# Assignments

• Mini-Homework

## Mini-homework 1 – Can Twitter predict election results?

A mini-homework about a data science study that used Twitter data to predict election outcomes.

• Module Exercise

## Module 1 exercises

For this module exercise, you will answer a series of questions that check your understanding of the material covered in the Module 1 lecture videos.

Introductory Statistics with Randomization and Simulation

Chapter 1: Introduction to data

• From the beginning up to the end of section 1.5, skipping section 1.4.2.
• Mini-Homework

## Mini-homework 2a – R Markdown practice

A mini-homework on editing R Markdown files and saving to GitHub.

Introduction to computational and data sciences supplemental book

Book URL: http://book.cds101.com

Chapter 2: GitHub

R for Data Science

Chapter 27: R Markdown

R Markdown: The Definitive Guide

Chapter 2: Basics

Introduction to Data Science: Data Analysis and Prediction Algorithms with R

Selections from chapters 2, 39, and 40

• Mini-Homework

## Mini-homework 2b – Visualization practice

A mini-homework to practice using RStudio to run code blocks in RMarkdown files and to create visualizations using ggplot2.

• Homework

## Homework 1

Your first major assignment is a set of exercises based around a single dataset called rail_trail, which will provide you with practice in creating visualizations using R and ggplot2.

• Mini-Homework

## Mini-homework 3 – Visualization by example

A mini-homework for practicing how to make plots using the ggplot2 library.

R for Data Science

Chapter 3: Data visualisation

Introductory Statistics with Randomization and Simulation

Chapter 1: Introduction to data

• Section 1.6 – Examining numerical data, skip subsection 1.6.8

• Section 1.7 – Considering categorical data

Introduction to computational and data sciences supplemental book

Book URL: http://book.cds101.com

Chapter 3: Describing numerical data

• Homework

## Homework 2

For your second major assignment, you will explore a dataset about the passengers on the Titanic, the British passenger liner that crashed into an iceberg during its maiden voyage and sank early in the morning on April 16, 1912.

• Mini-Homework

## Mini-homework 4 – Flights of New York

A mini-homework for practicing how to manipulate datasets using the dplyr library.

• Module Exercise

## Module 4 exercises

For this module exercise, you will follow along with the examples from the Module 4 lecture videos in an R Markdown file.

R for Data Science

Chapter 4: Workflow: basics

Chapter 5: Data transformation

• Mini-Homework

## Mini-homework 5 – Tidy Gradebook

A mini-homework for practicing how to reshape datasets using the tidyr library.

R for Data Science

Chapter 12: Tidy data

• Module Exercise

## Module 5 exercises

For this module exercise, you will answer a series of questions that check your understanding of the material covered in the Module 5 lectures.

• Mini-Homework

## Mini-homework 6 – Analyzing data distributions

A mini-homework for practicing how to analyze data distributions using basic statistical functions in R, ggplot2, and dplyr.

Introduction to computational and data sciences supplemental book

Book URL: http://book.cds101.com

Chapter 4: Representing distributions

• Module Exercise

## Module 6 exercises

For this module exercise, you will answer a series of questions that check your understanding of the material covered in the Module 6 lectures.

• Homework

## Homework 3

For your third major homework assignment, you will use statistical inference to answer a question about the National Survey of Family Growth, Cycle 6 dataset published by the National Center for Health Statistics.

• Mini-Homework

## Mini-homework 7 – Who busts the Mythbusters?

A mini-homework for practicing how to conduct hypothesis tests and calculate confidence intervals using the infer package.

Introductory Statistics with Randomization and Simulation

Chapter 2: Foundation for inference

• From the beginning up to the end of section 2.5

Chapter 4: Inference for numerical data

• Section 4.5, skipping subsection 4.5.3

Introduction to computational and data sciences supplemental book

Book URL: http://book.cds101.com

Chapter 5: Statistical inference with infer

• Homework

## Homework 4

For your fourth major homework assignment, you will build a regression model that predicts the market value of condominiums in New York City using a dataset published by the New York City Department of Finance.

• Mini-Homework

## Mini-homework 8 – Under (blood) pressure

A mini-homework for practicing how to build and analyze linear regression models.

R for Data Science

Chapter 23: Model basics

Introductory Statistics with Randomization and Simulation

Chapter 5: Introduction to linear regression

• Introduction

• Section 5.1

• Section 5.4, read subsection 5.4.1 only

• Project

## Final Project

For the final project, you will be assigned into a team to conduct an exploratory data analysis of the U.S. Department of Education’s College Scorecard dataset.