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Statistical Reasoning in Public Health provides a broad overview of bio statistical methods and concepts used in the public health sciences, emphasizing interpretation and concepts rather than calculations or mathematical details. It develops ability to read the scientific literature to critically evaluate study designs and methods of data analysis, it introduces basic concepts of statistical inference, including hypothesis testing, p-values, and confidence intervals.

Assessment

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

Certification

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Course Credit: JHSPH Open

Course Curriculum

Lecture 1 a Study Design 00:15:00
Lecture 1 b Study Design 00:10:00
Lecture 1 c Study Design 00:15:00
Lecture 1 d Study Design 00:15:00
Lecture 2 a Confounding and Effect Modification 00:15:00
Lecture 2 b Confounding and Effect Modification 00:20:00
Lecture 2 c Confounding and Effect Modification 00:15:00
Lecture 3 a Power and Sample Size Issues in Study Design 00:20:00
Lecture 3b Power and Sample Size Issues in Study Design 00:10:00
Lecture 3 c Power and Sample Size Issues in Study Design 00:15:00
Lecture 3 d Power and Sample Size Issues in Study Design 00:15:00
Lecture 3 e Power and Sample Size Issues in Study Design 00:10:00
Lecture 4 a Simple Linear Regression 00:15:00
Lecture 4 b Simple Linear Regression 00:15:00
Lecture 4 c Simple Linear Regression 00:15:00
Lecture 4 d Simple Linear Regression 00:20:00
Lecture 4 e Simple Linear Regression 00:15:00
Lecture 4 f Simple Linear Regression 00:10:00
Lecture 5 a Relating a Continuous Outcome to More than One Predictor Multiple Linear Regression 00:10:00
Lecture 5 b Relating a Continuous Outcome to More than One Predictor Multiple Linear Regression 00:10:00
Lecture 5 c Relating a Continuous Outcome to More than One Predictor Multiple Linear Regression 00:20:00
Lecture 5 d Relating a Continuous Outcome to More than One Predictor Multiple Linear Regression 00:25:00
Lecture 5 e Relating a Continuous Outcome to More than One Predictor Multiple Linear Regression 00:30:00
Lecture 6 a More Multiple Linear Regression 00:15:00
Lecture 6 b More Multiple Linear Regression 00:45:00
Lecture 7 a Logistic Regression 00:05:00
Lecture 7 b Logistic Regression 00:25:00
Lecture 7 c Logistic Regression 00:10:00
Lecture 7 d Logistic Regression 00:15:00
Lecture 7 e Logistic Regression 00:10:00
Lecture 8 a Multiple Logistic Regression 00:25:00
Lecture 8 b Multiple Logistic Regression 00:25:00
Lecture 8 c Multiple Logistic Regression 00:25:00
Lecture 9 a Tying It All Together Examples of Logistic Regression and Some Loose Ends 00:30:00
Lecture 9 b Tying It All Together Examples of Logistic Regression and Some Loose Ends 00:20:00
Lecture 9 c Tying It All Together Examples of Logistic Regression and Some Loose Ends 00:05:00
Lecture 10 a Regression for Survival Analysis 00:35:00
Lecture 10 b Regression for Survival Analysis 00:05:00
Lecture 11 Multivariate Survival Analysis 00:20:00
Assessment
Submit Your Assignment 00:00:00
Certification 00:00:00

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