| Date: | Topics: | Reading, course materials: | Homework assigned: | Due: |
| #1
Tues 28 August |
Review of syllabus and academic integrity code. Introduction to statistics, random variables, mean. | Syllabus | Homework 1 | |
| #2
Thurs 30 August |
Random variables: variance, intro to R, mean and variance in R | Homework 2 | ||
| Mon 3 September | CUNY: No classes (Labor Day) | |||
| #3
Tues 4 September |
Data description and exploratory data analysis: types of data, stripcharts and histograms | Kerns 3rd edition: 3.1.1, 3.1.2 Data types problems |
Homework 3 | |
| #4
Thurs 6 September |
Data description and exploratory data analysis cont'd: qualitative data, measures of center, order statistics and sample quantile | Kerns 3rd edition: 3.1.3, 3.1.4, 3.2 overview, 3.2.2, 3.3.3 | Homework 4: See blackboard | Homework 1 |
| Mon 10 September - Tues 11 September | CUNY: No classes | |||
| #5
Thurs 13 September |
Data description and exploratory data analysis cont'd: measures of spread, measures of shape, 5 number summary, boxplots, and outliers | Kerns 3rd edition: 3.3.4, 3.3.5, 3.4.2, 3.4.3, 3.4.4 | Homework 5: See blackboard | Homework 2 Project Milestone 1: GitHub user name |
| Tues 18 September - Wed 19 September | CUNY: No classes | |||
| #6
Thurs 20 September |
Data description and exploratory data analysis cont'd: standardizing variables, multivariate data and data frames, comparing populations Importing data into R from a CSV file |
Kerns 3rd edition: 3.4.5, 3.5, 3.6 Supplementary notes Basics of importing CSV file: Software Carperntry: Reading and Writing CSV Files Extra troubleshooting for importing CSV: Datacamp's import tutorial NYPD crime complaint data (Sept. 2017) NYC historical population data Green taxi trip data (Feb. 2, 2016) |
Homework 6: See blackboard | Homework 3 |
| #7
Tues 25 September |
Probability in a nutshell | Visualizing conditional probability | Homework 7: See blackboard | Homework 4 |
| #8
Thurs 27 September |
Random variables revisited, Probability distributions, binomial distribution, normal distribution | Random variables visualized Normal distribution interactive graph Binomial distribution visualization |
Homework 8: See blackboard | Homework 5 |
| #9
Tues 2 October |
Likelihood and maximum likelihood estimation | Kerns 3rd edition: 9.1 Maximum Likelihood Estimation |
Homework 9: See blackboard | Homework 6 |
| #10
Thurs 4 October |
Maximum likelihood estimation cont'd | Homework 10: See blackboard | Homework 7 Project Milestone 3: Reading in CSV files, means, and standard deviation Project Milestone 4: Plotting your numerical data |
|
| 8 October | CUNY: No classes (Columbus Day) | |||
| #11
Tues 9 October |
Midterm 1 review | Homework 8 | ||
| #12
Thurs 11 October |
Midterm 1 | |||
| #13
Tues 16 October |
Central Limit Theorem | Kerns 3rd edition: 8.3 Central Limit Theorem with R |
Homework 11: See blackboard | Homework 9 |
| #14
Thurs 18 October |
Confidence intervals | Kerns 3rd edition: 9.2 Penn State: Confidence Level for One Mean |
Homework 12: See blackboard | Homework 10 Project Milestone 5: Plotting your nominal or ordinal data and comparing data |
| #15
Tues 23 October |
Introduction to hypothesis testing; type 1 and 2 errors; p-values; tests about one proportion |
Kerns 3rd edition: 10.1, 10.2 Penn State: Hypothesis Testing for Proportions |
Homework 13: See blackboard | Homework 11 (Day 13) |
| #16
Thurs 25 October |
Hypothesis testing cont'd; tests about two proportions, tests about one mean | Kerns 3rd edition: 10.3.1 Penn State: Comparing two proportions 2 proportion tests in R: Two Proportion Z-Test in R Penn State: Tests about one mean |
Homework 14: See blackboard | Homework 12 (Day 14) Project Milestone 6: |
| #17
Tues 30 October |
imdb_1000.csv Kerns 3rd edition: 10.4.1 Penn State: Comparing two means Calculating proportions from datasets in R: Proportions with mean() Taking subsets of data in R: Subsetting data |
Homework 15: See blackboard | Homework 13 (Day 15) | |
| #18
Thurs 1 November |
Simple Linear Regression | Kerns 3rd edition: 11.1, 11.2 | Homework 16: See blackboard | Homework 14 (Day 16) Project Milestone 6: Confidence Intervals |
| #19
Tues 6 November |
Simple Linear Regression Cont'd, Multiple Linear Regression, QQ-plots | Code from class Kerns 3rd edition: 11.2.3, 11.2.4, 11.2.6, 12.1 |
Homework 15 (Day 17) | |
| 6 November | Last day to withdraw from class with a grade of W | |||
| #20
Thurs 8 November |
Midterm 2 review | Homework 16 (Day 18) | ||
| #21
Tues 13 November |
Midterm 2 | |||
| #22
Thurs 15 November |
Code from class: Day22.R | Project Milestone 7: Hypothesis Testing |
||
| #23
Tues 20 November |
Analysis of variance (ANOVA) | Code from class: Day23.R Penn State: One-Factor Analysis of Variance Visualizing ANOVA |
||
| 23-25 November | Thanksgiving Recess: College Closed | |||
| #24
Tues 27 November |
Analysis of variance cont'd | Penn State: One-Factor Analysis of Variance Visualizing ANOVA Code from class: Day24.R |
Homework 18: See blackboard | |
| #25
Thurs 29 November |
Chi-squared test | Penn State: Chi-Squared Goodness-of-Fit Test Code from class: Day25.R |
Homework 19: See blackboard | Project Milestone 7: Hypothesis Testing Milestone 8: Regression or another analysis |
| #26
Tues 4 December |
Bayesian statistics | Homework 20: See blackboard | Homework 18 (Day 24) | |
| #27
Thurs 6 December |
Project presentations, Bayesian satistics cont'd | Homework 19 (Day 25) Project slides due at 10am |
||
| #28
Tues 11 December |
Review for final exam | Homework 20 (Day 26) | ||
| Thurs 13 December | Final project due | |||
| Tues 18 December | Final exam 3:45pm - 5:45pm | |||