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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