BUS 735: Business Decision Making & Research

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 2
Due on Friday, December 15, at 9:00 PM to the D2L Dropbox folder

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

Module 10: Decision Analysis

Class Notes

Slides:

Reading

Taylor, Chapter 12, pp. 547-559; 575-577

Exercises

In-class Exercise

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

Class Notes

Slides:

R tutorials:

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

Class Notes

Slides:

R tutorials:

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

Class Notes

Slides:

R tutorials:

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

Class Notes

Slides, Printer Friendly

R tutorials:

Reading

Comparing Means:
FMF, Ch 9, pp. 368-397

Exercises

In-class Exercise: Bivariate Stats
Data set: electricity.RData

Homework: Bivariate Stats
Data set: facebook.RData
Due Wed, Sept 20, to D2L Dropbox

Answers to Homework

Module 1: Introduction to Statistics

Class Notes

Reading

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

Exercises

Online tutorial for first-time R user: https://tryr.codeschool.com/

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.