ST 597: Introduction to Data Analytics with R

Spring 2017

Project

Homework Details

All homework assignments are in DataCamp in our class group. You will be sent an email invitation to join the group. This system will record your homework progress so there is nothing to turn in.

Unless otherwise stated, homework assignments are due at 11am on the due date. Late homework will only be accepted in extreme situations.

Homework #1: Due Wed Jan 18

Working with RStudio IDE (Part 1): Orientation

Homework #2: Due Mon Jan 23

Introduction to R

Homework #3: Due Mon Jan 30

Data Visualization with ggplot2 (Part 1)

Homework #4: Due Mon Feb 6

Data Manipulation in R with dplyr

Homework #5: Due Mon Feb 13

Data Visualization with ggplot2 (Part 2)

Homework #6: Due Mon Feb 20

Working with RStudio IDE (Part 1): Programming

Working with RStudio IDE (Part 1): Projects

Intermediate R: Conditionals and Control Flow

Intermediate R - Practice: Conditionals and Control Flow

Homework #7: Due Mon Feb 27

Intermediate R: Loops

Intermediate R - Practice: Loops

Intermediate R: Functions

Intermediate R - Practice: Functions

Homework #8: Due Mon Mar 6

Joining Data in R with dplyr

Homework #9: Due Mon Mar 27

Importing Data in R (Part 1): Importing data from flat files with utils

Importing Data in R (Part 1): readr and data.table

Importing Data in R (Part 1): Importing Excel data

Homework #10: Due Mon Apr 3

Cleaning Data in R: Introduction and exploring raw data

Cleaning Data in R: Tidying data

Working with Geospatial Data in R: Basic mapping with ggplot2 and ggmap

Homework #11: Due Mon Apr 10

Cleaning Data in R: Preparing data for analysis

Cleaning Data in R: Putting it all together

Importing & Cleaning Data in R: Case Studies

Homework #12: Due Mon Apr 17

Exploratory Data Analysis in R: Case Study

Homework #13: Due Mon Apr 24

Text Mining: Bag of Words

Extra course (in case you are interested)

Exploring Pitch Data with R