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; pvalues; 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 ZTest 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, QQplots  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: OneFactor Analysis of Variance Visualizing ANOVA 

2325 November  Thanksgiving Recess: College Closed  
#24
Tues 27 November 
Analysis of variance cont'd  Penn State: OneFactor Analysis of Variance Visualizing ANOVA Code from class: Day24.R 
Homework 18: See blackboard  
#25
Thurs 29 November 
Chisquared test  Penn State: ChiSquared GoodnessofFit 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 