Metric theory

My log for studying metric theory

This pages contains log for my self-study on metric theory.

week date topic hw hw_sol exam notes
1 Aug 29 No lab
Aug 30 Welcome to STA 199
Sep 1 Meet the toolkit
2 Sep 5 Hello R! Release: Lab 0
Sep 6 Grammar of graphics
Sep 8 Visualizing various types of data Release: HW 1
Sep 9
Due: Lab 0 + AE 1
Sep 11
Due: AE 2
3 Sep 12 Data visualization Release: Lab 1
Sep 13 Grammar of data wrangling
Sep 15 Working with multiple data frames Due: HW 1 / Release: HW 2
Sep 16
Due: Lab 1
4 Sep 19 Data wrangling Release: Lab 2
Sep 20 Tidying data
Sep 22 Data types and classes Due HW 2
Sep 23
Due: Lab 2
5 Sep 26 Data tidying Release: Lab 3
Sep 27 Importing and recoding data
Sep 29 Exam 1 Review Release: Exam 1 at 12pm
Sep 30
Due: Lab 3
6 Oct 3 No lab - Work on Exam 1 Due: Exam 1 at 2pm
Oct 4 Data science ethics - Misrepresentation
Oct 6 Data science ethics - Algorithmic bias + data privacy Release: HW 3
7 Oct 10 No lab - Fall break
Oct 11 No Lec - Fall break
Oct 13 Web scraping Due: HW 3
8 Oct 17 Work on project proposal
Oct 18 Functions + iteration
Oct 20 The language of models
Oct 21
Due: Project proposal
9 Oct 24 Probability + Simpson's Paradox Release: Lab 4
Oct 25 Models with a single predictor
Oct 27 Models with multiple predictors Release: HW 4
Oct 28
Due: Lab 4
10 Oct 31 Predicting a numerical outcome Release: Lab 5
Nov 1 Models with multiple predictors + Overfitting
Nov 3 Logistic regression Due: HW 4 / Release: HW 5
Nov 4
Due: Lab 5 / Release: HW 6
Nov 5
Due: Team peer evaluations 1
11 Nov 7 Work on project draft
Nov 8 Quantifying uncertainty with bootstrap intervals
Nov 10 Hypothesis testing via simulation Due: HW 5
Nov 11
Due: Project draft 1
12 Nov 14 Prediction + Bootstrapping Release: Lab 6
Nov 15 Inference overview
Nov 17 Exam 2 Review Release: Exam 2 at 12pm
Nov 18
Due: Lab 6
13 Nov 21 No lab - Work on Exam 2 Due: Exam 2 at 2pm
Nov 22 No lecture - Work on projects
Nov 24 No lecture - Thanksgiving
Nov 25
Release: Exam retake (optional)
Nov 27
Due: Project draft 2 (optional)
14 Nov 28 Work on project peer review Due: Project peer review
Nov 29 Communicating data science results effectively Due: Team peer evaluations 2
Dec 1 Customizing Quarto reports and presentations
15 Dec 5 Project presentations
Dec 6 Looking further: Text analysis
Dec 8 Looking further: Interactive web applications with Shiny Due: Project everything
Dec 9
Due: HW 6 / Statistics experience
16 Dec 15
Due: Exam retake (optional)