***PLEASE ANSWER ALL QUESTIONS***
Question 21 (1 point)
While attempting to measure its risk exposure for the upcoming year, an insurance company notices a trend between the age of a customer and the number of claims per year. It appears that the number of claims keep going up as customers age. After performing a regression, they find that the relationship is (number of claims per year) = 2.579*(age) + 3.369. Interpret the slope.
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Question 22 (1 point)
Suppose that for a typical FedEx package delivery, the cost of
the shipment is a function of the weight of the package measured in
ounces. You want to try to predict the cost of a typical shipment
given package dimensions. If 10 packages in a city are sampled and
the regression output is given below, what can we conclude about
the slope of weight?
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21. Here regression is (number of claims per year) = 2.579*(age) + 3.369
As we know regression is of form y=slope*x+intercept
So slope value is 2.579 which means for every increase in x, there is corresponding 2.579 increase in y.
Correct answer is
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22. Here regression output is not given, so can't find answer
***PLEASE ANSWER ALL QUESTIONS*** Question 21 (1 point) While attempting to measure its risk exposure for...
A)
While attempting to measure its risk exposure for the upcoming
year, an insurance company notices a trend between the age of a
customer and the number of claims per year. It appears that the
number of claims keep going up as customers age. If 10 customers
are sampled and the regression output is given below, what can we
conclude about the slope of age?
Question 11 options:
1)
The slope significantly differs from 0.
2)
The slope is 0.003...
Suppose that for a typical FedEx package delivery, the cost of
the shipment is a function of the weight of the package measured in
ounces. You want to try to predict the cost of a typical shipment
given package dimensions. If 10 packages in a city are sampled and
the regression output is given below, what can we conclude about
the slope of weight?
Question 22 options:
1)
The slope is equal to 0.
2)
Since we are not given...
Question 9 (1 point) You work for a company in the marketing department. Your manager has tasked you with forecasting sales by month for the next year. You notice that over the past 12 months sales have consistently gone up in a linear fashion, so you decide to run a regression the company's sales history. You find that the regression equation for the data is (sales) 104.21*(time) + 113.38. In 11 months you see the actual sales quantity was 380.64....
Question 8 (1 point) Suppose that in a certain neighborhood, the cost of a home is proportional to the size of the home in square feet. If the regression equation quantifying this relationship is found to be (cost) = 85.779*(size) + 693.738, what does the slope indicate? Question 8 options: 1) When size increases by 1 square foot, cost increases by 85.779 dollars. 2) When size increases by 1 square foot, cost increases by 693.738 dollars. 3) We are not...
Question 5 (1 point) Suppose that for a typical FedEx package delivery, the cost of the shipment is a function of the weight of the package. You find out that the regression equation for this relationship is (cost of delivery) = 0.728*(weight) + 5.49. If a package you want to ship weighs 13.753 ounces and the true cost of the shipment is $12.229, the residual is -3.273. Interpret this residual in terms of the problem. Question 5 options: 1) The...
Use the following linear regression equation to answer the questions. x1 = 1.7 + 3.9x2 - 8.1X3 + 1.9x4 (a) Which variable is the response variable? O O O O Which variables are the explanatory variables? (Select all that apply.) o X3 O X4 Сх, (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient Xz coefficient x4 coefficient (C) If x2 = 8, X3 = 3, and X4 = 1, what...
Question 7 (1 point) Zagat restaurant guides publish ratings of restaurants for many large cities around the world. The restaurants are rated on a 0 to 30 point scale based on quality of food, decor, service, and cost. Suppose the regression equation that predicts the cost of dinner using the rating of the quality of food for the restaurants in a particular city is (cost of dinner) = 4.989*(food quality) + 2.406. If a restaurant in the city was given...
Use the following linear regression equation to answer the questions. X1 = 1.7 + 3.6x2 - 8.4x3 + 1.5x4 (a) Which variable is the response variable? O X1 O X2 O X4 O X3 Which variables are the explanatory variables? (Select all that apply.) X3 X1 U X2 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient X3 coefficient X4 coefficient (c) If x2 = 8, X3 = 5, and x4...
Use the following linear regression equation to answer the questions. x1 = 1.5 + 3.4x2 – 8.3x3 + 2.3x4 (a) Which variable is the response variable? Which variables are the explanatory variables? (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant? x2 coefficient? x3 coefficient? x4 coefficient? (c) If x2 = 1, x3 = 8, and x4 = 6, what is the predicted value for x1? (Use 1 decimal place.) (d) Explain how...
Question 13 (1 point)
A trucking company considered a multiple regression model for
relating the dependent variable of total daily travel time for one
of its drivers (hours) to the predictors distance traveled (miles)
and the number of deliveries of made. After taking a random sample,
a multiple regression was performed and the output is given below.
Interpret the slope of the distance variable.
Question 13 options:
1)
When distance increases by 1 miles, time decreases by 1.18
hours, holding...