Stat 431: Statistical Analysis

Fall 2013, University of Idaho, Section 01, CRN 36142

Instructor: Brian Dennis
Professor, Department of Statistical Science
316 Phinney, 208-885-7423,

Office hours: 1:30-3:00PM  Mon, Tues, Wed, Thur

Meeting times & places:
Lecture: MWF 9:30-10:20AM TLC 046 (not 45;  course was moved to a bigger room)

Ott, R.L. & Longnecker, M. 2010. An Introduction to Statistical Methods and Data Analysis, Sixth Edition. Brooks/Cole, Belmont, CA.


Other materials:
You should bring a scientific calculator (w/ memory, square root, logarithms) to tests.


Other resources:

Stat Assistance Center (SAC): first floor Library, 885-2929, for help with this course


Statistics Consulting Center (SCC):  Call 885-2929 for an appointment, for statistics advice concerning research or thesis

Based on 600 possible points, 90% A, 80% B, and so on

Economy data

county demographics data


Makeup tests: Makeup tests will not be given, except for legitimate scheduled university activities or grave, urgent reasons. Prior arrangements with instructor are required.

Final exam rescheduling: By Department of Statistical Science policy, no student may reschedule the final exam without permission of the Department Chair.


Outcomes:  Students successfully completing this course will be able to conduct and interpret standard statistical analyses used in research, including multiple regression, analysis of variance, analysis of covariance, analysis of categorical and other non-normal data, as well as to plan sample sizes and allocations for basic designs and surveys.

SAS documentation:

Introduction to SAS (dated, but informative for ordinary uses of SAS)

SAS online documentation

All the SAS examples you could possibly want

UCLA SAS starter kit

Introduction and documentation for PROC MIXED (pdf of now-defunct but informative website at Univ Kentucky)


The amazing, free R language for statistics, graphics, and computing



SAS examples for class:                                                                                R examples:


      summary statistics                                                                                     summary statistics

      batting average simulation                                                                        batting average simulation

      one-sample t-test example                                                                         one-sample t-test example

      two-sample t-test example                                                                        two-sample t-test example

      analysis of variance example

      two binomial proportions example

      multinomial model example

      two-way table example

      homogeneous proportions example, PROC FREQ

      homogeneous proportions example

      linear regression example

      linear regression with GPLOT graphics

      multiple regression example one

      multiple regression example two

      AOV by regression example

      nonlinear regression example

      logistic regression example

      simple random sample example

      AOV power calculation example

      randomized complete block design

      Latin square design example

      two-factor AOV example

      unbalanced AOV example

      three-factor AOV example

      analysis of covariance example

      generalized linear models examples:

            Poisson regression

            Gamma distribution

     random and mixed effects examples:

            random effects ex 1:  PROC GLM

            random effects ex 2:  PROC MIXED

            mixed effects example


MINITAB documentation:

     Intro Handbook by Minitab, Inc

     Georgetown University MINITAB intro


Course evaluations



Topics & Readings (might change!)

Aug 26


Aug 28          Ch 4


Aug 30


Sep 2

no class:

Labor Day

university closed

Sep 4
probability distributions, continued

Sep 6

Getting started with SAS

Sep 9

Getting started with R

Sep 11

sampling distributions

Sep 13          Ch 5

inferences for central values

Sep 16

inferences for central values, continued

Sep 18          Ch 6

inferences for comparing two central values

Sep 20

comparing two central values,


Sep 23          Ch 7

inferences about


Sep 25          Ch 8

1-way AOV

Sep 27

1-way AOV

Sep 30


              Test 1

Oct 2          Ch 9

multiple comparisons

Oct 4

multiple comparisons

Oct 7

inferences for non-normal models (& corresponding sections of Chapter 8)

Oct 9          Ch 10

categorical data

Oct 11

categorical data

Oct 14

categorical data

Oct 16

categorical data


Oct 18           Ch 11
linear regression

Oct 21

linear regression

Oct 23

linear regression

Oct 25


            Test 2

Oct 28          Ch 12

multiple regression

Oct 30
multiple regression



Nov 1          Ch 13

model selection

Nov 4

nonlinear regression

Nov 6

non-normal regression

Nov 8          Ch 14


design intro

Nov 11

factorial experiments

Nov 13          Ch 15

randomized complete

block design

Nov 15

Latin square


Nov 18

              Test 3

Nov 20

AOV unbalanced & 3-way

Nov 22          Ch 16

analysis of covariance


Fall Break!


Dec 2

AOV & regression

Dec 4

generalized linear models (GLIM)

Dec 6

generalized linear models (GLIM)


Dec 9

mixed effects models

Dec 11

mixed effects models

Dec 13

other topics


Final exam occurs in the scheduled final exam period, 10AM-12noon, Tuesday, Dec 17.  (No earlier reschedules will be allowed).




 Items for further interest and enjoyment


Statistics-related links and resources


Dallal’s essay on why significance level is 5%


Brian’s essay on Bayesian statistics


Aaron and Brian’s essay on statistics education for ecologists


Scientists on medical & health practices  (If it talks like a quack, and bills like a quack, it probably is a quack):


     Quack watch


     Acupuncture study


     Science based medicine


Paranormal/supernatural phenomena:


     Committee for Skeptical Inquiry


            The Last Will and Testament of Philip J. Klass

To UFOlogists who publicly criticize me…or who even think unkind thoughts about me in private,

I do hereby leave and bequeath THE UFO CURSE: No matter how long you live, you will never know

any more about UFOs than you know today. You will never know any more about what UFOs really

are, or where they come from. You will never know any more about what the U.S. Government really

knows about UFOs than you know today. As you lie on your own death-bed you will be as mystified

about UFOs as you are today. And you will remember this curse.


            — Philip J. Klass, prominent UFO skeptic, posted on a UFO discussion site shortly before his death


     Bye-Bye, Psi


Scientists on evolution, intelligent design, biblical creation:


     Talk origins


     Panda’s thumb




     Why evolution is true


     Dover trial transcripts  (read what scientists and “cdesign proponentists” say under oath)


     Department of Biological Sciences, Lehigh University


The continuing futile attacks by evolution’s opponents reminds me of another legendary confrontation,

that between Arthur and the Black Knight in the movie Monte Python and the Holy Grail.  The Black

Knight, like evolution’s challengers, continues to fight even as each of his limbs is hacked off, one by

one.  The “no transitional fossils” argument and the “designed genes” model have been cut clean off,

the courts have debunked the “ID is science” claim, and the nonsense here about the edge of evolution

is quickly sliced to pieces by well-established biochemistry.  The knights of ID may profess these blows

are “but a scratch” or “just a flesh wound,” but the argument for design has no scientific leg to stand on.


    Sean B. Carroll, in a review (2007 Science 316:1427-1428), of Michael J. Behe’s book

The Edge of Evolution:  The Search for the Limits of Darwinism.


     National Science Teachers Association


Statisticians analyze USA elections:


     Exit poll discrepancy analyses (2004 USA presidential election)


     (How the 2004 election fraud was committed:  A.  B.)


    Prima facie evidence of criminal vote-flipping with computerized voting machines


Scientists on climate change research:


     Spencer Weart’s history of global change research (plus many fine links)




LaTeX (science/math/tech typesetting) resources:


     Introduction to LaTeX


Comparing public, private, and charter schools with NAEP data:


     Lubienski study


     another Lubienski study


     AFT report


     NAEP/US Department of Education analysis


     Education "Rhee-form" makes things worse


Postmodern comedy:  which of the following articles is a (deliberate) parody?


     A.  Deconstructing the evidence-based discourse in health sciences: truth, power and fascism


     B.  Transgressing the boundaries:  towards a transformative hermeneutics of quantum gravity


               Answer is here


And of course, no statistics course website would be complete without:


     Todd Snider "Statisticians Blues"

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