Education 160, Fall 2008

Education 160 Fall 2008 David Rogosa
NOTE 10/6 This course is being reformulated--Details in class Monday

Course Description

EDUC 160. Introduction to Statistical Methods in Education. (Master's students register for 150.) 
For doctoral students. Describing measured, count, and categorical data. 
Statistical inference procedures for comparisons of group outcomes and for
associations among variables. Course content integrated with statistical computing in R. 
See http://statistics.stanford.edu/~rag/ed160/ 
Students cannot also receive credit for PSYCH 60 or for STATS 60/160. (all areas)  3-4 units, Aut

Logistics
Main course meeting: Monday 3:20--5:05, classroom 60-120 (Bldg 60 in Main Quad).
   note: best entrance interior of quad (north of church); use door "Bldg 60 classrooms", 120 on your left)
Computing Labs: selected Wednesday 11:15-12:30 (see below) Ceras 108 (Big Tree)
Weekly discussion/review section: Thursday 12:35-1:45 PM, Ceras 108 (Big Tree)
             sections and office hours will not be held during the Take-home assessment weeks, 10/20, 12/1

Instructor Information
David Rogosa    rag AT stat DOT stanford DOT edu
   Rogosa Office Hours: Th 3:30-5, Sequoia room 224
Teaching Assistants:
    Allison Atteberry (acma@stanford.edu) Office hours: Tuesdays 1:30--2:30, CERAS room 509
    Heather Hough (hjhough@stanford.edu) Office hours: Mondays 10:45--11:45, CERAS room 511
Adminstrative Course Contact: Sharon Dauskardt Cubberley 143 (650) 498-5181

Course Resources
Course Outline        Course Readings, Examples and Files        Course Assignments

Empirical Research Exemplars
1. Science education, ordered categorical data
Public Acceptance of Evolution, Science 11 August 2006 Vol. 313. no. 5788, pp. 765 - 766 Jon D. Miller, Eugenie C. Scott, Shinji Okamoto    supplemental materials
The view from Louisiana, and rukus in the UK

2. Higher education, pre-post data, comparing groups, t-tests
College: A weighty endeavor? 'Freshman 15' may be a myth, but many students pack on pounds. San Francisco Chronicle Tuesday, September 26, 2006
Changes in Body Weight and Fat Mass of Men and Women in the First Year of College: A Study of the "Freshman 15.". By: Hoffman, Daniel J.; Policastro, Peggy; Quick, Virginia; Soo-Kyung Lee. Journal of American College Health, Jul/Aug2006, Vol. 55 Issue 1, p41-45,     note: access through the Lane Library portal, lane.stanford.edu

3. Random sampling, Sample Sizes
It's not easy being random.    Oh no, not Steely Dan again             Slashdot discussion    How Much Does iTunes Like My Five-Star Songs?
'Wisdom of Crowds' Works For Individuals Too The crowd within , publication: Vul and Pashler Measuring the Crowd Within: Probabilistic Representations Within Individuals Psychological Science

4. Experimental Design, Gender differences
Guns Up Testosterone, Male Aggression
Guns, Testosterone, and Aggression: An Experimental Test of a Mediational Hypothesis Klinesmith, Jennifer; Kasser, Tim; McAndrew, Francis T, Psychological Science. Vol 17(7), Jul 2006, pp. 568-571.

5. Math education, Gender differences
a. Ring finger envy
Science See Those Fingers? Do the Math   Slashdot Boys with Longer Ring Fingers are Better at Math
Publication . Digit ratio as an indicator of numeracy relative to literacy in 7-year-old British schoolchildren: Brosnan, Mark J. Source: British Journal of Psychology, Volume 99, Number 1, February 2008 , pp. 75-85(11)
Additional data: Univ of Bath academic staff
b. No difference  Gender Similarities Characterize Math Performance Janet S. Hyde, Sara M. Lindberg, Marcia C. Linn, Amy B. Ellis, and Caroline C. Williams Science 25 July 2008: 494-495.  supplemental

6. Correlation and Causation: God, Beer, and TV
a. God High IQ turns academics into atheists
b. Beer NY Times: For Scientists, a Beer Test Shows Results as a Litmus Test   Slashdot Scientists' Success Or Failure Correlated With Beer   but Beer-Drinking Scientist Debunks Productivity Correlation   21/03: In Defense of Beer-Drinking Scientists
Publication. A possible role of social activity to explain differences in publication output among ecologist Thomas Grim Oikos, 2008 Abstract
c. TV Is TV bad or is it bad parenting? Attention Deficit Disorder and TV
2004 version : Pediatrics. 2004;113:708-713. Christakis DA, Zimmerman FJ, DiGiuseppe DL, McCarty CA. Early television exposure and subsequent attentional problems in children.   Publication   summary    press release    news report      audio NPR interview    interview transcript and publication
2006 reversal? (with LISREL) Pediatrics. March 2006. Stevens T and Mulsow M. There is no meaningful relationship between television exposure and symptoms of attention-deficit hyperactivity disorder. Pediatrics. 2006; 117(3):665-672.
News Reports: TV may not cause kids' attention disorders   Researchers say TV is not to blame for ADHD   TV may not cause kids' attention disorders: study.
Good general commentary in Slate Feb '06 The Benefits of Bozo Proof that TV doesn't harm kids.
As with most important issues, definitive wisdom is provided by South Park via Cartman: here, episode 404 (4/19/2000), episode summary      script and episode video

Textbooks
Main Text
Required: Alan Agresti and Chris Franklin(AF) Statistics: The Art and Science of Learning from Data, Publisher: Prentice Hall, Copyright: 2009, Available at the bookstore
An electronic only version of this text is available from Coursesmart
We did consider an alternative text by Agresti: Statistical Methods for the Social Sciences (4th edition, Pearson Prentice Hall, 2008), which does cover introductory material plus much of the material from the courses that would follow ed160. AF covers, in more depth, the ed160 material.
Optional text(but quite useful)
Using R for introductory Statistics, J. Verzani, Chapman & Hall, 2005.
Available at the bookstore
Draft version of much of the Verzani material avaliable from R-project
In addition, supplemental materials for Verzani are available.

Computing
for references and software: The R Project for Statistical Computing   Note: use R version 2.7.2, released on 2008-08-25.
Closest download mirror is Berkeley. The "base" distribution is adequate for the OS that offer that choice.
Computing Sessions/Labs
We plan four R computer lab sessions in Ceras 108 during the quarter
  Lab 1. Wed 9/24, 11:15-12:30   Lab1pdf Lab1 data
  Lab 2. Wed 10/8, 11:15-12:30
  Lab 3. Wed 10/29, 11:15-12:30
  Lab 4. Wed 11/19, 11:15-12:30
Lastly, if you have R installed on your laptop, you may find it helpful to bring your laptop to the lab rather than using the lab computers.
Typically the Lab session text will be posted prior to the Lab so you can bring a hard copy.

Administrative Notes
The course is graded Pass/NoCredit (or whatever euphemisms Stanford is using this year).
Assignments and Assessment
1. Weekly Problem Sets.
There will be short problems posted approximately weekly on lecture content. Solutions to these problems will be posted, and these will not be collected and graded. That said, taking these problem sets seriously is important because that's where much of the real learning takes place. Applied statistical methods is in the doing.
Tentative schedule is posting problems on Thursdays with solutions the following Wednesday.
2. Take Home Assessments.
In addition, there will be two graded problem sets:
TH1 will take place during the week of 10/20
   Details: posting on assignment page Tuesday 10/21 AM, due Monday 10/27 in class.
TH2 will take place during the End Quarter/Exam period
   Details: posting on assignment page Tuesday 12/2 AM, due at latest on scheduled exam day 12/12 (I believe)
Students not able to be on campus will be expected to turn in exams via hard-copy fax.
SUSE requirements
The Education 160 course is a requirement for first-year students. It provides an accessible introduction or a gentle review of basic data analysis and statistical methods. Students who have had strong prior instruction, continued participation in empirical research, and solid computing skills may well be best served by doing something else this fall qtr. One guidepost is to take a look at the take-home exams from another intro course I teach: Stat141, stat4bio, (a course in which freshman and English majors succeed); if you can go through TH1 and TH2 and find those routine, then you should talk to Rogosa about a waiver of the Ed160 requirement. Context note: Ed160 is a subset of Stat141 so don't be intimidated if you look at those materials.