https://www.stuvia.com/user/nursecare
ISYE 6501 Homework 5 2026 Solutions & Answers (Verified, A+ Grade)
Problem 8.1
ALL NEEDED TO PASS IS HERE
One of the current problems in my life is if I want to sell my car. I currently drive a 2011
Honda
Accord and would like to get a new car. I look online on Carvana, Craigslist, Kelly Blue
Book,
and other websites to see what’s a fair asking price to trade my car for. I can use a linear
regression model to take my car’s characteristics and estimate the resale value. Some
Mileage of the car – higher mileage will lower the car’s value
predictors
for thisAccident
problem history
are: – any accident will decrease the value of the car
Age of the car – the older the car, the less value of the car
Number of previous owners – fewer owners can increase the price
Brand/model of the car – Honda is a reliable and durable brand, so they tend
to hold
value
Problem 8.2
Methodology and Analysis
I loaded the data set and assigned it to “crime.” I created a lm model named
“model_crime with
all the predictors in it that we will use in helping to predict other models later. Then I
used the
summary() function to get the summary of model_crime.
Looking at the results of the summary() function, we see there are some significant
coefficients
that are important in the data set. These coefficients are M, Ed, Po1, U2, Ineq, Prob.
Additionally,
I use the range function to find the min and max values of the Crime column in the original
data
https://www.stuvia.com/user/nursecare
,https://www.stuvia.com/user/nursecare
set. The min was 342 and max was 1993. This model predicts the crime is 155.4349.
This is
below the minimum value so there is some overfitting.
Next, I created another lm model named “model_crime2,” which had the coefficients
with
symbols next to them. I used the summary() function to get the summary of this
model.
This model predicts crime will be 1304.245 which falls in between the min and max
range. This
model also has a higher adjusted R-Squared and lower residual standard error than the
previous
Imodel
also made
whicha makes
qq plotthis
for more
the Crime column
accurate fit tofrom the original data set to see if it is
the data.
a good
predictor.
https://www.stuvia.com/user/nursecare
ISYE 6501 Homework 5 2026 Solutions & Answers (Verified, A+ Grade)
Problem 8.1
ALL NEEDED TO PASS IS HERE
One of the current problems in my life is if I want to sell my car. I currently drive a 2011
Honda
Accord and would like to get a new car. I look online on Carvana, Craigslist, Kelly Blue
Book,
and other websites to see what’s a fair asking price to trade my car for. I can use a linear
regression model to take my car’s characteristics and estimate the resale value. Some
Mileage of the car – higher mileage will lower the car’s value
predictors
for thisAccident
problem history
are: – any accident will decrease the value of the car
Age of the car – the older the car, the less value of the car
Number of previous owners – fewer owners can increase the price
Brand/model of the car – Honda is a reliable and durable brand, so they tend
to hold
value
Problem 8.2
Methodology and Analysis
I loaded the data set and assigned it to “crime.” I created a lm model named
“model_crime with
all the predictors in it that we will use in helping to predict other models later. Then I
used the
summary() function to get the summary of model_crime.
Looking at the results of the summary() function, we see there are some significant
coefficients
that are important in the data set. These coefficients are M, Ed, Po1, U2, Ineq, Prob.
Additionally,
I use the range function to find the min and max values of the Crime column in the original
data
https://www.stuvia.com/user/nursecare
,https://www.stuvia.com/user/nursecare
set. The min was 342 and max was 1993. This model predicts the crime is 155.4349.
This is
below the minimum value so there is some overfitting.
Next, I created another lm model named “model_crime2,” which had the coefficients
with
symbols next to them. I used the summary() function to get the summary of this
model.
This model predicts crime will be 1304.245 which falls in between the min and max
range. This
model also has a higher adjusted R-Squared and lower residual standard error than the
previous
Imodel
also made
whicha makes
qq plotthis
for more
the Crime column
accurate fit tofrom the original data set to see if it is
the data.
a good
predictor.
https://www.stuvia.com/user/nursecare
