Downloads - Paul Johnson Homepage - FreeFaculty.org

POLS 706 PSYCH 650/790 : Spring 2012
Paul E. Johnson
pauljohn@ku.edu
Professor, Political Science
Assoc. Director, Center for Research Methods and Data Analysis
1541 Lilac Lane, Room 523 470 Watson Library
Office Hours: 2-4 M&W + Appt., POLS: (785) 864-9086 CRMDA: (785)864-3353
GTA: Matt Miles , 408 Blake Hall
Luke McCune , 10 Fraser Hall
KU BlackBoard: http://courseware.ku.edu
Lectures: http://pj.freefaculty.org/guides
Textbooks
Verzani, John. 2005. Using R for Introductory Statistics. Chapman & Hall/CRC.
John Fox. 2008. Applied Regression Analysis and Generalized Linear Models. Beverly Hills: Sage.
Zuur, Alain, Elena N. Ieno, and Erik HWG Meesters. 2009. A Beginner’s Guide to R. (KU Library-Ebook)
Johnson, Paul. Stuff Worth Knowing. Newest edition always available in the KU Blackboard system.
Course Topics: distributions, inference, regression analysis
Prerequisites: One semester of statistics and/or research design. Algebra is vital and will be used regularly.
Calculus is not required, but helpful in understanding derivations.
Grades
Tests: Midterm Exam: 2 x 25%
Final Exam: 30%
Homework Exercises: 20%
Software
You can use any software you want, but we can only help you with SAS and R. R is the “hot new” thing.
SAS is a venerable “old friend”. SPSS is frowned upon because it “dumbs down” too many user choices.
Stata is quite nice, you should look into it as well.
What is in KU Blackboard?
1. Announcements
2. Downloads: Readings, example code, and other miscellaneous items.
3. A “forum” (or “bulletin board”) where we want you to ask questions. DON’T email us individually,
always ask publicly.
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Why http://pj.freefaculty.org?
Blackboard is a closed system and it is difficult to keep up-to-date. It also excludes non-students. I want
my course notes and programs to remain available to you after the semester is over. Students at other
institutions often find these pages useful.
Everything is organized this rubric: http://pj.freefaculty.org/guides. The sections are “Computing-
HOWTOs”, “Rcourse”, “stat”, “c-programming”, and “java-programming.”
In the top section of “stat”, I have a Java applet that displays a “mind map” of the statistical offerings. If
that does not help you to understand what’s going on, just browse down the page and the directory list is
available.
What files will you see there? The folders include source code that I use to produce the slide shows, the
“pdf” output files, R code files, and maybe some graphics.
Subversion repository.
There is another way to keep up to date. I put everything–I mean everything–code, document markup,
etc–into a “version management system” called Subversion. If you register for a free CRMDA account, you
can have direct access to all of these files in an easy-to-update folder. Follow along with the instructions in my
Subversion writeup: http://pj.freefaculty.org/guides/Computing-HOWTO/SubversionUse/SVN-intro.
pdf to obtain access.
About Computing Skills
1. The ability to use a computer effectively is vital for all researchers. While this course is not primarily
about computing, I still want to help you become effective users.
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Along those lines, I have been working on a book manuscript for a long time called Stuff Worth Knowing:
And Not Much More. It is almost finished, and you might want to browse the chapter headings to see
if it has some advice that will help you. I’ll make sure there is always a copy somewhere in the KU
Blackboard page for this class.
2. From time to time, I will set aside time to tell you neat things about computing. That’s not something
I will test you about. It just makes me happy.
3. Tips:
Conduct
(a) Keep your projects organized into separate folders.
(b) Develop a good backup scheme. Today, I integrate backup with version management in Subversion,
but mirroring is also a handy way to backup.
(c) Never put blank spaces in file names or directory names. It creates trouble when interacting with
other systems.
(d) Become a “grown up” software user: join email lists like “r-help”, (http://www.r-project.org),
semnet (http://www2.gsu.edu/~mkteer/semnet.html), etc. I suggest you get an account on
Gmail for those lists (and learn how to use labels and filters on Gmail).
(e) Learn to make professional looking tables and graphs. If you can’t make them, at least learn what
they are supposed to look like!
Students are expected to comply with University codes, policies, laws, and guidelines. Information on
academic misconduct is available at the following address: http://www.studenthandbook.ku.edu/codes.
shtml#Academic%20Misconduct.
Schedule of Readings
1. Jan 17. Welcome, Howdy, Install your software and get going.
You can use whatever kind of computer OS you like, whatever software you like. I can show you how
to get some things done with L Y X and R that will be more difficult with MS Word, but the choice
is up to you. My opinion is that technical work–especially research computing–is quite a bit different
than pointing and clicking in Microsoft Office, but you will have to draw your own conclusions.
(a) For Documents: Most of my documents are prepared with LYX, a “GUI editor” for L A TEX documents.
LYX is available for all major OS (http://www.lyx.org). If you want to work on
documents of type “*.lyx”, you need LYX (and the things it requires). If you are on Windows or
Macintosh, I suggest you download the full installer “bundle”, rather than the small script that
tries to separately download the individual pieces.
(b) For Stats: R is easy and free to install on just about any operating system. R for Macintosh
includes a pretty good built-in file editor. For Linux, there is no editor at all, and in Windows
there is a poor editor. What to do?
i. If you are a Windows user, I have system setup advice on the CRMDA web pages.
http://web.ku.edu/~quant/cgi-bin/mw1/index.php?title=Windows:AdminTips
Probably the easiest-to-manage R setup would include “RStudio” as the editor, but in the lab
many Windows people also like Notepad++. I use Emacs with ESS (http://www.emacswiki.
org/emacs/ESSWindowsAdvice). But you can choose.
If I were you, I’d turn off “hide extensions of known file types in Windows.”
ii. If you use Linux, install Emacs, install ESS.
(c) For Stats: SAS exists and offers some fitting routines that are handy.
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(d) The CRMDA has some “remote desktop accessible” Microsoft Windows workstations. You can
use a remote desktop client program to access those systems and try them out. We are improving
the documentation at (http://quant.ku.edu/mw1).
2. Jan 19. Describing One Variable (primarily numeric variables)
Read: Verzani, Ch. 1 & 2, Fox, Chapter 3.1
Priorities: histogram, kernel density, mean, median, mode, standard deviation, variance, scaling
Lecture: /stat/Descriptive/CentralTendencyAndDispersion
http://pj.freefaculty.org/guides/stat/Descriptive/CentralTendencyAndDispersion/CentralTendencyAndDi
pdf
3. Jan 24. Describing Two Variables
Read: Verzani, Ch. 3, Fox, Chapter 3.2, 3.3
Priorities: scatterplot, barplot, boxplot, correlation
Lecture: /stat/Descriptive/ScatterBoxBarPlots
http://pj.freefaculty.org/guides/stat/Descriptive/ScatterBoxBarPlots
4. Jan 26. Regression Survey: The “Big Picture” For This Course
Read: Fox, Ch. 2
Math Refresher: If you have forgotten college algebra, please consider the Emergency Math Review
of material in Stuff Worth Knowing. I’d suggest Chapter 10 “Summation Signs” & 11 “Curves in
Theory”.
Lecture: stat/Regression/Overview
http://pj.freefaculty.org/guides/stat/Regression/Overview/Regression-Overview-Lecture.pdf
5. Jan 31. Statistical Distributions
Read: Verzani, Chapter 5 & 6
Paul E. Johnson, “Distribution Overview: Probability by the Seat of the Pants,” http://pj.freefaculty.
org/guides/stat/Distributions/DistributionOverview/DistributionReview.pdf
an essay I have created just for this purpose!
Browse through this: Regress+ Compendium of Statistical Distributions http://www.causascientia.
org/math_stat/Dists/Compendium.pdf
Math Refresher: If you never took calculus–or forgot–I suggest you review “Integrals are not Scarey”
http://pj.freefaculty.org/guides/stat/Math/Integrals/Integrals-guide.pdf. There is
a more extended discussion of integrals in Stuff Worth Knowing.
Lecture: /stat/Distributions/DistributionOverview/ http://pj.freefaculty.org/guides/stat/Distributions/
DistributionOverview/DistributionReview-1-lecture.pdf
6. Feb 2. Statistical Distributions (continued): Using R to Explore Distributions:
Read: Catch up on what I assigned before.
Lecture: /Rcourse/rRandomVariables
http://pj.freefaculty.org/guides/Rcourse/rRandomVariables/rRandomVariables.pdf
7. Feb 7. Central Limit Theorem and Sampling Distributions
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Read: Bowen & Weisberg, An Introduction to Data Analysis, Ch. 10 “Statistical Inference” (available
in the Blackboard)
Lecture: stat/Inferential/CentralLimitTheorem http://pj.freefaculty.org/guides/stat/Inferential/
CentralLimitTheorem/CLT-lecture1.pdf
8. Feb 9. Confidence Intervals
Read: Verzani, Ch. 7
Lecture: stat/Inferential/ConfIntervals
http://pj.freefaculty.org/guides/stat/Inferential/ConfIntervals/ConfIntervals-lecture.pdf
9. Feb 14. Hypothesis Testing
Read: Verzani, Ch. 8
Lecture: stat/Inferential/HypoTesting
http://pj.freefaculty.org/guides/stat/Inferential/HypoTesting/SignifTests-lecture.pdf
10. Feb 16. Regression: One Input Variable
Read: Verzani, Ch. 3.4, and Ch. 10; Fox, Ch 5.1; Cohen, et al, Ch. 2
Lecture: stat/Regression/ElementaryOLS
http://pj.freefaculty.org/guides/stat/Regression/ElementaryOLS/Regression-1-lecture.pdf
11. Feb 21. Regression: Hypo testing: t tests, F test, Confidence Intervals
Read: *Woolridge, Introductory Econometrics, Chapter 3; Fox, Ch. 6.1
Lecture: stat/Regression/ElementaryOLS http://pj.freefaculty.org/guides/stat/Regression/
ElementaryOLS/Regression-2-lecture.pdf
12. Feb 23. Regression: Review & Worked Examples
13. Feb 28. Test 1
14. Mar 1. Regression: Multiple Inputs
Read: *Woolridge, Introductory Econometrics, Chapter 3; Verzani, Ch. 11; Cohen, Ch. 3
Lecture: stat/Regression/MultipleRegression
http://pj.freefaculty.org/guides/stat/Regression/MultipleRegression/Regression-MultipleInputs-lectu
15. Mar 6. Regression: Semi-partial Correlations, etc:
Read: Cohen, Ch. 5.5
Lecture: http://pj.freefaculty.org/guides/stat/Regression/MultipleRegression/Regression-MultipleInp
pdf
16. Mar 8. Regression Assumptions and Plots For Checking Them
Read: Cohen, Ch. 4
Lecture: http://pj.freefaculty.org/guides/stat/Regression/MultipleRegression/Regression-MultipleInp
pdf
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17. Mar 13. Nonlinear Regression I
Read: Fox, Ch. 12.3, Cohen, Ch. 6.1, 6.2, 6.4
Lecture: /stat/Regression-Nonlinear/Nonlinear-Overview/
http://pj.freefaculty.org/guides/stat/Regression-Nonlinear/Nonlinear-Overview/Nonlinear-1-Overviewpdf
18. Mar 15. Nonlinear Regression, II
Read: Fox, Ch 18, Cohen, Ch. 6.6
Lecture: /stat/Regression-Nonlinear/Nonparametric-Loess-Splines/ http://pj.freefaculty.org/guides/
stat/Regression-Nonlinear/Nonparametric-Loess-Splines/Nonparametric-1-lecture.pdf
19. Mar 27. Error Term Trouble: Heteroskedasticity & Autocorrelation
Read: Cohen, Ch 4.4.4-4.4.5; 4.5.4-4.5.5
Lecture: /stat/Regression/Heteroskedasticity-WLS http://pj.freefaculty.org/guides/stat/Regression/
Heteroskedasticity-WLS/Heteroskedasticity-WLS-lecture.pdf
Lecture: /stat/Regression/TimeSeries http://pj.freefaculty.org/guides/stat/Regression/TimeSeries/
TimeSeries-1-lecture.pdf
20. Mar 29. Test #2.
21. Apr 3. Categorical Predictors
Read: Cohen, Ch. 8
Lecture: /stat/Regression/CategoricalPredictors/lecture-1 http://pj.freefaculty.org/guides/stat/
Regression/CategoricalPredictors/
22. Apr 5. Topic: Multicollinearity and Variable Selection
Read: Cohen, 10.5-10.7, Fox 13
Lecture: /stat/Regression/Multicollinearity/
http://pj.freefaculty.org/guides/stat/Regression/Multicollinearity/Multicollinearity-1-lecture.
pdf
23. Apr 10. Points of Caution (even Skepticism!)
Read: King, Gary. (1986). “How Not to Lie with Statistics: Avoiding Common Mistakes in Quantitative
Political Science.” American Journal of Political Science, 30(3), 666-687.
Lecture: /stat/Regression/StandardizedBeta/
http://pj.freefaculty.org/guides/stat/Regression/StandardizedBeta/Standardized-1-lecture.
pdf
24. Apr 12. Influence Diagnostics (The Hat Matrix)
Read: Cohen, 10.1-10.5, Fox Ch. 11
Lecture: /stat/Regression/RegressionDiagnostics/
http://pj.freefaculty.org/guides/stat/Regression/RegressionDiagnostics/RegDiagnostics-1-lecture.
pdf
25. Apr 17. Interactions
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Read: Cohen, 7
Lecture: /stat/Regression-Nonlinear/Interaction-Categorical/ http://pj.freefaculty.org/guides/
stat/Regression-Nonlinear/Interaction-Categorical/Interaction-Continuous-1-lecture.
pdf
Additional Reading: More on why Mean Centering does not help with Multicollinearity (
Echambadi, R., & Hess, J. D. (2007). Mean-Centering Does Not Alleviate Collinearity Problems in
Moderated Multiple Regression Models. Marketing Science, 26(3), 438-445.
Kromrey, J. D., & Foster-Johnson, L. (1998). Mean Centering in Moderated Multiple Regression:
Much Ado about Nothing. Educational and Psychological Measurement, 58(1), 42 -67.
26. Apr 19. Interactions: Categorical with Continuous
Read: Cohen, 9.3
Lecture: Regression-Nonlinear/Interaction-Categorical
http://pj.freefaculty.org/guides/stat/Regression-Nonlinear/Interaction-Categorical/Interaction-Cate
pdf
27. Apr 24. Catch Up, Comments on “missing values” if time permits.
28. Topic: Logit I
Read: Verzani, Ch. 12; Cohen, 13.1-13.2
This guide on Logit and Probit models was perfected over years and years http://pj.freefaculty.
org/guides/stat/Regression-Categorical/LogitProbit/LogitProbit-1-guide.pdf. The lecture
slideshow is not quite so well evolved...
Lecture: /stat/Regression-Categorical/LogitProbit 1 http://pj.freefaculty.org/guides/stat/Regression-Categ
LogitProbit/LogitProbit-1-lecture.pdf
29. Logit II
Read: Same
Lecture: /stat/Regression-Categorical/LogitProbit-WorkedExample
30. Last Day
Final Exam: Friday, May 11, 1:30-4:00pm Please Doublecheck that: http://timetable.ku.edu/~registr/
pdf/exams/spring_2012_final_exam_schedule.pdf
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