Individual R Assignment #10:
#1) Download data, simple regression house.xlsx from Bb and save it as house.csv in our class folder.
We like to predict housing price in thousand $ (dependent variable) based on the number of square foot
(independent variable) with 0.05 alpha.
Do the followings:
a) For this regression model, do the validity checks. Need to provide plot. Explain whether it is
valid. If it is valid, then do (b) to (h).
b) Write down the sample regression line.
c) Interpret the slope of the number of square feet.
d) Is number of square feet statistically important variable?
e) Forecast mean housing price when # of square foot = 1800 with 95% confidence
f) Forecast housing price when # of square foot = 1800 with 95% confidence
g) Talk about the predictive ability of this regression model
h) Talk about the descriptive ability of this regression model
Note:
• For any statistical test, provide H0 and H1, conclusion with p-value, and implication
#2) #2) Download data, simple regression movie.xlsx from Bb and save it as movie.csv in our class folder.
We like to predict Gross revenue ( in million dollars) based on the amounts of DVD revenue (in million
dollars) with 0.05 alpha.
Do the followings:
a) For this regression model, do the validity checks. Need to provide plot. Explain whether it is
valid. If it is valid, then do (b) to (h).
b) Write down the sample regression line.
c) Interpret the slope of the DVD revenue.
d) Is DVD revenue statistically important variable?
e) Forecast mean Gross revenue when DVD revenue = 22 million with 95% confidence
f) Forecast Gross revenue when DVD revenue = 22 million with 95% confidence
g) Talk about the predictive ability of this regression model
h) Talk about the descriptive ability of this regression model
Note:
• For any statistical test, provide H0 and H1, conclusion with p-value, and implication.
• If the regression for both questions are not valid, please do the rest of questions for #1 in order for you to exercise the regression.