BST 260 Schedule : Lectures

1 | Lecture | Date | Topics | Lecture Material | Homework | Discussion | References |
---|---|---|---|---|---|---|---|

2 | 1 | 9/5 | Introduction to course, R, RStudio and RMarkdown | Course introduction slides | |||

3 | Introduction to R and RMarkdown | ||||||

4 | 2 | 9/10 | Introduction to git, GitHub and homework submission | git, GitHub, and GitHub in RStudio | HW1 | ||

5 | 3 | 9/12 | Basic R | 00-motivation.Rmd | |||

6 | 01-data-types.Rmd | ||||||

7 | 02-vectors.Rmd | ||||||

8 | 03-sorting.Rmd | ||||||

9 | 4 | 9/17 | Basic R Continued | 04-vector-arithmatics.Rmd | |||

10 | 05-indexing.Rmd | ||||||

11 | 05-indexing-assessment-solutions.Rmd | ||||||

12 | 06-basic-data-wrangling.Rmd | ||||||

13 | 5 | 9/19 | Basic R Continued | 06-basic-data-wrangling.Rmd | |||

14 | 07-basic-plots.Rmd | ||||||

15 | 08-importing-data.Rmd | ||||||

16 | 09-programming-basics.Rmd | ||||||

17 | 6 | 9/24 | Intro to data visualization | distributions.Rmd | |||

18 | intro-to-ggplot2.Rmd | ||||||

19 | 7 | 9/26 | Data visualization continued | intro-to-ggplot2.Rmd | HW 1 Due by 11:59pm | ||

20 | gapminder.Rmd | HW2 | |||||

21 | 8 | 10/1 | Data visualization continued | gapminder.Rmd | |||

22 | dataviz-principles.Rmd | ||||||

23 | 9 | 10/3 | Data visualization continued | dataviz-principles.Rmd | |||

24 | 10 | 10/8 | Indigenous Peoples' Day | No Class | |||

25 | 11 | 10/10 | Midterm #1 | ||||

26 | 12 | 10/15 | Probability | discrete-probability.Rmd | HW 3 | ||

27 | continuous-probability.Rmd | ||||||

28 | 13 | 10/17 | Inference | HW 2 Due by 11:59pm Extension: HW 2 Due 10/21 by 11:59pm | |||

29 | intro-to-inference.Rmd | ||||||

30 | confidence-intervals-p-values.Rmd | ||||||

31 | 14 | 10/22 | Inference continued | parameter-estimates.Rmd | |||

32 | clt.Rmd | ||||||

33 | confidence-intervals-p-values.Rmd | ||||||

34 | models.Rmd | ||||||

35 | 15 | 10/24 | Inference continued | models.Rmd | HW 4 | ||

36 | Bayesian statistics | bayes.Rmd | |||||

37 | Election Forecasting | election-forecasting.Rmd | |||||

38 | 16 | 10/29 | Election Forecasting | election-forecasting.Rmd | |||

39 | Intro to Regression | motivation-regression.Rmd | |||||

40 | intro-to-regression.Rmd | ||||||

41 | 17 | 10/31 | Regression continued | intro-to-regression.Rmd | HW 3 Due by 11:59pm Extension: HW 3 Due 11/4 by 11:59pm | ||

42 | linear-models.Rmd | ||||||

43 | 18 | 11/5 | Regression continued | linear-models.Rmd | |||

44 | confounding.Rmd | ||||||

45 | 19 | 11/7 | Regression continued | confounding.Rmd | |||

46 | 20 | 11/12 | Veterans Day | No Class | |||

47 | 21 | 11/14 | Wrangling | intro-to-wrangling.Rmd | |||

48 | tidy-data.Rmd | HW 4 Due 11/18 by 11:59pm | |||||

49 | data-import.Rmd | ||||||

50 | reshaping-data.Rmd | ||||||

51 | 22 | 11/19 | Wrangling continued | reshaping-data.Rmd | HW 5 | ||

52 | combining-tables.Rmd | ||||||

53 | dates-and-times.Rmd | ||||||

54 | web-scraping.Rmd | ||||||

55 | 23 | 11/21 | Thanksgiving Recess | No Class | |||

56 | 24 | 11/26 | Wrangling continued | string-processing.Rmd | |||

57 | 25 | 11/28 | Midterm #2 | ||||

58 | 26 | 12/3 | Machine Learning | intro-ml.Rmd | |||

59 | 27 | 12/5 | Machine Learning continued | intro-ml.Rmd | |||

60 | 28 | 12/10 | Machine Learning continued | intro-ml.Rmd | HW 5 Due 12/9 by 11:59pm | ||

61 | Linear Discriminant Analysis (LDA) | lda.Rmd | |||||

62 | matrices.Rmd | ||||||

63 | 29 | 12/12 | Regularization and PCA | matrices.Rmd | |||

64 | regularization.Rmd | Final Projects Due 12/16 by 11:59pm | |||||

65 | 30 | 12/17 | Regularization and PCA | regularization.Rmd | |||

66 | Decision Trees | decision-trees.Rmd | |||||

67 | 31 | 12/19 | Decision Trees continued | decision-trees.Rmd | |||

68 | Next steps and screencast presentations |