(Solved): WPC 300 Quiz 9 : Score for this attempt: 15 out of 15 : Attempt 1 ...
WPC300 Quiz 9
Score for this attempt: 15 out of 15
This attempt took 20 minutes.
Question 1
1.5 / 1.5 pts
Which of the following assumptions is not true for multiple linear regression?
- There will be a multi-collinearity effect.
- The relationship between dependent and independent variables is linear.
- The residuals are normally distributed.
- The independent variables are not correlated.
Question 2
1.5 / 1.5 pts
A manager wishes to predict the annual cost (y) of an automobile based on the number of miles (x) driven. The following model was developed: y = $1500 + 0.36x. If a car is driven 15000 miles in a year, the model predicts the annual cost of the car to be:
- $2090
- $3850
- $7400
- $6900
Question 3
1.5 / 1.5 pts
The correlation coefficient between the age of a vehicle and the money spent to repair it is 0.9. Which of the following statement is true?
- 90% of the money spent on repair is explained by the age of the vehicle
- 81% of money spent on repairs is explained by the age of the vehicle
- 90% of the repair cost will be explained by the age of the vehicle
- 81% of the variation in the money spent on repairs is explained by the age of the vehicle
Question 4
1.5 / 1.5 pts
What would be the null hypothesis for testing a linear regression model with profit as the dependent variable and sales as the independent variable?
- There is no linear relationship between profit and sales.
- There is a negative relationship between profit and sales.
- There is a positive relationship between profit and sales.
- There is a linear relationship between profit and sales that can be either positive or negative.
Question 5
1.5 / 1.5 pts
A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural). The "neighborhood" variable in this model is ________.
- a dependent variable
- a linear variable
- a continuous variable
- an independent variable
Question 6
1.5 / 1.5 pts
A correlation coefficient between “college entrance exam” grades and scholastic achievement was found to be -1.08. On the basis of this, you would tell the university that:
- They should hire a new statistician.
- Students who do best on this exam will make the worst students.
- The entrance exam is a good predictor of success.
- The exam is a poor predictor of success.
Question 7
1.5 / 1.5 pts
Which of the following is true about multi-collinearity?
- The regression coefficients become clearer and are easier to interpret.
- It is measured using a measure called variance inflation factor (VIF).
- The P-value reduces significantly, leading to rejection of the null hypothesis.
- The effect of an independent variable on the dependent variable becomes difficult to isolate.
Question 8
1.5 / 1.5 pts
The value of R-Squared always falls between ________ and ________, inclusive.
- -infinity to + infinity
- 0 and -1
- -1 and +1
- 0 and 1
Question 9
1.5 / 1.5 pts
Which of the following statement is true based on the following regression equation?
IQ = 4.0 + Reading Label * 5.6
- A unit point change in IQ will result in 9.6-point increase in reading label.
- A unit point change in reading label will increase IQ by 5.6 point.
- Reading label is not a good predictor of IQ.
- A unit point change in IQ will result in 5.6-point increase in reading label.
Question 10
1.5 / 1.5 pts
The unexplained variance in the regression analysis is also known as:
- Residual variance
- Regression variance
- Total variance
- Predicted variance
Expert Answer
Question 1
1.5 / 1.5 pts
Which of the following assumptions is not true for multiple linear regression?
- There will be a multi-collinearity effect.
- The relationship between dependent and independent variables is linear.
- The residuals are normally distributed.
- The independent variables are not correlated.
Question 2
1.5 / 1.5 pts
A manager wishes to predict the annual cost (y) of an automobile based on the number of miles (x) driven. The following model was developed: y = $1500 + 0.36x. If a car is driven 15000 miles in a year, the model predicts the annual cost of the car to be:
- $2090
- $3850
- $7400
- $6900
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