Project Information

Annotated Bibliography due November 1, 2017
Description of six (6) sources

R Tutorial: Tips for working with IPUMS data in R

Exams

Take Home Exam 1
Due on Wednesday, October 18, at 5:30 PM to the D2L Dropbox folder

Module 9: Transportation & Assignment Models

Class Notes

Slides:

Reading

  • Transportation models: Taylor Ch 6, pp. 237-244
  • Assignment models: Taylor Ch 6, pp. 251-253

Exercises

Homework Taylor End of Chapter 6 Problems 26, 32, 37

Module 8: Linear Programming

Class Notes

Slides:

Reading

  • Graphical Solution: Taylor, Ch 2, pp. 31-45, 48-53
  • Computer Solution: Taylor, Ch 3, pp. 74-77
  • Sensitivity Analysis: Taylor, Ch 3, pp. 82-93
  • Example: Taylor, Ch 3, pp. 93-95
  • More Examples: Taylor, Ch 4, pp. 114-127

Exercises

Homework Taylor End of Chapter 3 Problems 13, 22, 23, 24a,b.

Module 7: Analysis of Variance

Reading

  • One-way ANOVA: FMF, Ch 10, pp 399-414, 447-449
  • Multiway ANOVA: FMF, Ch 12, pp 501-511, 520-530
  • Kruskal Wallis test: FMF, Ch 15, pp 674-686

Exercises

Exercise: ANOVA
Data set: jobsat.RData

Module 6: Binary Variables in Regression

Class Notes

Slides: R tutorials:

Reading

  • Logistic regression: FMF, Ch. 8

Exercises

Exercise: Logit
Data set: jobsat.RData

Module 5: Multiple Regression

Reading

  • Multiple regression: FMF, Ch. 7, pp. 261-263(top), 276-284
  • Assumptions: FMF, Ch. 7, pp. 271-273(top)

Exercises

In-class Exercise: Regression
Wed Oct 18

Homework: Regression
Due on Wed Oct 25

Module 4: Bivariate Relationships

Reading

  • Correlation: FMF, Ch. 6, pp. 205-212 (skim math); 219-225
  • Chi-square test of independence, FMF Ch. 18, pp. 815-816(top)
  • Bivariate regression: FMF, Ch. 7, pp. 245-253, 256-260

Exercises

No Homework Due for Oct 11

Worksheet: Correlation and Regression
For exam practice, be able to do problems 1, 2, 3, and 4(a)

For regression exam practice: Know how to interpret the meaning of coefficients in regression; conduct hypothesis tests on the regression coefficients.

Module 3: Visualizing Means

Class Notes

R tutorials:

Reading

R for Data Science
by Hadley Wickham and
Garrett Grolemund
Chapter 3

Exercises

Module 2: Univariate and Bivariate Statistics

Module 1: Introduction to Statistics

Reading

  • Intro to statistics:
    FMF Ch 2 - All of it, but skim the math
  • R environment: FMF Ch 3, pp. 62-83

Exercises

R Resources

Installing R

  • Rstudio is a great Integrated Development Environment (IDE). This is the graphical user interface that you use to interact with R, which is actually a separate software package than the R computing package.
  • R is a language and environment for statistical computing and graphics. You can learn more about it and when you are ready, download R to install to your Windows, Linux, or Mac computer.

Online Tutorial

Instructor

James Murray, Ph.D.

  403T Wimberly Hall
  608-785-5140
    608-406-4068
  jmurray@uwlax.edu

Office Hours Appointments

Office hours appointments are available with only a one-hour notice, and are generally available at the following times:

  • 8:30 AM - 11:00 AM Monday through Thursday
  • 1:00 PM - 2:30 PM Monday and Wednesday
  • 10:00 AM - 11:30 AM Friday
  Make office hours appointment