for BusinessWhat you will learn
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
Skills you will gain
- Confidence Interval
- Statistical Hypothesis Testing
- p values
- sampling
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Sampling Distributions and Standard Errors
Confidence Intervals for Single Population Parameters
Confidence Intervals for Population Comparison Measures
Two-Group Hypothesis Testing: The General Concept and Comparing Means
Hypothesis Testing (Comparing Proportions and Incidence Rates Between Two Populations) & Extended Hypothesis Testing
Project
Reviews
- 5 stars84.83%
- 4 stars13.22%
- 3 stars1.23%
- 2 stars0.35%
- 1 star0.35%
TOP REVIEWS FROM HYPOTHESIS TESTING IN PUBLIC HEALTH
Beautiful and highly educative course with very applicable steps. However, the correction to all tests done will go a long way to help better understanding. Thanks
Great overview of basic hypothesis testing for means, proportions, and survival curves. Only additional thing that would be nice was a deeper review of the code involved in R.
I was able to review all of the concepts I learned previously in biostatistics. This is an excellent refresher course. Professor McGready is quite articulate and knowledgeable.
excellant descriptions, good examples and challenging practice sessions. Better if some more were added about ANOVA also. If it is considered as advanced , then it is ok. Good experience
About the Biostatistics in Public Health Specialization

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