Hypothesis Testing in Public Health (Coursera)

Hypothesis Testing in Public Health (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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.
What 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

Course 2 of 4 in the Biostatistics in Public Health Specialization.

Syllabus

WEEK 1
Sampling Distributions and Standard Errors
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.

WEEK 2
Confidence Intervals for Single Population Parameters
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.
Confidence Intervals for Population Comparison Measures
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.

WEEK 3
Two-Group Hypothesis Testing: The General Concept and Comparing Means
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.

WEEK 4
Hypothesis Testing (Comparing Proportions and Incidence Rates Between Two Populations) & Extended Hypothesis Testing
Project
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.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

The People, Power, and Pride of Public Health (Coursera) Coursera
Johns Hopkins University

The People, Power, and Pride of Public Health (Coursera)

The People, Power, and Pride of Public Health provides an engaging overview of the incredible accomplishments and promise of the public health field. The first module includes interviews with legendary public health figures whose work led to millions of lives saved with vaccines, air bags and car seats, and the federal Women Infants and Children (WIC) nutrition program.

Oct 12th 2026
3 Weeks
COVID Vaccine Ambassador Training: How to Talk to Parents (Coursera) Coursera
Johns Hopkins University

COVID Vaccine Ambassador Training: How to Talk to Parents (Coursera)

Vaccination is a key strategy for preventing serious illness and death from COVID-19. COVID-19 vaccines are available for children 5 and older, but many parents have questions about vaccinations. This training course prepares parents of school-age children, PTAs, community members, and school staff to be Vaccine Ambassadors and promote vaccine acceptance in their communities. **Free enrollment available until December 31, 2022. Valid for one enrollment per person.**

Oct 19th 2026
1 Week
Stories of Infection (Coursera) Coursera
Stanford University

Stories of Infection (Coursera)

This course introduces learners to a variety of infectious diseases using a patient-centered, story-based approach. Through illustrated, short videos, learners will follow the course of each patient’s illness, from initial presentation to resolution. Integrating the relevant microbiology, pathophysiology and immunology, this course aims to engage and entice the learner towards future studies in microbiology, immunology and infectious diseases.

Oct 12th 2026
5-12 Weeks
A Crash Course in Causality: Inferring Causal Effects from Observational Data (Coursera) Coursera
University of Pennsylvania

A Crash Course in Causality: Inferring Causal Effects from Observational Data (Coursera)

We have all heard the phrase “correlation does not equal causation.” What, then, does equal causation? This course aims to answer that question and more! Over a period of 5 weeks, you will learn how causal effects are defined, what assumptions about your data and models are necessary, and how to implement and interpret some popular statistical methods. Learners will have the opportunity to apply these methods to example data in R (free statistical software environment).

Oct 12th 2026
5-12 Weeks
Chemicals and Health (Coursera) Coursera
Johns Hopkins University

Chemicals and Health (Coursera)

This course covers chemicals in our environment and in our bodies and how they impact our health. It addresses policies and practices related to chemicals, particularly related to how they get into our bodies (exposures), what they do when they get there (toxicology), how we measure them (biomonitoring) and their impact on our health. Most examples are drawn from the US.

Oct 12th 2026
5-12 Weeks
Principles of fMRI 1 (Coursera) Coursera
Johns Hopkins University

Principles of fMRI 1 (Coursera)

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s).

Oct 12th 2026
4 Weeks
Bayesian Statistics: Mixture Models (Coursera) Coursera
University of California, Santa Cruz

Bayesian Statistics: Mixture Models (Coursera)

Bayesian Statistics: Mixture Models introduces you to an important class of statistical models. The course is organized in five modules, each of which contains lecture videos, short quizzes, background reading, discussion prompts, and one or more peer-reviewed assignments. Statistics is best learned by doing it, not just watching a video, so the course is structured to help you learn through application.

Oct 19th 2026
5-12 Weeks
Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Oct 19th 2026
5-12 Weeks
Systems Science and Obesity (Coursera) Coursera
Johns Hopkins University

Systems Science and Obesity (Coursera)

Systems science has been instrumental in breaking new scientific ground in diverse fields such as meteorology, engineering and decision analysis. However, it is just beginning to impact public health. This seminar is designed to introduce students to basic tools of theory building and data analysis in systems science and to apply those tools to better understand the obesity epidemic in human populations.

Oct 19th 2026
4 Weeks