Lectures
Please check often. Subject to change. New material is added approximately on a weekly basis.
Chapters refer to the assigned textbook (3rd edition). Corresponding chapters exist in the 2nd edition but may have a different number.
| 1 |
9/3 |
1.1 Statistics & Samples |
Ch. 1 |
| 2 |
9/8 |
1.2 Statistics & Samples |
Ch.1, Interleaf 1: Correlation does not require causation |
| 2 |
9/10 |
1.3 Statistics & Samples |
Ch.1, Interleaf 1: Correlation does not require causation |
| 3 |
9/15 |
1.4 Statistics & Samples |
Interleaf 6: Controls in medical studies |
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2.1 Displaying & Describing Data |
Ch.2-3 |
| 3 |
9/17 |
2.2 Displaying & Describing Data (center) |
Ch.2-3 |
| 4 |
9/22 |
2.3 Displaying & Describing Data (spread) |
Ch.2-3 |
| 4 |
9/24 |
2.4 Displaying & Describing Data (plots) |
Ch. 2-3 |
| 5 |
9/29 |
2.5 Displaying & Describing Data (plots) |
Ch. 2-3 |
| 5 |
10/1 |
3.1 Probability |
Ch.5 |
| 6 |
10/6 |
3.2 Probability |
Ch.5 |
| 6 |
10/8 |
3.3 Probability |
Ch. 5 |
|
10/13 |
No classes (Fall Break!) |
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| 7 |
10/20 |
4.1 Estimation & Hypothesis Testing |
Ch. 4 |
| 7 |
10/22 |
4.2 Estimation & Hypothesis Testing |
Ch.4-6 |
| 8 |
10/27 |
4.3 Estimation & Hypothesis Testing |
Ch.4-6 |
| 8 |
10/30 |
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| 9 |
11/3 |
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| 9 |
11/5 |
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| 10 |
11/10 |
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| 10 |
11/12 |
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| 11 |
11/17 |
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| 11 |
11/19 |
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| 12 |
11/24 |
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| 12 |
11/26 |
No in-person class (recorded lecture posted on Moodle) |
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| 13 |
12/1 |
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| 13 |
12/3 |
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| 14 |
12/8 |
Wrap-up, Review |
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| 14 |
12/10 |
Review, Course Evals |
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Labs
| 1 |
2/9 |
Course Logistics |
|
| 1 |
2/9 |
Rstudio/R introduction |
DC Introduction to R |
| 2 |
9/9 |
Data Types |
DC Introduction to R |
| 3 |
9/16 |
Data Stuctures |
DC Introduction to Importing Data With R |
| 4 |
9/23 |
Describing Data: Summary Statistics and Plots |
DC Data Manipulation with dplyr |
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DC Introduction to the Tidyverse (Grouping and Summarizing; Data Wrangling; Data Visualization; Types of visualizations) |
| 5 |
9/30 |
R markdown, Tidyverse, and Exploratory Data Analysis |
DC Reporting with Rmarkdown (Getting Started; Adding Analyses and Visualizations) |
| 6 |
10/7 |
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Introduction to Data Visualization with ggplot2 |
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10/14 |
No lab (fall break!) |
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| 7 |
10/21 |
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10/28 |
No lab (in class Midterm) |
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| 8 |
11/4 |
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| 9 |
11/10 |
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| 10 |
11/18 |
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| 11 |
11/25 |
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| 12 |
12/2 |
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| 13 |
12/9 |
Wrap-up |
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Problem sets
| 1 |
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Fri 10/3 |
Easy/Medium |
Formative |
| 2 |
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Wed 10/22 |
Medium/Hard |
Formative |
| 3 |
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Fri 11/7 |
Medium/Hard |
Formative |
| 4 |
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T 11/25 |
Medium/Hard |
Formative |
| 5 |
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W 12/10 |
Medium/Hard |
Formative |
Coding Assignments
| 1 |
TBD |
Fri 10/31 |
Hard |
Summative |
| 2 |
TBD |
Fri 12/05 |
Hard |
Summative |
Midterms
| Midterm 1 |
Week 1-7 |
10/28, during lab |
Hard |
Summative |
| Midterm 2 |
Weeks 1-14 |
Finals week, scheduled (TBD) |
Hard |
Summative |
Office Hours
Please attend OH at least 2x during the semester (the more the merrier).
| Professor drop-in hours |
Monday 2-3:30pm |
Park 211 |
| Professor drop-in hours |
Wednesday 2-3:30pm |
Park 211 |
| Professor drop-in hours |
Thursday 2-3:30pm |
Zoom |
| TA |
Thursday 4-6pm |
Park 227 |
If you can’t attend any of the times above you can schedule an appointment with me using my calendly link.