- Logistic Regression
- Linear Regression
- Statistical Thinking
- Survival Analysis
- Data analysis with R
Statistical Analysis with R for Public Health
Completed by Roxana Popa
December 28, 2020
Approximately 1 months at 10 hours a week to completeRoxana Popa's account is verified. Coursera certifies their successful completion of Imperial College London Statistical Analysis with R for Public Health Specialization.
Course Certificates Completed
Introduction to Statistics & Data Analysis in Public Health
Linear Regression in R for Public Health
Logistic Regression in R for Public Health
Survival Analysis in R for Public Health
What you will learn
Recognise the key components of statistical thinking in order to defend the critical role of statistics in modern public health research and practice
Describe a given data set from scratch using descriptive statistics and graphical methods as a first step for more advanced analysis using R software
Apply appropriate methods in order to formulate and examine statistical associations between variables within a data set in R
Interpret the output from your analysis and appraise the role of chance and bias as explanations for your results
Skills you will gain
Course Certificates
Earned after completing each course in the Specialization
Introduction to Statistics & Data Analysis in Public Health
Imperial College London
Taught by: Alex Bottle
Completed by: Roxana Popa by November 22, 2020
2-5 hours/week
Linear Regression in R for Public Health
Imperial College London
Taught by: Alex Bottle & Victoria Cornelius
Completed by: Roxana Popa by December 6, 2020
4 weeks of study 3-5 hours per week
Logistic Regression in R for Public Health
Imperial College London
Taught by: Alex Bottle
Completed by: Roxana Popa by December 19, 2020
3-5 hours/week
Survival Analysis in R for Public Health
Imperial College London
Taught by: Alex Bottle
Completed by: Roxana Popa by December 28, 2020
3-5 hours/week