You will need to write a simple R script to execute the following data preprocessing and statistical analysis. Where required show analytical output and interpretations.

Please use rio, car, moments packages, not tydiverse. Preprocessing 1. Please Load the file "6304 Module 8 Assignment Data.xlsx" into R. This file contains information on 46,484 vehicles listed for sale on Craig's List in the United States. This will be your master data set. 2. Create a single data frame for your analysis which will be your primary data set. The primary data set should have the following characteristics: a. Only includes cars from the regions of vermont, appleton, green bay, indianapolis, and worcester. b. Only includes cars with 4, 6, or 8 cylinder engines. c. Includes all variables appearing in the master (N=46,484) data set. d. Be a random sample of n=50 cars from each of the five regions listed above. This is referred to as a stratified sample. (Remember to use the numerical portion of your U number as the random number seed.) Analysis 1. Within your n=250 stratified sample, determine if asking.price has an equal variance across the five regions. Briefly interpret your results 2. Conduct a one-way analysis of variance on your sample data with asking.price as the dependent variable and region as the independent variable. Plot the results of a Tukey HSD test to show whether/where differences in asking.price among the regions exist. Briefly explain the results shown in the plot, stating which pairs of regions do and do not appear to show significant mean differences in asking.price. Make sure region names can be clearly and completely read on the appropriate axis of your plot. 3. Repeat Steps 1 and 2 above using the odometer as the dependent variable and region as the independent. Again, briefly explain your analysis results and make sure region names can be clearly and completely read on the appropriate axis of your plot. 4. Referring to Steps 1 and 2 again, conduct a one-way analysis of variance using asking.price as the dependent variable and cylinders as the independent. Show model output and explain your results as you did in Step 3. Your deliverable will be a single MS-Word file created using R Markdown. Your file will show 1) the R script which executes the above instructions and 2) the results of those instructions. Your code and analysis results should be presented in order listed above.

Here is the link below:

https://docs.google.com/spreadsheets/d/1rJRzBK8BbRx4LvwMMv31SRnReB7kIlQBUnnkp4apNMg/edit?usp=sharing