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Note : I prefer to use R software and when you write the results, interpret thes

ID: 3064657 • Letter: N

Question

Note : I prefer to use R software and when you write the results, interpret these results to make them easier to understand An oil company has been promoting a motor oil that is supposed to increase gas mileage. In addition, the company also says the new oil is specially formulated for smaller engines. An independent research company conducts an experiment to test this claim. They employ 15 identical cars with six cylinder engines, and 15 identical cars with four cylinder engines. They will use three different types of oil Five cars of each engine type are randomly assigned to each of the three types: a standard single weight oil (STANDARD), a multiweight oil (MULTI), and the new oil (GASMISER). The data are given below. They want to compare the mean gas mileage of the new oil to each of the other two types, and they also want to compare the mean gas mileage between four and six cylinder cars using the new oil (thus, these are preplanned comparisons) Motor oil Multil Gasmis 23.6 23.5 21.4 21.7 22.8 20.7 Enginel6 cylinder 20.3 24.6 20.5 21.0 24.6 23.2 22.0 225 21.3 22.6 23.7 26.0 24.5 24.6 25.0 cylinder 23.25.026.9 25.3 24.026.0 22.1 23.1 25.4 The question is Perform the means comparisons of interest, and summarize the results. Also justify your choice of multiple comparison procedure. Assume important interaction exists.

Explanation / Answer

RCODE

## loading the data from text file
dataset_chegg<-read.csv("chegg.csv")
#converting into categorical variables
dataset_chegg$Engine <-as.factor(dataset_chegg$Engine)
dataset_chegg$Motor.oil <-as.factor(dataset_chegg$Motor.oil)
summary(dataset_chegg)


## Running one way ANOVA test
results <- aov(dataset_chegg$Milage~dataset_chegg$Engine*dataset_chegg$Motor.oil, data=dataset_chegg)
summary(results)

ROUTPUT:

summary(results)
Df Sum Sq Mean Sq F value Pr(>F)   
dataset_chegg$Engine 1 37.63 37.63 34.705 4.46e-06 ***
dataset_chegg$Motor.oil 2 8.56 4.28 3.948 0.032929 *  
dataset_chegg$Engine:dataset_chegg$Motor.oil 2 20.33 10.16 9.374 0.000981 ***
Residuals 24 26.02 1.08
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

P- values of blocks are <0.05. So milage is significantly different among

1) Engine

2) Motor oil

3) interaction effect is also significant.

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