Date:  Topics:  Lab and Handouts:  Reading:  Classwork & Quiz Topics:  
#1
Tues 27 August 
Syllabus; What is Data Science; Introduction to Python (math, variables, and printing); line plots with Pandas  Syllabus Citi Bike data example Data Science Process Lab 1  Introduction to Python and Pandas (Jupyter notebook) nycHistPop.csv 
Academic Integrity Policy, 3.1,3.2,3.3 Variables Line graphs 
Online quiz: Academic Integrity  
#2
Thurs 29 August 
Statistical varaibles; proportions; column operations  Lab 2  Plotting NYC's shelter population  Statistical variables  Classwork: Statistical variables  
Mon 2 September  CUNY: No classes (Labor Day)  
#3
Tues 3 Sept 
Bar charts  Lab 3  Bar charts Sept3_2018_Green_Taxi_Trip_Data.csv 
7.1  Online quiz: variables and functions (all of Lab 1 except the plotting section)  
Thurs 5 Sept  Classes follow a Monday schedule  
#4
Tues 10 Sept 
Histograms  Lab 4  Histograms  7.2, Histograms  Online quiz: Lab 1, statistical variables  
#5
Thurs 12 Sept 
Mean, median, and mode; filtering  Lab 5  Mean, Median, and Mode 
Online Stats: Median and mean Nontechnical overview: mean, median, mode 
Online quiz: Lab 2  
#6
Tues 17 Sept 
Measures of Spread: range, variance, and standard deviation  Lab 6  Measures of spread (Range, Variance, and Standard Deviation)  Measures of Variability Subway trip variability 
Classwork: mean, median, and variance  
#7
Thurs 19 Sept 
Behavior of sample vs. population; boxplots  Lab 7  Samples and boxplots  10.2 Sampling from a Population, percentiles, boxplots  Online quiz: Labs 3 and 4  
#8
Tues 24 Sept 
Introduction to probability, computing probabilities, filtering  Lab 8  Computing probabilities  9.5 Finding Probabilities,
Introduction to Probability, Computing probabilities Filtering 
Paper quiz: Labs 1 and 2 (assigments 14), statistical variables; 1 sheet of paper (8 1/2" x 11") with handwritten notes on both sides is allowed Sample quiz 

#9
Thurs 26 Sept 
Filtering  Lab 9  Filtering imdb_1000.csv 
Filtering with Pandas  Classwork  
30 September  1 October  CUNY: No classes  
#10
Thurs 3 October 
Computing probabilities with and/or, subsets of dataframes 
Lab 10  Computing probabilities 2 Sept17_2019_311_Service_Requests.csv 
9.5 Finding Probabilities  Online quiz: review, Labs 5 and 6  
89 October  CUNY: No classes  
#11
Thurs 10 October 
Iteration, Sampling and Empirical Distributions  Lab 11  Iteration and Sampling Distributions  10.3 Empirical Distribution of a Statistic 9.3 Iteration Iteration with turtles 
Paper quiz: Labs 3 and 4 (assigments 58); 1 sheet of paper (8 1/2" x 11") with handwritten notes on both sides is allowed Sample quiz 

#12
Tues 15 October 
Comparing distributions visually, data and time in pandas  Lab 12  Comparing distributions visually  Online quiz: review, Labs 7, 8, and 9  
#13
Thurs 17 October 
Simulations and hypotheses  Lab 13  Simulations and hypotheses  11.1 Assessing Models Introduction to Hypothesis Test 
Classwork: Introduction to hypotheses  
#14
Tues 22 October 
Hypothesis testing of proportions  Lab 14  Hypothesis testing of proportions 
11.1 Assessing Models Introduction to Hypothesis Test 
Paper quiz: Labs 5, 6, and 7 (assigments 914); 1 sheet of paper (8 1/2" x 11") with handwritten notes on both sides is allowed Sample quiz 

#15
Thurs 24 October 
Hypothesis testing of proportions continued  Lab 15  Hypothesis testing of proportions continued  Online quiz: Review, Labs 10, 11, 12  
#16
Tues 29 October 
Bootstrap and confidence intervals  Lab 16  Bootstrap and confidence intervals  13.1 Percentiles 13.2 The Bootstrap 13.3 Confidence Intervals Much more detail about the dataset 
Online quiz: Review and Labs 13 and 14  
#17
Thurs 31 October 
Normal distributions  Lab 17  Normal distributions  14.3 The SD and the Normal Distribution Online stats book: normal distributions Visualizing the normal distribution 
Paper quiz: Labs 8, 9, 10 (assigments 1520); 1 sheet of paper (8 1/2" x 11") with handwritten notes on both sides is allowed Sample quiz 

5 November  Last day to withdraw from class with a grade of W  
#18
Tues 5 November 
Central Limit Theorem  Lab 18  Central Limit Theorem Data: starbucksmenunutritiondrinks.csv 
14.4 The Cental Limit Theorem 14.5 The Variability of the Sample Mean Visualization of the Central Limit Theorem 
Classwork: Probabilities  
#19
Thurs 7 November 
Functions and conditional statements  Lab 19  Functions and conditional statements  8.1 Applying a function to a column 9.1 Conditional statements 
Online quiz: Review, Labs 15 and 16  
#20
Tues 12 November 
Correlation, Causation, and Heat maps  Lab 20  Correlation, causation, and heat maps Data: Feb2019_labor_market_majors.csv 
Spurious correlations Correlation guessing game 15.1 Correlation Online stats book: intro to correlation 
Paper quiz: Labs 11 and 12 (assignments 21  24); 1 sheet of paper (8 1/2" x 11") with handwritten notes on both sides is allowed Sample quiz (note that labs 10 and 11 in the sample quiz are labs 11 and 12 this term) 

#21
Thurs 14 November 
Simple linear regression, checking residuals for normality  Lab 21  Simple linear regression Data: Feb2019_labor_market_majors.csv 
15.2 The Regression Line 15.5 Visual Diagnostics Introduction to linear regression Visual explanation of linear regression 
Classwork: linear regression  
#22
Tues 19 November 
Multilinear regression, Rsquared, and prediction  Lab 22  Multilinear regression, Rsquared, and prediction  15.4 Least Squares Regression 17.6 Multiple Regression 
Online quiz: Labs 17 and 18  
#23
Thurs 21 November 
Confidence intervals for the slope of linear regression  Lab 23  Confidence intervals for regression  16.1 A regression model, 16.2 Inference for the true slope  Paper quiz: Labs 13, 14, and 15 (assignments 25  30); 1 sheet of paper (8 1/2" x 11") with handwritten notes on both sides is allowed Sample quiz 

#24
Tues 26 November 
Intro to Machine Learning: understanding the data  Lab 24  Understanding the Titantic data Kaggle: Titanic: Machine Learning from Disaster train.csv test.csv 
Classwork: Understanding the Titanic data  
28 November  1 December  Thanksgiving Recess: College Closed  
#25
Tues 3 December 
knearest neighbors (machine learning)  Lab 25  kNearest Neighbors classifier 1  17 Classification 17.1 Nearest Neighbors 17.2 Training and Testing KNN classification using ScikitLearn (Datacamp) 
Paper quiz: Labs 16 (bootstrap and confidence interval), 17 (normal distribution), 18 (Central Limit Theorem), 19 (functions), 20 (correlation and heatmaps) Sample quiz 

#26
Thurs 5 December 
knearest neighbors continued (machine learning)  Lab 26  kNearest Neighbors classifier 2  
#27
Tues 10 December 
The data science process revisited  Lab 27  The data science process revisited  Paper quiz: Labs 21, 22, 23 (linear regresesion) Sample quiz 

#28
Thurs 12 December 
Review  Sample final Spring 2019(answers) Final Spring 2019(answers) 

Thurs 19 December  Final exam 1:30pm  3:30pm, Gillet 231 