Developing Data Products - Project

This presentation explains the app created to respond the following question:

1. Is an automatic or manual transmission better for MPG?

The data used is the data set mtcars, provided in datasets package.

Link for GitHub repository containing all codes:

https://github.com/andmorato/Developing_data_products_project

The “mtcars” data set was extracted from the 1974 Motor Trend US magazine. It comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models).

The data is formated in a data frame with 32 observations on 11 variables, as follows:

[, 1] - mpg - Miles/(US) gallon; [, 2] - **cyl* - Number of cylinders;* [, 3] - disp - Displacement (cu.in.); [, 4] - **hp* - Gross horsepower;* [, 5] - drat - Rear axle ratio; [, 6] - **wt* - Weight (1000 lbs);* [, 7] - qsec - ¼ mile time; [, 8] - **vs* - V/S;* [, 9] - am - Transmission (0 = automatic, 1 = manual); [,10] - **gear* - Number of forward gears;* [,11] - carb - Number of carburetors

The interactive app fit a linear model with predictors set by the user. The milleage per gallon is the response predicted by the other variables selected, the predictors.

If no predictor is selected, the fitted model will have only the transmission as predictor.

Below, the fitted milleage per gallon with only one predictor, the transmission (reduce zoom to plot appear in screen):

data("mtcars"); fit<-lm(mpg ~ am, data=mtcars)
with(mtcars, plot(am, mpg,xlab="Transmission[0 = automatic - 1 = manual]", ylab="Milleage per gallon"))
abline(fit, col = "red")

The app evaluate the following:

1. The expected influence of transmission in fuel consumption. How much bigger is the milleage per gallon of manual cars comparing to automatic cars.

2. The 95% confidence interval of value given above.

3. The result of a hipothesis test that evaluate the influence of transmission in fuel consumption.

4. A plot of residuals of predicted milleage per gallon.