Using the data set CarPrice, carry out the following question:

a. Construct a table that show the sample mean, standard deviation, and minimum and maximum values for each variable.

b. Construct a table that show the correlation coefficient of each two variable listed and selected 3 as the regressor.

c. Selected 3 variables as the regressor and explain the reason for your choice.

d. Run a regression of Price on 3 selected independent variables.

e. Write down your regression function and interpret the value of this coefficient.

f. Evaluate the fitness of your regression model(tips: R square, Adjusted R square, SER, residual plot)

please show answers by excel
 

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Car ID. wheelbase carlength carwidth carheight curbweight enginesize boreratio stroke compressionratio horsepower peakrpm citympg highwaympg price(Dependent variable) DATA DICTONARY Unique id of each observation (Interger) Weelbase of car (Numeric) Length of car (Numeric) Width of car (Numeric) height of car (Numeric) The weight of a car without occupants or baggage. (Numeric) Size of car (Numeric) Boreratio of car (Numeric) Stroke or volume inside the engine (Numeric) compression ratio of car (Numeric) Horsepower (Numeric) car peak rpm (Numeric) Mileage in city (Numeric) Mileage on highway (Numeric) Price of car (Numeric) **Source: https://archive.ics.uci.edu/ml/datasets/Automobile.