Week
 Unit
 Day
 Date
 Topic
 Due / In class


Week 1
 Unit 1 
M 
26Aug 
Getting to know you survey 






Gmails for RStudio accounts 






Develop questions for the class survey 




T 
27Aug 
Introduction 




R 
29Aug 
Data collection, observational studies and experiments 
Pretest (Access code: LSR9129LSP) 





Application exercise: 1.1 Scientific studies in the press 




Sa 
01Sep 

By midnight: Class survey 

Week 2 

M 
02Sep 
Lab 0  Intro for R and RStudio  [video] 




T 
03Sep 
Exploratory data analysis 
RA1 





Application exercise: 1.2 Shapes of distributions 






Application exercise: 1.3. Variability 




R 
05Sep 
EDA (cont.) + Introduction to statistical inference 




F 
06Sep 

PA1, Clicker registration 

Week 3 
Unit 2 
M 
09Sep 
Lab 1  Introduction to data 




T 
10Sep 
Probability and conditional probability 
RA2 



R 
12Sep 
Bayes' theorem and Bayesian inference 
PS1 





Application exercise: Breast cancer screening 


Week 4 

M 
16Sep 
Lab 2  Probability 
L1 



T 
17Sep 
Normal distribution 
PE1 





Application exercise: Working with the normal distribution 




R 
19Sep 
Binomial distribution 
PS2 



F 
20Sep 

PA2 

Week 5 
Unit 3 
M 
23Sep 
Lab 3  Foundations for inference: Sampling distributions 
L2 



T 
24Sep 
Variability in estimates and CLT 
RA3 



R 
26Sep 
Confidence intervals and hypothesis testing 
PS3 

Week 6 

M 
30Sep 
Lab 4  Foundations for inference: Confidence intervals 
L3 



T 
01Oct 
Decision errors, significance levels, sample size, and power 






Application exercise: 3.1 Calculating power 



 R 
03Oct 
Review / synthesis 
PS4 





Practice problems & solutions 






Midterm  Spring 2013  [Key] 




F 
04Oct 

PR1 Proposal, due at 5pm 



Sa 
05Oct 

PA3 

Week 7 

M  07Oct  Review / synthesis  L4  


T 
08Oct 
MIDTERM  [grade distribution] 



Unit 4 
R 
10Oct 
Comparing two means 
PE2 





Application exercise: 4.1 Comparing two means 


Week 8 

M 
14Oct 
Fall Break  No lab 




T 
15Oct 
Fall Break  No class 




R 
17Oct 
Bootstrap intervals 
PS5, RA4 

Week 9 

M 
21Oct 
Lab 5  Inference for numerical variables 




T 
22Oct 
ttests/intervals 




R 
24Oct 
ANOVA 
PS6 





Application exercise: Comparing two or more means 




F 
25Oct 




 S  26Oct 

PA4 

Week 10 
Unit 5 
M 
28Oct 
Lab 6  ANOVA + Inference for categorical variables 
L5 



T 
29Oct 
Large sample proportions
 RA5 



R 
31Oct 
Guest lecture  Tim Hesterberg (Google) 
PS7 



F 
1Nov 

PE3 

Week 11 

M 
04Nov 
Lab  Work on Project 1 
L6 



T 
05Nov 
Small sample proportions 




R 
07Nov 
Chisquare 
PR1, due in class 



F 
08Nov 

PA5 

Week 12 
Unit 6 
M 
11Nov 
Lab 7  Simple linear regression 




T 
12Nov 
Introduction to SLR 
RA6 



R 
14Nov 
Outliers & Inference for SLR 
PS8 



S 
16Nov 

PA6 

Week 13 
Unit 7 
M 
18Nov 
Lab 8  Multiple linear regression 
L7 



T 
19Nov 
Introduction to MLR 
RA7 



R 
21Nov 
Model selection & diagnostics for MLR 
PS9 





Application exercise: MLR: Interpretations & diagnostics 


Week 14 

M 
25Nov 
Lab  Work on project 2 
L8 



T 
26Nov 
Confidence and prediction intervals & Transformations 




R 
28Nov 
Thanksgiving  no class 


Week 15 

M 
02Dec 
Lab  Project 2 Presentations 
PA7 


T 
03Dec 
Bayesian vs. frequentist inference 






Application exercise: Bayesian inference (revisited) 




R 
05Dec 
Review / synthesis  [Solutions] 
PR2,
PS10 





MT2  S12, MT2  S12  Key 






Final Review, Final Review  Key 






Final Review  Add Q, Final Review  Add Q  Key 






Posttest (Access code: CYE4118OBM) 


Week 16 

T 
10Dec 

PA8 (extra credit) 



W 
11Dec 
Final review, 5:30pm  6:30pm, FCIEMAS SCHICIANO A 


  F  13Dec  FINAL (2pm  5pm)   