SI 544 Introduction to Statistics and Data Analysis


SI 544 home

Readings, assignments, etc. will be posted to the course ctools website

problem sets

software tools for the class

other resources

waiving the stats requirement for HCI


Fall 2006:

Lectures will be
Tuesdays and Thursdays
from 9:00 to 10:30 am (argh, I know).
On Tuesdays we will usually meet in 409 West Hall, on Thursdays we will be at the DIAD lab.

Office hours:
Tuesday 10:30-11:30am
in 3082 West Hall




This course teaches the fundamentals of statistics, that is, the ability to describe data samples and draw inferences about the populations from which they were drawn. It should also sharpen individual intuition about how to read data, interpret data, and judge others' claims about data.

Specifically, at the end of this course students should be able to:
  • characterize population data intuitively for themselves and others;
  • draw conclusions and inferences from population data;
  • check assumptions of others' claims and debug their putative "facts";
  • look for correlations while controlling for confounding effects

Prerequisites: none

Reading: We will be using two textbooks:

  • Introductory Statistics for the Behavioral Sciences (5th Edition) by Welkowitz, Ewen, and Cohen (the publisher is just coming out with the 6th edition, but we'll be sticking with the 5th).
  • Introductory Statistics with R (Paperback) by Peter Dalgaard

Both books will be available at Ulrich's.

Assignments and grading

Instructor: Lada Adamic, office hour Tuesday 10:30-11:30 am

Course Syllabus (click on PDF icon to download lab notes)

  date subject reading assignment due
1 Tue 9/5 intro S.ch1  
2 Thu 9/7 lab: descriptive statistics S.ch2-5,7, R.ch1, R.ch3  
3 Tue 9/12

probability intro

McClave & Sincich Ch 3  
4 Thu 9/14 lab: discrete distributions R.ch2  
5 Tue 9/19 continuous distributions S.ch9, A1* PS 1 (extension)
6 Thu 9/21

lab: scatter plots and transformed scores

S.ch6 PS 2
7 Tue 9/26 sampling A2,A3*  
8 Thu 9/28 examples of applications R.ch4 PS 3
9 Tue 10/3 concepts of statistical inference S.ch8  
10 Thu 10/5 lab: outliers, confidence intervals R.ch5.103 PS 4
11 Tue 10/10 significance testing S.ch10, S.ch11  
12 Thu 10/12 lab: one and two sample tests R.ch4 PS 5
  Tue 10/17 --study break--    
13 Thu 10/19 in-class midterm
14 Tue 10/24 simple linear regression S.ch12, S.ch13  
15 Thu 10/26 lab: simple linear regression and correlation
R.ch5.4 PS 6
project proposal
16 Tue 10/31 analysis of variance S.ch15 & ch 16  
17 Thu 11/2 lab: analysis of variance R.ch6 PS 7
18 Tue 11/7 tabular data S.ch17  
19 Thu 11/9 guest lecture: Mick McQuaid   article review
20 Tue 11/14 statistical communication A4*,A5*  
21 Thu 11/16 lab: tabular data R.ch7 PS 8
22 Tue 11/21 power S.ch14 ( 8)  
  Thu 11/23 -- Thanksgiving break--    
23 Tue 11/28 logistic regression   PS 9
24 Thu 11/30 lab: multiple & logistic regression R.ch9, R.ch11  
25 Tue 12/5 other random statistical tests   project report
26 Thu 12/7 student project presentations    
27 Tue 12/12 review take home final given out due 12/19

*The following can be obtained from cTools:

  • A1: Freakonomics Introduction: the hidden side of everything
  • A2: Freakonomics 1. What do schoolteachers and sumo wrestlers have in common?
  • A3: Feakonomics 5. What makes a perfect parent?
  • A4: Fairness and the Assumptions of Economics
    Daniel Kahneman; Jack L. Knetsch; Richard H. Thaler
    The Journal of Business, Vol. 59, No. 4, Part 2, 1986
  • A5: Joel Best. 2004. “Chapter 1: Missing Numbers.” in More Damned Lies and Statistics. Berkeley and Los Angeles: University of California Press.

The Tuesday lectures used slides from a previous version of this course taught by Paul Resnick. You can download the slides there.