IES 612 - Environmental Analysis and Modeling
STA 473/573 - Applied Multiple Regression
STA 476/576 - Experimental Design

Spring 2009

Meeting Times: 800- 850 MT RF
Meeting Location: 201 Bachelor Hall  

Prerequisites: basic course in statistics (e.g. STA 671); willingness to work hard and ask questions when confused; desire to understand more about how statistical models are used to analyze experimental and observational studies.
Instructor: Dr. John Bailer
E-mail address: baileraj@muohio.edu
URL: http://www.users.muohio.edu/baileraj
Office (phone):

292 Bachelor (9-3538) *

Office Hours (locations):

* 900-1000 Monday, Tuesday, Thursday, Friday

(in 292 BAC or 106 BAC [M F reserved for 1 h])

(other times by appointment - don't be shy!)

Teaching Assistant/Grader TBA

Purpose of Course:
  1. Introduce regression models and accompanying assumptions. (STA 473/573) - 1/13 through 2/13
  2. Introduce experimental designs and their associated analyses. (STA 476/576) - 2/15 through 3/27
  3. Introduce methods of probability sampling.
  4. Introduce stochastic simulation and mathematical models
Course Objectives:
  1. Identify and correctly analyze various regression models and experimental designs using SAS.
  2. Develop a sense for the most appropriate sampling method for addressing a particular problem.
  3. Develop a sense for what issues are important in the construction and validation of mathematical models.

Texts:
regression and experimental design (OL) Ott, R.L. and Longnecker, M. (2001) Statistical Methods and Data Analysis, 5th Ed., Pacific Grove, CA,  Duxbury.
sampling Course notes - based in part on sampling chapter from Piegorsch, W.W. and Bailer, A.J. (2005) Analyzing Environmental Data. John Wiley & Sons: West Sussex , England (also used for reg./exp. design)
modeling

(Bkgd.) Neuwirth E and Arganbright D (2004) Mathematical Modeling with Microsoft Excel. Thomson - Brooks/Cole: Belmont, CA

Course notes - based in part on Giordano, F.R., Weir, M.D. and Fox, W.P. (2003) A First Course in Mathematical Modeling, 3rd Ed., Pacific Grove, CA,  Duxbury

Grading:           Straight 90-80-70-60 split for A,B,C,D, respect. (+/- used on boundaries)

 (for IES 612)

Item

contribution to grade

Homework

1/3

Exam 1 (following reg.)

1/3

Exam 2 (following exp. design)

1/3

 (for STA 473/576 or STA 476/576)

Item

Contribution to grade

Homeworka

1/2

Exama,b

1/2

aAdditionally, students in STA 573/576 may be required to work additional "grad-only" problems on homework or exams. 

bExam will be handed out during the last regularly scheduled class period and will be due Monday of the next week.

 Comments:            Exams will be take-home exams.  The first exam will focus on regression analysis, and the second exam will focus on experimental design.

Tentative course outline

IES 612 Part I and STA 473/573 - Regression

Week

Day

Comments

Reading

Expanded topic list

1

1/12

First day of classes - Intro.

OL 11.1

Linear regression; model; error terms

 

1/13

 

OL 11.2

Least squares; Residuals, leverage, outliers, estimating s

 

1/15

 

 

 

 

1/16

Inference

OL 11.3

b1 and b0 inference; General linear test

2

1/19

HOLIDAY, no class

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1/20

Diagnostics

 

Remedial measures; transformations

 

1/22

 

OL 11.4

Mean response and new response inference

 

1/23

 

OL 11.7

Correlation and r2

3

1/26

Multiple Reg.

OL 12.1

Intro, Model, interpretation, dummy/indicators

 

1/27

 

OL 12.2

GLM

 

1/29

 

OL 12.3,12.4

estimation, inference

 

1/30

 

 

Extra SS; collinearity; VIF

4

2/02

 

OL 12.5

Testing subsets

 

2/03

 

OL 12.6

Forecasting/prediction

 

2/05

 

OL 12.7

OL 16

Slopes of several reg. Lines (connection to ANCOVA)

 

2/06

 

OL 12.8

Logistic reg.

5

2/09

Selecting variables

OL 13.1

All possible reg.; PRESS; Cp; backward elimination; forward selection; stepwise

 

2/10

Model formulation/ assumptions

OL 13.2, 13.3, 13.4

Linearity; transformation; Plots

 

2/12

TOPICS

 

Nonlinear regression/ Logistic Regression/  time series

 

{PH] 2/13

 

 

 

End of REGRESSION

IES 612 Part II and STA 476/576 - ANOVA models and Exp. Design

6

2/16

Experimental Design

OL 8.1-8.2

One-way AOV vocab, t-test analog, F-test, SS/AOV table

 

2/17

Single factor anova models

OL 8.3

CRD

 

2/19

 

OL 8.4

AOV conditions; residual analysis

 

2/20

 

 

 

7

2/23

 

 

 

2/24

 

OL 8.5, OL 8.6

Transformation, Kruskal-Wallis

 

2/26

Multiple comparisons

OL 9.1, OL 9.2

Contrasts, SSC

 

2/27

 

OL 9.3

Error rates - individual, per comparison, Bonferroni

8 

3/02

MCA

OL 9.4, OL 9.5, OL 9.6

Fisher, Tukey, SNK

3/03

MCC+

OL 9.7, OL 9.8

 

 

3/05

Design concepts

OL 14.1-14.3

Intro, study types, vocab

 

3/06

 

 

Oneway, factorial, control, experimental unit, replication

9

3/09

SPRING BREAK

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3/10

SPRING BREAK

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3/12

SPRING BREAK

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3/13

SPRING BREAK

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 10

[PH] 3/16

 

OL 14.5-14.6

Randomization, Replication (study size)

[PH] 3/17

AOV for standard designs

OL 15.1-15.7

Oneway CRD

 

3/19

 

 

RCBD, LS?, Factorial treatment in CRD and RCBD

 

3/20

 Topics

 OL 17/18

 Fixed/random effects, repeated measures

11

3/23

 

 

 

 

3/24

 

 

 

 

3/26

 

 

 

 

3/27

 

 

 

End of EXPERIMENTAL DESIGN

IES 612 Part III - Sampling & Stochastic Simulation and Math Modeling

 

12

3/30

Sampling -

Course notes

SRS

 

3/31

 

 

 

 

4/02

 

 

Stratified RS, Cluster Sampling

 

4/03

 

 

 

13

4/06

 

 

Systematic samples

 

4/07

 

 

 

 

4/09

 

 

Estimating Wildlife Population Size

 

4/10

 

 

 

14

4/13

 Modeling

Course notes

Vocabulary; model/variable types

 

4/14

 

 

 

 

4/16

 

 

 

 

4/17

 

 

 

15

4/20

Monte Carlo models

Course notes

 

 

4/21

 

 

 

 

4/23

 

 

 

 

4/24

Deterministic models

Course notes

 

16

4/27

 

 

 

 

4/28

 

 

 

 

4/30

 

 

 

 

5/01

Last Day of Class

 

 

 

 

Other dates of potential interest (use as a rough guide - make sure you check dates independently!)

Jan. 12

classes begin

Jan. 16

 

X Sprint Class- Last day to drop course without a grade

X Sprint Class- Credit/ no credit deadline

Jan. 19

NO CLASSES - Martin Luther King Day

Jan. 30

  Feb. 2

X Sprint - Last day to change to/from audit or to withdraw with "W"

IES 612 - credit/no credit deadline AND last day to drop without grade

Feb. 13

X Sprint Class - Last day of classes

 Regression exam distributed (TENTATIVE)

Feb. 16

Y Sprint Class- Beginning of class

Feb. 20

Y Sprint Class - Last day to drop course without grade

Y Sprint Class - Credit/No credit deadline

Mar. 6

 

Y Sprint Class- Last day to drop course with Grade of W

Y Sprint Class - Last day to change course to audit

Mar 26

IES 612 - LAST DAY TO DROP WITH "W" - after this date, you are in for the duration!
Mar. 27

Y Sprint Class - Last day of classes

 Exp. Design exam distributed (TENTATIVE)