Week 1: R Introduction and Statistical Principles

Weekly Objectives

• Understand basic probability concepts such as random variables and distribution functions
• Understand the fundamental mechanism of statistical hypothesis tests
• Be able to define or identify null and alternative hypotheses, type I and type II errors
• Be able to interpret p-value and statistical power
• Understand the limitations of statistics
• Install R, R Studio and R packages and be familiar with their basics
• Perform statistical calculations in R
• Understand the goal of the final project
• Get familiar with NHANES data and know how to process the data in R

Lecture Note and R Examples

• Lecture Notes
  • [Intro to Statistics]
  • Follow this guide to install R and RStudio before class
• Download [this .rmd file] for in-class practice
• Download the birthrate data(.csv data file) and save it into the same folder as your .rmd file

NHANCE Data Example

You need to use some public available dataset to support the final project analysis. NHANCE data is a rich nation-wide questionnaire data provided by the CDC. If you choose to use the NHANCE data, some data processing need to be done. Here is a toy example for downloading and processing the 2015-2016 data. For your own analysis, you may want to consider the more recent NHANES 2017-March 2020 Pre-pandemic Version. Additional source and data files to run this example file:

• Toy example
• .Rmd [Source File]
• Data Files (from NHANES 2015-2016)
  • Demographic data: DEMO_I.XPT
  • Diabetes data: DIQ_I.XPT
  • Examination data: BMX_I.XPT

Further Reading

• Sections 11.1, 11.3.3 and 11.3.4 of the BPS textbook