first row of questions (please use document below for the data)
1.
2.Based on the above simple regression analysis, how much should the hiring managers expect to have for Newspaper/Magazine in the following January (Month 13)? Round to two decimal places, do not include the dollar sign.
3The hiring managers want to compare three different employment sources: Newspaper/Magazine, CareerBuilder, and Monster.com. Perform simple regressions as you did above predicting allocations for month 13 for those three employment sources. Which of the following statements would be the best conclusion from your analysis?
4For ease of performing the next task, move the variable “Social Networks – Facebook, Twitter, etc” to column A on the spreadsheet. (i.e. Make sure it is the first column in the spreadsheet.)
The hiring managers recognize that the funding for one employment source depends on the funding for the other sources. Therefore, they want you to perform a multiple regression predicting Social Network funding from Months 1-12, while controlling for the funding of Billboard, Careerbuilder, Company Intranet – Partner, and Diversity Job Fair.
Assume that we know the funding for the the controlled variables for Month 13. They are:
Billboard: 520
Careerbuilder: 800
Company Intranet: 0
Diversity Job Fair: 1000
For this model and these known values, what is the predicted value for Social Network funding for Month 13?
5.Compare the performance of the model above with a model that just controls for the funding of Billboard. In other words, create a multiple regression predicting Social Network funding from Months 1-12, while controlling for the funding of Billboard. Compare the Regression Statistics. Which model does a better job of explaining the variance in Social Network funding?
second row
1
xi | yi |
1 | 3 |
2 | 7 |
3 | 5 |
4 | 11 |
5 | 14 |
Which of the following is a scatter diagrams accurately represents the data above?
2Find the slope (b1) for the regression equation for the following values. Round to 3 decimal places.
xi | yi |
---|---|
33 | 180 |
25 |
170 |
50 | 200 |
65 | 155 |
57 | 160 |
27 | 165 |
3Try to approximate the relationship between x and y by drawing a straight line through the data. Which of the following is a scatter diagrams accurately represents the data?
4Find the intercept (b0) for the regression equation for the following values. Round to 3 decimal places.
Attention: The numbers may be different from the previous question.
xi | yi |
---|---|
33 | 180 |
25 |
170 |
50 | 200 |
65 | 192 |
57 | 160 |
27 | 165 |
5Flight bookings on the Orbitz travel site fluctuate throughout the year. In the month of December, the Orbitz team knows that bookings increase throughout the month. The team is trying to predict number of bookings in a given day throughout the month. They have sampled data from a few dates out of last December and would like to predict the upcoming December bookings. The data are below.
In this scenario’s regression equation, x is __________.
Dates in December | Bookings in the thousands |
---|---|
1 | 3 |
4 |
7 |
7 | 4 |
10 | 5 |
13 | 6 |
16 | 5 |
19 | 8 |
22 | 10 |
25 | 13 |
27 | 14 |
30 | 16 |
6Flight bookings on the Orbitz travel site fluctuate throughout the year. In the month of December, the Orbitz team knows that bookings increase throughout the month. The team is trying to predict number of bookings in a given day throughout the month. They have sampled data from a few dates out of last December and would like to predict the upcoming December bookings. The data are below.
Dates in December | Bookings in the thousands |
---|---|
1 | 3 |
4 |
7 |
7 | 4 |
10 | 5 |
13 | 6 |
16 | 5 |
19 | 8 |
22 | 10 |
25 | 13 |
27 | 14 |
30 | 16 |
If the intercept for the above data is 1.82 and the slope is 0.41, what is the complete regression equation?
7A casino is interested in the relationship between the amount of alcohol people buy and the amount of money they spend at the slot machines. They have sampled 10 people and measured the amount of alcohol they drank and how much they spend that day. Based on the regression line, they would like to predict how much money people will spend based on the amount that they drink. The data are below.
Ounces purchased | Dollars spent on slots |
---|---|
.5 | 35 |
1 |
64 |
2 | 100 |
1 | 73 |
2.5 | 110 |
3 | 150 |
1.5 | 130 |
5 | 300 |
3 | 130 |
2.5 | 105 |
If the regression line is:
y = 50.87x + 7.78,
How much money do we predict that a person who drinks 2.94 ounces of alcohol spends? Round to 2 decimal places. Do not put a dollar sign in your answer.
8An apartment management company wants to explore the consequences of allowing residents to have multiple dogs. They would like to find out whether the number of dogs predicts resident ratings. They would also like to control for the year the apartment complex was built because they know that might also affect the resident rating. They have collected data on several of their existing complexes. For each complex, they have counted the number of dogs currently living in the complex, the year the complex was built, and the average rating for that particular complex. They would like to perform a multiple regression on these variables to predict resident ratings. See data below:
Number of dogs | Year of facility | Rating (out of 5) |
---|---|---|
54 | 1975 | 2 |
31 |
1964 | 3.5 |
0 | 2015 | 4.8 |
11 | 2011 | 3.8 |
73 | 1964 | 2.3 |
23 | 2016 | 3.7 |
0 | 2015 | 4.7 |
49 | 1989 | 2.7 |
In this scenario, the y (dependent variable) is:
9An apartment management company wants to explore the consequences of allowing residents to have multiple dogs. They would like to find out whether the number of dogs predicts resident ratings. They would also like to control for the year the apartment complex was built because thaty might also affect the resident rating. They have collected data on several of their existing complexes. For each complex, they have counted the number of dogs currently living in the complex, the year the complex was built, and the average rating for that particular complex. They would like to perform a multiple regression on these variables to predict resident ratings. See data below. These data are the same as the previous question.
Number of dogs | Year of facility | Rating (out of 5) |
---|---|---|
54 | 1975 | 2 |
31 |
1964 | 3.5 |
0 | 2015 | 4.8 |
11 | 2011 | 3.8 |
73 | 1964 | 2.3 |
23 | 2016 | 3.7 |
0 | 2015 | 4.7 |
49 | 1989 | 2.7 |
What is the b coefficient for Number of Dogs? Round to 3 decimal places.
10An apartment management company wants to explore the consequences of allowing residents to have multiple dogs. They would like to find out whether the number of dogs predicts resident ratings. They would also like to control for the year the apartment complex was built because that might also affect the resident rating. They have collected data on several of their existing complexes. For each complex, they have counted the number of dogs currently living in the complex, the year the complex was built, and the average rating for that particular complex. They would like to perform a multiple regression on these variables to predict resident ratings. See data below. These data are the same as the previous question.
Number of dogs | Year of facility | Rating (out of 5) |
---|---|---|
54 | 1975 | 2 |
31 |
1964 | 3.5 |
0 | 2015 | 4.8 |
11 | 2011 | 3.8 |
73 | 1964 | 2.3 |
23 | 2016 | 3.7 |
0 | 2015 | 4.7 |
49 | 1989 | 2.7 |
What is the p-value for Number of Dogs? Round to 3 decimal places.
11An apartment management company wants to explore the consequences of allowing residents to have multiple dogs. They would like to find out whether the number of dogs predicts resident ratings. They would also like to control for the year the apartment complex was built because thaty might also affect the resident rating. They have collected data on several of their existing complexes. For each complex, they have counted the number of dogs currently living in the complex, the year the complex was built, and the average rating for that particular complex. They would like to perform a multiple regression on these variables to predict resident ratings. See data below. These data are the same as the previous question.
Number of dogs | Year of facility | Rating (out of 5) |
---|---|---|
54 | 1975 | 2 |
31 |
1964 | 3.5 |
0 | 2015 | 4.8 |
11 | 2011 | 3.8 |
73 | 1964 | 2.3 |
23 | 2016 | 3.7 |
0 | 2015 | 4.7 |
49 | 1989 | 2.7 |
Fill in the blanks using the dropdown menus.
The effect of Number of Dogs has a p-value [ Select ] [“more than”, “equal to”, “less than”] .05, which means it is [ Select ] [“significant”, “not significant”] . It is [ Select ] [“likely”, “unlikely”] that the effect of Number of Dogs on Resident Ratings is due to chance (i.e. not a real effect).
The effect of Year of Facility has a p-value [ Select ] [“less than”, “equal to”, “more than”] .05, which means it is [ Select ] [“not significant”, “significant”] . It is [ Select ] [“unlikely”, “likely”] that the effect of Year of Facility on Resident Ratings is due to chance (i.e. not a real effect).
12An apartment management company wants to explore the consequences of allowing residents to have multiple dogs. They would like to find out whether the number of dogs predicts resident ratings. They would also like to control for the year the apartment complex was built because that might also affect the resident rating. They have collected data on several of their existing complexes. For each complex, they have counted the number of dogs currently living in the complex, the year the complex was built, and the average rating for that particular complex. They would like to perform a multiple regression on these variables to predict resident ratings. See data below. These data are the same as the previous question.
Number of dogs | Year of facility | Rating (out of 5) |
---|---|---|
54 | 1975 | 2 |
31 |
1964 | 3.5 |
0 | 2015 | 4.8 |
11 | 2011 | 3.8 |
73 | 1964 | 2.3 |
23 | 2016 | 3.7 |
0 | 2015 | 4.7 |
49 | 1989 | 2.7 |
What is the R Square value for this model? Round to 3 decimal places.
13. An apartment management company wants to explore the consequences of allowing residents to have multiple dogs. They would like to find out whether the number of dogs predicts resident ratings. They would also like to control for the year the apartment complex was built because that might also affect the resident rating. They have collected data on several of their existing complexes. For each complex, they have counted the number of dogs currently living in the complex, the year the complex was built, and the average rating for that particular complex. They would like to perform a multiple regression on these variables to predict resident ratings. See data below. These data are the same as the previous question.
Number of dogs | Year of facility | Rating (out of 5) |
---|---|---|
54 | 1975 | 2 |
31 |
1964 | 3.5 |
0 | 2015 | 4.8 |
11 | 2011 | 3.8 |
73 | 1964 | 2.3 |
23 | 2016 | 3.7 |
0 | 2015 | 4.7 |
49 | 1989 | 2.7 |
What can we conclude about this multiple regression analysis? Fill in the blanks.
There is a [ Select ] [“negative”, “positive”] effect of Number of Dogs on Resident Ratings. There is a [ Select ] [“positive”, “negative”] effect of Year of Facility on Resident Ratings. As Number of Dogs increases, Resident Ratings [ Select ] [“decrease”, “stay the same”, “increase”] . Therefore, we recommend that the management [ Select ] [“does not make any changes to dog limits”, “allows more dogs”, “allows fewer dogs”] in their future complexes.