Statistical Analysis with R for Public Health Specialization

There are statistics everywhere. the likelihood that today will be rainy. trends in unemployment rates throughout time. the chances of India winning the upcoming cricket world championship. They began as a little bit of fun in sports like football but have developed into enormous business. Not least in the vast and essential field of public health, statistical analysis is crucial in medicine.

You will gain a better understanding of medical research in Statistical Analysis with R for Public Health Specialization as well as how and why a hypothesis is developed from a hazy idea. The fundamental statistical ideas of sampling, uncertainty, variation, missing values, and distributions will be covered. Then you'll get your hands dirty by using R, one of the most popular and adaptable free software programs available, to analyze data sets pertaining to some significant public health issues, such as fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalization.

Statistical Analysis with R for Public Health Specialization is a part of our future Global Master in Public Health degree, which is scheduled to begin in September 2019. This can be considered as one of the Best Online Public Health Courses. You will learn about important ideas and a data collection that will be used as a worked example throughout each lesson. Public health data are disorganized, with many instances of missing numbers and odd distributions. The information you'll utilize comes from actual patient-level data sets, either directly or indirectly (all anonymised and with usage permissions in place).

When you run into standard data and analytical challenges, the emphasis will be on "learning through doing" and "learning through discovering," which you can solve and discuss with your fellow students. Before getting access to the solutions and explanations offered by the teachers, you'll have the option to figure things out on your own and with your peers.

What you will learn

• To defend the crucial role of statistics in contemporary public health research and practice, one must be aware of the fundamental elements of statistical reasoning.
• As a first step in more complex analysis using the R software, describe a given data set from scratch using descriptive statistics and graphical techniques.
• Utilize the right techniques to create and analyze statistical correlations between variables in a data collection in R.
• Analyze the outcomes of your analysis and evaluate how chance and bias contributed to your findings.

Skill you will gain

• Statistical Thinking
• Survival Analysis
• Logistic Regression
• Data analysis with R
• Linear Regression
• Run basic analyses in R
• R Programming
• Understand common data distributions and types of variables
• Formulate a scientific hypothesis
• Correlation And Dependence

Instructors: Alex Bottle and Victoria Cornelius

Offered by: Imperial College London

Coursera rating: 4.7/5.0, 1.470 ratings

Enroll here: https://www.coursera.org/specializations/statistical-analysis-r-public-health#instructors