# STAT 486/586 Introduction to Statistical Computing

This website is designed to host course material for STAT 486/586 Introduction to Statistical Computing at Iowa State University.

## Relevant course pages

## Textbook

The required textbook for this course is

There is now second edition of this book

### Additional free textbooks

- R Programming for Data Science
- Hands on Programming with R
- OpenIntro Statistics - background material

## Software

We will be using the statistical software R. I will be using RStudio as the interface to R. Although both will be available on lab computers, I suggest you install R and RStudio on your own laptop or desktop.

Install links:

## Course Description

Modern statistical computing. Topics may include: data management; spread sheets; verifying data accuracy; transferring data between software packages; data and graphical analysis with statistical software packages; algorithmic programming concepts and applications; simulation studies and resampling methods; software reliability; statistical modeling and machine learning.

## Course Objectives

By the end of this course, students will be able to

- Wrangle data and construct visualizations to demonstrate scientific phenomenon.
- Implement a data management pipeline, including relevant feed back loops in order to obtain a reproducible workflow.
- Construct R functions and scripts to obtain a stated input-output goal.
- Produce a Monte Carlo simulation study to demonstrate a theoretical probability result.

## Prerequisite

The prerequisite for the course is previous enrollment in one of the following statistics (STAT) courses: 301, 326, 401, or 587.

## Schedule

## Week|Topic|Reading

1|Review|Open Intro (entire book) 2|Visualization|R4DS Ch1-3

## Q&A

Please use the Canvas discussion forum.

## Center for Excellence in Learning and Teaching Recommendations

This course abides by the Center for Excellence in Learning and Teaching Recommendations.