Click on the text like “Week 1: Sept 4 – 8” to expand or collapse the items we covered in that week.

I will fill in more detail and provide links to lecture notes and labs as we go along. Items for future dates are tentative and subject to change.

Chapter 1: Observational Units, Categorical and Quantitative Variables

Wed, Sept 6

  • In class, we will work on:
    • Introductory lab: friend or foe? pdf
  • After class, please do the following:

Fri, Sept 8

  • Before class, please do the following:
    • Reading: Read Chapter 1 of Stats: Data and Models 4th edition, or Chapter 2 of the 3rd edition
    • Homework 1: Complete 4 DataCamp chapters on Introduction to R – you will get an email by the end of the day on Sept 6 inviting you to join our class organization with an assignment pointing you to the specific chapters to do. You should feel free to work on this in groups – but if you do, please email me to let me know who you worked with! Your grade on this assignment is only for completion, not correctness.
  • In class, we will work on the following:

Chapters 2 – 4: More on categorical and continuous data, data visualization, comparing distributions

Mon, Sept 11

  • Before class, please do the following:
    • Reading: Read Chapter 2 of Stats: Data and Models 4th edition, or Chapter 3 of the 3rd edition
    • Homework 1: Deadline extended to Monday
  • In class, we will do the following:
    • Discussion of material from Chapter 2 and Simpson’s paradox. slides Rmd
    • Continue work on the Intro to R lab from last week Friday.
  • After Class, please:
    • Fill out this form – this should take less than 5 minutes.

Wed, Sept 13

  • Before class, please do the following:
    • Reading: Read Chapters 3 and 4 of Stats: Data and Models 4th Edition, or Chapters 4 and 5 of the 3rd edition. Skip the sections about stem-and-leaf displays and dot plots. Look carefully at the stuff that is summarized in the Learning Objectives section on page 69 of the 4th edition or page 67 of the 3rd edition about the shape of a distribution, the summaries of the center of a distribution, summaries of the spread of a distribution, and when to use those different summaries.
  • In class, we will do the following:
    • Quiz on the material from Chapter 3 of the 4th edition, Chapter 4 of the 3rd edition. I will ask you two short questions involving the intuitive meaning of the sample mean, median, Q1, Q3, IQR, and standard deviation, and the circumstances when it is appropriate to use each of those numbers to describe a distribution. The formulas are not important for today. It may be helpful to look at (i.e., memorize) the definitions of these terms on pages 69-70 of the 4th edition, pages 67-68 of the 3rd edition.
    • Answer your questions: slides Rmd
    • Go over plotting with ggplot2: slides Rmd
    • Start a lab about making plots with ggplot2 and calculating statistics using dplyr: html Rmd. Solutions: html Rmd

Fri, Sept 15

  • Before class, please do the following:
    • Reading No additional reading for today.
    • Homework 2: I recommend that you should have finished at least the first 4 problems of Homework 2 by today.
  • In class, we will:
    • Continue working on the lab about making plots with ggplot2 and calculating statistics using dplyr
    • Go over data manipulation with dplyr: slides Rmd

Chapter 5: The normal model

Mon, Sept 18

  • Before class, please do the following:
    • Homework 2 continue working on homework 2 and old labs – post questions on Piazza
    • Reading: No additional reading
  • In class, we will:
    • Finish slides about data manipulation with dplyr (posted for Fri, Sept 15)
    • Continue working on homework 2 and the lab about making plots with ggplot2 and calculating statistics using dplyr.

Wed, Sept 20

  • Before class, please do the following:
    • Reading: Read Chapter 5 of Stats: Data and Models 4th edition, or Chapter 6 of the 3rd edition
  • In class, we will do the following:
    • Discuss the material in Chapter 5: the normal model and z-scores. slides Rmd
    • Here’s a worksheet with more examples that you can use to practice this material: pdf Solutions: pdf

Fri, Sept 22

  • Before class, please do the following:
    • Homework 2 is due today at the start of class!
    • Reading: Read Chapter 6 of Stats: Data and Models 4th edition, or Chapter 7 of the 3rd edition
  • In class, we will do the following:
    • Answer all questions about R; review for R quiz
    • If we have time, start discussing the material in Chapter 6: scatter plots and correlation. slides Rmd

Chapters 7 – 9: Linear Regression

Mon, Sept 25

  • Before class, please do the following:
    • Study for R Quiz
    • Homework 3: You know enough to do the entire assignment by Monday; you should at least do the first 3 problems.
  • In class, we will do the following:
    • Quiz on R: variables, data types, data frames, plotting with ggplot2, and calculating statistics with dplyr. I will give you a sample quiz and review this material on Fri, Sept 22.
    • Lab about scatter plots and correlation: html Rmd Solutions: html Rmd

Wed, Sept 27

  • Before class, please do the following:
    • Reading: Chapters 7 and 8 of Stats: Data and Models 4th edition, or Chapters 8 and 9 of the 3rd edition
  • In class, we will do the following:

Fri, Sept 29

  • Before class, please do the following:
    • Homework 3 is due today at the start of class!
    • Reading: Chapter 9 of Stats: Data and Models 4th edition, or Chapter 10 of the 3rd edition
  • In class, we will do the following:
    • Discuss some more material in Chapter 7 – residual standard deviation and \(R^2\): slides Rmd
    • Mini-Lab about residual standard deviation and \(R^2\): html Rmd Solutions: html Rmd

Chapters 9 and 11: Finishing Regression, starting on Design

Mon, Oct 2

  • Before class, please do the following:
    • Reading: Chapter 9 of Stats: Data and Models 4th edition, or Chapter 10 of the 3rd edition
  • In class, we will do the following:
    • Section 1: We will talk more about residual standard deviation and \(R^2\).
    • Finish off the “not-so-mini-lab” about residual standard deviation and \(R^2\) that we started on Friday.
    • Wrap-Up for Not-So-Mini-Lab: slides Rmd
    • Briefly discuss material from Chapter 9 of SDM4/Chapter 10 of SDM3: slides Rmd

Wed, Oct 4

  • Before class, please do the following:
    • Reading: Chapter 11 of Stats: Data and Models 4th edition, or Chapter 12 of the 3rd edition
  • In class, we will do the following:
    • Briefly discuss sampling (material from Chapter 11 of SDM4/Chapter 12 of SDM3): slides Rmd
    • Lab about sampling: html Rmd Solutions: html Rmd

Fri, Oct 6

  • Before class, please do the following:
    • Homework 4 is due today at the start of class!
    • Reading: Chapter 12 of Stats: Data and Models 4th edition, or Chapter 13 of the 3rd edition
  • In class, we will do the following:
    • Finish off the lab about sampling from Wednesday
    • Discuss material from Chapter 12 of Stats: Data and Models 4th edition, or Chapter 13 of the 3rd edition: slides Rmd
    • If time: Think about how this material relates to two recently published studies: worksheet: pdf Rmd
      • Study 1: Meditation or Exercise for Preventing Acute Respiratory Infection: A Randomized Controlled Trial pdf
      • Study 2: Association of Coffee Drinking with Total and Cause-Specific Mortality pdf

Chapter 12: Design

Mon, Oct 9

  • No Class (mid-semester break)

Wed, Oct 11

  • Before class, please do the following:
    • Reading: Chapter 13 of Stats: Data and Models 4th edition, or Chapter 14 of the 3rd edition (I didn’t tell you to do this until class, but please go back and read this material.)
  • In class, we will do the following:
    • Section 2: Discuss material from Chapter 12; slides posted Fri, Oct 6.
    • Lab introducing hypothesis testing and probability: html Rmd
    • Probability Rules: pdf
    • Probability Examples: pdf Solutions: pdf

Fri, Oct 13

  • Before class, please do the following:
    • Reading: Chapter 14 of Stats: Data and Models 4th edition, or Chapter 15 of the 3rd edition
  • In class, we will do the following:
    • Finish off examples from Wed, Oct 11

Midterm 1 and Chapters 13 and 14: Probability and Random Variables

Sun, Oct 15

  • Review Session for Midterm 1: 7-9 PM in Cleaveland L-1. I will not come with anything prepared, but I will answer any and all questions.

Mon, Oct 16

  • Midterm 1: Chapters 1 – 8 (topics from Homework 1 – 4 and lectures up through Friday, Sept 29).

Wed, Oct 18

  • Before class, please do the following:
    • Reading: Chapter 14 of Stats: Data and Models 4th edition, or Chapter 15 of the 3rd edition
  • In class, we will do the following:
    • Discuss material from Chapters 13 and 14 – no slides
    • If time, start some more examples (probably won’t have time to finish these today): pdf Solutions: pdf

Fri, Oct 20

  • Before class, please do the following:
    • Homework 5: You should be able to do at least the first 3 problems on homework 5 by today.
  • In class, we will do the following:
    • Class meets in Dwight 101
    • No new material covered
    • Time to work on probability examples posted Wed, Oct 11 and Wed, Oct 18, and homework assignments

Chapters 15 – 17: Models for sampling distributions

Mon, Oct 23

  • Before class, please do the following:
    • Reading: Chapters 15 and 16 of Stats: Data and Models 4th edition, or Chapters 16 and 17 of the 3rd edition. For the chapter about Probability Models, focus on the sections about Bernoulli Trials, the Geometric Model, Independence, The Binomial Model, and Approximating the Binomial with a Normal. Skim the sections about the Poisson Model and Other Continuous Random Variables in the 4th edition, Exponential Model in the 3rd edition; we will not use that material in this class, but it’s good to know that it’s out there.
  • In class, we will do the following:
    • Section 2 Only: Discuss Bayes’ Rule
    • Discuss random variables and probability models: slides Rmd
    • Work through this example of a problem with the Binomial distribution as a class: pdf Solutions: pdf
    • If time, work on these examples of problems with the Binomial distribution in small groups: pdf Solutions: pdf

Wed, Oct 25

  • Before class, please do the following:
    • Reading: Chapter 17 of Stats: Data and Models 4th edition, or Chapter 18 of the 3rd edition.
  • In class, we will do the following:

Fri, Oct 27

  • Before class, please do the following:
    • Homework 5 is due today!
    • Reading: Chapter 17 of Stats: Data and Models 4th edition, or Chapter 18 of the 3rd edition.
  • In class, we will do the following:
    • Discuss Chapter 17: Sampling Distributions: slides Rmd
    • Start a Lab about Sampling Distributions: html Rmd Solutions: html Rmd

Chapters 17 – 18: Inference for proportions

Mon, Oct 30

  • Before class, please do the following:
    • Reading: No new reading
  • In class, we will do the following:
    • In class quiz on probability. This quiz will focus on the definitions of disjoint events and independent events – both in terms of their intuitive meaning and the formal definitions (that is, how to check whether or not two events are disjoint or independent). The quiz will not include any questions about Bayes’ Rule. You may use a 1 page notes sheet (start making your notes for the next midterm!)
    • Continue lab from Friday
    • Talk about sampling distributions for sample mean and sample proportion: Updated slides Rmd

Wed, Nov 1

  • Before class, please do the following:
    • Reading: Chapter 18 of Stats: Data and Models 4th edition, or Chapter 19 of the 3rd edition.
  • In class, we will do the following:
    • Start on Chapter 18: Confidence Intervals for proportions. slides pdf Rmd
    • Start a lab about confidence intervals for proportions. html Rmd Solutions: html Rmd

Fri, Nov 3

  • Before class, please do the following:
    • Homework 6 is due today!
    • Reading: No new reading
  • In class, we will do the following:
    • Continue with Chapter 18: Confidence Intervals for proportions

Chapters 18, 19, 20: Hypothesis tests for proportions, inference for means

Mon, Nov 6

  • Before class, please do the following:
    • Reading: No new reading
  • In class, we will do the following:
    • Continue with Chapter 18: Confidence Intervals for proportions
    • No quiz
    • Example exercise about computing confidence intervals for proportions manually. pdf Rmd Solutions: pdf

Wed, Nov 8

  • Before class, please do the following:
    • Reading: Chapter 19 of Stats: Data and Models 4th edition, or Chapter 20 of the 3rd edition.
    • Lab: Please turn in the lab about confidence intervals that we started on Wed, Nov 1 by 5pm today.
  • In class, we will do the following:

Fri, Nov 10

  • Before class, please do the following:
    • Reading: Chapter 20 of SDM4, or Chapter 23 of SDM3
  • In class, we will do the following:

Chapters 20 and 21: More about Inference; Midterm 2 around here

Mon, Nov 13

  • Before class, please do the following:
    • Reading: No new reading
  • In class, we will do the following:
  • After class
    • Review Session for midterm 2, 6 - 8 pm in Clapp 306. I will not prepare anything, so bring your questions!

Wed, Nov 15

  • In class, we will do the following:
    • Midterm 2! See exams page for details.

Fri, Nov 17

  • Before class, please do the following:
    • Reading: No new reading
  • In class, we will do the following:
    • Discuss the highlights of the lab about confidence intervals for proportions (solutions posted for Nov 1)
    • Talk about the differences between 4 things for a quantitative variable (Slides: pdf html Rmd )
      1. distribution of values in the population;
      2. distribution of values in a sample from the population;
      3. sampling distribution for the sample mean;
      4. a confidence interval for the population mean
    • A little time to work on old labs (all solutions are posted) and/or homework?

No Class Wed, Nov 22 or Fri, Nov 24 (Thanksgiving) – safe travels!

Chapter 22 (first half): Differences in Proportions

Mon, Nov 20

  • Before class, please do the following:
    • Reading: Chapter 22 (in both SDM4 and SDM3)
  • In class, we will do the following:
    • Hypothesis Tests for a Difference in Proportions (SDM4 Chapter 22). Slides: pdf html Rmd
    • Lab/Example: html Rmd Solutions: html Rmd

Tues, Nov 21

  • Homework 7 is due by 5pm today!

Chapters 22, 23, and 25:Comparing groups and paired samples; start on inference for regression

Mon, Nov 27

  • Before class, please do the following:
    • Reading: Chapters 22 and 23 in SDM4, Chapters 24 and 25 in SDM3
  • In class, we will do the following:

Wed, Nov 29

  • Before class, please do the following:
    • Reading: Chapter 25 in SDM4, Chapter 27 in SDM3
  • In class, we will do the following:
    • Start talking about inference for simple linear regression. Lecture Example: pdf Solutions: pdf
    • A few other notes from the lecture: pdf
    • Lab/extra examples: html Rmd

Fri, Dec 1

  • Before class, please do the following:
    • Reading: No new reading
  • In class, we will do the following:
    • Continue with inference for simple linear regression.

Chapters 25 and 21: inference for regression, more on hypothesis testing

Mon, Dec 4

  • Before class, please do the following:
    • Reading: Chapter 21 (in both SDM4 and SDM3)
    • Homework 8 is due today!
  • In class, we will do the following:

Wed, Dec 6

  • Before class, please do the following:
    • Reading: No new reading
  • In class, we will do the following:

Fri, Dec 8

  • Before class, please do the following:
    • Reading: No new reading
  • In class, we will do the following:
    • Quiz covering the information from Homework 8: hypothesis tests and confidence intervals for a difference in two population proportions or population means. Identification of whether we are dealing with paired data or unpaired data. You may use 1 notes sheet.

Monday, Dec 11 is the last day of class

Mon, Dec 11

  • Before class, please do the following:
    • Homework 9 is due today!
  • In class, we will do the following:
    • Review
    • Assumptions summary: docx pdf
    • Inference summary: jpg

We will have a cumulative final exam.