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.
Hypothesis Testing in Public Health
Hypothesis Testing in Public Health
This course is part of Biostatistics in Public Health Specialization
Instructor: John McGready, PhD, MS
Sponsored by Coursera Learning Team
19,035 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(623 reviews)
Beginner level
Recommended experience
Flexible schedule
Approx. 19 hours
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95%
Most learners liked this course
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
Details to know
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Assessments
11 assignments
Taught in English
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This course is part of the Biostatistics in Public Health Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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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.
What's included
6 videos1 reading2 assignments
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.
What's included
6 videos1 reading2 assignments
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.
What's included
8 videos1 reading2 assignments
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.
What's included
6 videos1 reading2 assignments
What's included
11 videos2 assignments
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.
What's included
1 reading1 assignment
Instructor
Instructor ratings
4.8 (172 ratings)Offered by
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Learner reviews
4.8
623 reviews
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AA
5
Reviewed on Jul 9, 2021
Excellent course, excellent teaching. Prof McGready knows his stuff and also knows how to teach it. The projects exercices are fun to work on and see how statistics is used in research.
BV
5
Reviewed on Mar 31, 2020
Very well-organized course. Easy to understand. I also enjoyed solving Formative and Summative Quizzes and enjoyed answering to Project Questions.
NZ
5
Reviewed on Apr 10, 2019
Excellent course, very well explained and the scientific articles used were a superb way to boost my confidence that I can do this, meaning stats. Thank you!
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