Schedule

Week	Date	Les-son	Theme	Topic	Lesson video	Slides	TB 1	TB 2
1	06/22	1	Course info	Welcome			Intro
		2	Course info	Course logistics
		3	R Basics	Download + Intro to R & Rstudio				3.4-3.5
		4	R Basics	R scripts			6.1	3.8
		5	R Basics	Basics			2.1	8.2
		6	Best Practices in R	Comments			2.2
	06/28			Practice 1 due
2	06/29	7	Rigor & Reproducibility	Folder and file Organization
		8	Rigor & Reproducibility	Quarto and .qmd’s			28
		9	R Basics	Packages				3.7
		10	Rigor & Reproducibility	R projects and working directories			6.2.3-6.2.4	6
	07/05			Practice 2 due
				Nicky on vacation this week
3	07/06	11	Course info	Introduction to HRS dataset
		12	R Basics	Functions			2.4	3.6
		13	R Basics	Objects				3.10
		14	Best Practices in R	Common Errors				47.2
		15	Best Practices in R	Getting help			8
	07/12			Practice 3 Due
				Nicky out of town, but can answer emails
4	07/13	16	R Basics	Piping			3.4, 4.3	8.1
		17	R Basics	Key operators and functions			12.3	8.2
		18	R Basics	Import and Export			7	7
		19	R Basics	Tidy data			5.2	4.1
	07/19			Practice 4 due
	07/19			Lab 1 due
5	07/20			Catch-up week, no work
6	07/27	20	Data transformation	Intro to data transformations and summarizations			3.1
		21	Data transformation	Data transformation: rows			3.2	13.7-13.8
		22	Data transformation	Data transformation: columns			3.3
		23	Data transformation	Data transformations: advanced			12.2, 16	11
	08/02			Practice 5 due
7	08/03	24	Data summarization	Data summarization: Intro				17
		25	Data summarization	Data summarization: quick summaries				17
		26	Data summarization	Data summarization: tables				17
		27	Data summarization	Data summarization: grouped summaries			3.5	17
	08/09			Practice 6 due
	08/09			Lab 2 due
8	08/10	28	Data transformation	Lengthening data			5.3
		29	Data transformation	Widening data			5.4
		30	Rigor & Reproducibility	Quarto and .qmd’s: Revisited			28
	08/16			Practice 7 due
	08/16			Lab 3 due
9	08/17	31	Data visualization	Data visualization: Intro to ggplot			1.1-1.3	30.2-30.5
		32	Data visualization	Data visualization: Basic plotting			9.2-9.3	30.4-30.5
		33	Data visualization	Data visualization: Design choices			1.5	30.6-30.10
	08/23			Practice 8 due
10	08/24	34	Data visualization	Missing data: summarization and visualization				20.4
		35	Data transformation	Missing data: transformations
	08/30			Practice 9 due
	08/30			Lab 4 due
11	08/31		Course info	Project help
	09/06			Final Project due