Hypothesis Testing in Public Health

Instructor: John McGready, PhD, MS

Beginner Level • Approx. 19 hours • Flexible Schedule

What You'll 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'll Gain

Medical Science and Research
Public Health
Sampling (Statistics)
Biostatistics
Statistical Hypothesis Testing
Quantitative Research
Statistical Analysis
Statistical Inference
Probability & Statistics
Scientific Methods

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 6 modules in this course

Within module one, you will learn about sample statistics, sampling distribution, and the central limit theorem. You will have the opportunity to test your knowledge with a practice quiz and, then, apply what you learned to the graded quiz.

Module two builds upon previous materials to discuss confidence intervals, the need for ample sizes of data, and ways to get around the need for ample sizes of data. The practice quiz helps you prepare for the graded quiz.

Within module three, confidence intervals are discussed at length and ratios are discussed again. Aside from the lectures, you will also be completing a practice quiz and graded quiz.

Within module four, you will look at statistical hypothesis tests, confidence intervals, and p-value. There is a practice quiz to prepare you for the graded quiz.

During this module, you get the chance to demonstrate what you've learned by putting yourself in the shoes of biostatistical consultant on two different studies, one about asthma medication and the other about self-administration of injectable contraception. The two research teams have asked you to help them interpret previously published results in order to inform the planning of their own studies. If you've already taken the Summarization and Measurement course, then this scenario will be familiar.