# COMMunicationRESearch.NET

### Site Tools

c:ma:2019:multiple_regression_exercise

# Class Activities

## Ex. 1

• Install packages ISLR
• use a dataset, Carseats
• Build regression models with a DV, sales and IVs, your choices
• Use ?Carseats command for the explanation of the dataset
• Use str function to see the characteristic of each variable. Make it sure that SelvesLoc variable should be factor, not int or anything.
• 변인설명을 토대로 가설만들기
• 종속변인 = Sales
• 독립변인 = 숫자변인 1 + 종류변인 1 (조별 선택)
• Multiple regression without interactin
• Multiple regression with interaction
• 가설 만들기
• 종속변인 Sales
• 독립변인 여러개 (interaction 없이)
• Modeling 해 볼 것

see hierarchical regression

• Make a full model (with all variables) then reduce down the model until you find it fitted.
• Make a null model (with no variables) then, build up the model with additional IVs until you find a fitted model.
• Can we use step or stepAIC (MASS package needed) function?
• Interpret the result

> step(lm.full, direction=“back”)

## Ex. 2

• Install packages tidyverse
• install.packages("car")
• install.packages("carData")
• load the car and the carData
• data("Salaries", package = "carData")
• ?Salaries
• explain what it is
• describe the data set

—-

• Regress sex variable on salary variable
• Write the regression model
• Discuss the difference male and female (sex)
• Use rank variable for the same purpose
• Write the regression model
• Regress rank + sex on salary
• How do you interpret the result?
• And regress rank + sex + rank:sex on salary
• How do you interpret this result?
• Do factorial ANOVA test with rank and sex on salary
• How do you interpret the result?
• Test regression model of your own choice
• Interpret the result

위의 Salaries 데이터사용이 안 될 때

• use to import the data set. Salaries <- read.csv("http://commres.net/wiki/_media/salaries.csv")
• use ??Salaries to describe the data set.

—–
Please copy and paste the proper r command and output to a txt file (use notepad or some other text editing program). You could use MS Word, but, please make it sure that you use type-setting fonts such as “Courier New.” The below output, as an example, includes the r command head(Salaries) and the output.
<code>

# Discussion

Common topics

• What affects students GPA? Or what determines students' GPA?

Group topics

# Making Questionnaire

Questions you submit at the ajoubb.