\(~\)

Last updated: Wed Dec 10 2025, 08:30

Final Project

Final Project Instructions

Due Date
Wednesday December 17

Midterm

Midterm Instructions

Helpful Hints on Getting Data Ready

Step Due Date
Data Selection/Project Proposal October 10
Data Reading/Check In October 31
Presentations November 14

Exam

Your final will be roughly as long as a normal exam but I will give you 2 hours to do the exam (not the full 3 hours the final’s schedule gives me). You may bring a notecard and a calculator. If you do not have a calculator you may leave your answer unsimplified. Eg predicted price = $ e^2.19.

Study Guide Date
Exam 1 Study Guide Wednesday October 15th
Exam 2 Study Guide Monday Dec 1st
Final Exam Study Guide Wednesday Dec 17th @ 9am

Homework

All homework is due at 9pm unless clearly specified otherwise.

Rmd Due Date Helpful Things
Homework 1 October 1st Examples of the graphs you’ll be remaking
Homework 2 (Probability) Nov 12
Homework 3 (Regression Testing lab) Dec 12


Required Readings

Title Author Journal Year Quiz
Tidy Data Hadley Wickham Journal of Statistical Software 2014 9/15
Principles of Effective Data Visualization Stephen R. Midway Patterns 2020 10/6
Somewhere Over the Rainbow: An Empirical Assessment of Quantitative Colormaps Yang Liu & Jeffrey Heer Conference on Human Factors in Computing Systems Proceedings 2018 11/7

Please note that you are fully allowed (encouraged even!) to visit during office hours to talk about the required reading if you’d like. I’m glad to chat about it and discuss any questions you might have. Also please note that I’d like you to understand the broad strokes of the paper/what the author is getting at. I will avoid quizzing you over the nitty-gritty details.


Notes

Week 1 (Introduction)

Date Lecture Lab Suggested Reading
Friday 8/28 Syllabus - -
Introduction - IMS Sections 1.2.1-1.2.3

Assignments and Deadlines

  1. Install R (https://cran.r-project.org/)

  2. Install RStudio (https://posit.co/download/rstudio-desktop/)

  3. Begin thinking of interesting data sources for you midterm projects


Week 2 (R)

Date Lecture Lab Suggested Reading
Wednesday 9/3 Intro to R lab 1 -
- - lab 1 Helpful Hints -
Friday 9/5 Visualizations in R Continue lab 1 -

Assignments and Deadlines

  1. First lab is due Septmber 9th
  2. Hadley Wickham’s Tidy Data published in Journal of Statistical Software in 2014 with a quiz on September 15th


Week 3 (Data Visualization)

Date Lecture Lab Suggested Reading
Monday 9/8 Finish Data Visualization -
Wednesday 9/10 Data Visualization Part II lab 2 (to be posted later) -
Friday 9/12 Data Visualization Part III Accessibility data vis lab-

Assignments and Deadlines

  1. First lab is due Septmber 9th
  2. Hadley Wickham’s Tidy Data published in Journal of Statistical Software in 2014 with a quiz on September 15th


Week 4 (ggplot2 and Numeric Summaries)

Date Lecture Lab Suggested Reading
Monday 9/15 ggplot2 finish lab 2, ggplot 2 lab -
Wednesday 9/17 finish ggplot 2 lab -
ggplot2 lab helpful hints
Friday 9/19 Numeric Summaries If time work on ggplot2 lab -

Assignments and Deadlines

  1. Second lab is due September 15th
  2. ggplot2 lab is due September 24th


Week 5 (Numeric Summaries + Correlations)

Date Lecture Lab Suggested Reading
Monday 9/22 Numeric Summaries Cont. NumericCode Along
Wednesday 9/24 Correlations Numeric Code along finished
Friday 9/26 Finish Correlations Correlation Code along
Correlation Code along finished

Assignments and Deadlines

  1. ggplot2 lab is due September 24nd
  2. Homework 1 is due October 1st
  3. Second required reading quize is October 6th


Week 6 (Linear Regression)

Date Lecture Lab Suggested Reading
Monday 9/28 Simple Linear Regression (SLR)
Wednesday 10/01 Simple Linear Regression Cont.
Friday 10/03 Cor., SLR, and R\(^2\) Lab

Assignments and Deadlines

  1. Homework 1 is due October 1st
  2. Second required reading quiz is October 6th


Week 7 (Linear Regression Continued)

Date Lecture Lab Suggested Reading
Monday 10/6 Regression: Transformations Slide 29 corrected
Wednesday 10/8 Trans. continued, indicators possible code along (not done)
Wednesday 10/8 Indicators Alternative Slide Deck Same material, presented differently
Friday 10/10 Transform and Indicator (Non-graded) Lab Solutions to Transform and Indicator lab

Assignments and Deadlines

  1. Regression Lab is due October 10th
  2. Midterm project proposals due October 10th
  3. Exam is October 15th


Week 8 (Exam)

Date Lecture Lab Suggested Reading
Monday 10/13 review day
Wednesday 10/15 exam day
Friday 10/17 multiple regression lab

Assignments and Deadlines

  1. Multiple regression lab is due Wednesday, October 29th


Week 9 (Probability and Permutation Tests)

Date Lecture Lab Suggested Reading
Monday 10/27 Probability
Wednesday 10/29 Permutation Tests How to Write a CSV
Halloween Permutation Tests Updated

Assignments and Deadlines

  1. Multiple regression lab is due Wednesday, October 29th



Week 10 (Normality)

Date Lecture Lab Suggested Reading
Nov 3 Normal Distribution Probability Distribution Lab
Nov 5 Continue Normal
Nov 7 Sampling Distributions

Assignments and Deadlines

  1. Dice lab due Nov 12th

  2. Homework 2 due Nov 12th



Week 11 (Testing)

Date Lecture Lab Suggested Reading
Nov 11 Z-test
Nov 14 Confidence Intervals Z-test Lab
Nov 16 Presentations



Week 12 (Intervals and Sampling)

Date Lecture Lab Suggested Reading
Nov 17 Confidence Intervals Slide 37 Answers are in CI Simulatior Solutons Rmd file Confidence Interval Simulator
Nov 17 Sampling Methods Confidence Interval Simulator Solutions
Nov 19 t-tests and confidence intervals
Nov 21 More Inferences practice practice solutions



Week 13 (THANKSGIVING!!)

Date Lecture Lab Suggested Reading
Nov 24 More Inferences Final Hypothesis Statement Practice Solutions
Nov 26 Adv Regression



Week 14 (Almost Done!!)

Date Lecture Lab Suggested Reading
Dec 1 SNOW DAY!!
Dec 3 Exam Day
Dec 5 Regression Testing Regression Testing



Week 15 (Almost Done!!)

Date Lecture Lab Suggested Reading
Dec 8 Multiple Linear Regression
Dec 10 ANOVA
Dec 10 Regression Errors



Syllabus

Welcome to the course website for SST 115, Introduction to Statistics. To begin, you can find the course syllabus linked below:

You can locate course content by scrolling, or by using the outline in the upper left. Please note: material will not be posted until we’ve reached that point in the course.

Coding

My goal is to include the R code that I use to make different graphs, expamples, etc…, for the course. Most of it will be more advanced than what I will teach you or that you need but I want you to have access to examples if you’d like.

Please go here.