Lab Slides for STATS 250 at the University of Michigan

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Slides for STATS 250 Labs 106, 108, and 115 in Fall 2020

View the Project on GitHub nseewald1/250fa20-slides

Slides for Nick’s STATS 250 Labs - Fall 2020

PDF versions of the slides are available on our Lab Resources page on Canvas.

All materials © 2020 Nicholas J. Seewald

Introduction Video

Welcome to STATS 250 Lab! Please watch this video for details on lab policy and logistics.

Jump to a specific lab by clicking the appropriate link:
[Lab 1: Getting Started with R] [Lab 2: Basics of Data with R] [Lab 4: Probability and Scatterplots]


Lab 1: Getting Started with R

Lab materials for the week of August 31, 2020

Statistical Learning Goals

  1. Learn how to visualize categorical data in a bar chart
  2. Learn how to summarize quantitative and categorical data

R Learning Goals

  1. Learn the difference between R, RStudio, and R Markdown
  2. Become familiar with the RStudio interface
  3. Understand key components of an R Markdown document
  4. Become familiar with R functions and arguments

Slides


Lab 2: Basics of Data with R

Lab materials for the week running Friday 9/4 - Friday 9/11. All labs are asynchronous due to Labor Day.

Statistical Learning Objectives

  1. Understand the structure of data (observations and variables)
  2. Think about the scope of a data set: what questions can and cannot be answered with a particular data set?

R Learning Objectives

  1. Learn how to “assign” information to “objects” in R
  2. See how R “reads in” a data set from a file
  3. Be able to identify the names of variables contained in a data set
  4. Make a frequency table for one or two variables

Slides


Lab 3: No materials available due to GEO strike


Lab 4: Probability and Scatterplots

Lab materials for the week running Friday 9/18 - Friday 9/25.

Statistical Learning Objectives

  1. Sampling with replacement versus sampling without replacement
  2. The Law of Large Numbers and expected values
  3. Scatterplots with linear associations
  4. The correlation coefficient

R Learning Objectives

  1. Creating a sequence of integers between two values.
  2. Learning how to randomly sample from a set, with replacement or without replacement.
  3. Creating a plot of (x,y) quantitative values.
  4. Finding the correlation coefficient between two quantitative variables.

Slides