# STAT 302 Elementary Statistical Methods II

### R and R Studio

### VMware Horizon

VMware Horizon is a “virtual desktop” which you can use to run R.

### Tutorial 1

- downloading and installing R and R Studio
- first look at R Studio
- basic R
- dataframes (1 of 2)
- dataframes (2 of 2)
- downloading mystatlab datasets into R Studio for analysis

### Tutorial 2

### Tutorial 3

- histograms and stem and leaf plots
- summary statistics and (two types of) IQR
- 5-number summary and boxplot
- time series and transformed data

### Tutorial 4

### Tutorial 5

### Tutorial 6

- groups (categories) and linear regression
- autocorrelation and durbin-watson statistic
- re-expressing (transformating) data

### Tutorial 7

### Tutorial 8

- multiple linear regression two parallel (additive) predictors
- multiple linear regression two interacting predictors
- unusual points: studentized residuals, leverage and cook’s distance
- multicollinearity measured by VIF (variance inflation factor)
- building multiple linear regression models: exhaustive method
- building multiple linear regression models: stepwise method
- quadratic regression model

### Tutorial 9

- multiple linear regression two parallel (additive) predictors
- multiple linear regression two interacting predictors
- unusual points: studentized residuals, leverage and cook’s distance
- multicollinearity measured by VIF (variance inflation factor)
- building multiple linear regression models: exhaustive method
- building multiple linear regression models: stepwise method
- quadratic regression model

### Tutorial 10

- one-way analysis of variance (ANOVA) and Bonferroni comparison of multiple means
- two-way ANOVA and interaction plots

### Tutorial 11

### Tutorial 12

- in/dependent two center location tests: Wilcoxon rank-sum/signed rank tests
- in/dependent multiple center location tests: Kruskal-Wallace and Friedman tests
- association: Spearman’s correlation and Kendall’s tau

### Tutorial 13

- minimax and expected value (EV) minimax
- expected value of perfect information
- expected value of sample information
- risk: standard deviation (SD), coefficient of variation (CV), return to risk ratio (RRR)

### Tutorial 14

As explained by G. Jay Kerns, “Perhaps the most important part of a statistician’s job once the analysis is complete is to communicate the results to others. This is usually done with some type of report that is delivered to the client, manager, or administrator. Other situations that call for reports include term papers, final projects, thesis work, etc.”

For each case study, write and submit an (at most, otherwise it will not be accepted) 3-page report on any of the given data sets listed for each case study or from a data set you provide which has been approved by me.

Your case study report MUST contain the following items:

1. Title (on title page) (5 points, 10%)

2. Abstract (on title page) (5 points, 10%)

3. Background and Significance (part of 3 pages) (5 points, 10%)

4. Methods (part of 3 pages) (10 points, 20%)

5. Results (part of 3 pages) (10 points, 20%)

6. Discussion/Conclusions (part of 3 pages) (10 points, 20%)

7. References (not included in the 3 page limit) (5 points, 10%)

Detailed explanation of these items are given in greater detail at https://www.causeweb.org/usproc/Report%20Template

Award winning examples of these types of reports are given at https://www.causeweb.org/usproc/usclap/2016/winners

You MUST include a statistical analysis using R otherwise the report will not be accepted: R output and R script must appear in your report but it may appear in the (optional) appendix of your report. R plots and graphs can be copied into Microsoft Word: after creating a plot in R Studio, go to the plot panel, click on Export, then copy to clipboard, then paste in Word. R script and numerical output can be highlighted in either the Source or Console panels of R Studio, then left-click for copy out of R Studio, then left-click paste into Word. copy from R-paste into Word

All data sets suggested for the case studies are available at http://media.pearsoncmg.com/aw/aw_sharpe_business_3/datasets/sbs3e_datasets_text.html

Please be forewarned I will be checking for plagiarism, any student caught plagiarizing will receive zero for their report.

A tutorial video on how to submit your case study paper online through blackboard is given here. This tutorial also tells you how to check if your case study paper successfully submitted and also how to look at your graded paper.