Inferential and Predictive Statistics for Business | Online Course Support

To predict the price of a hotel room for a weekday in Manhattan, a hotel rating agency uses a multiple regression model. A short snapshot of the results are given below :

10. Question 10 To predict the price of a hotel room for a weekday in Manhattan, a hotel rating agency uses a multiple regression model. A short snapshot of the…

Inferential and Predictive Statistics for Business | Online Course Support

To predict the sales of a certain brand of cheese dip, a retail store manager uses a multiple regression model. Some of the factors he considers and their respective p-values are as below:

5. Question 5 To predict the sales of a certain brand of cheese dip, a retail store manager uses a multiple regression model. Some of the factors he considers and…

Inferential and Predictive Statistics for Business | Online Course Support

To predict the average speeds of vehicles on the interstates, the DOT plans to use a multiple regression model. They feel that the vehicle speed is determined by a variety of factors including the type of the vehicle (coupe, sedan, hatchback, etc.), vehicle age, engine size, road conditions, weather, driver age, time of the day (morning, afternoon, etc).

9. Question 9 To predict the average speeds of vehicles on the interstates, the DOT plans to use a multiple regression model. They feel that the vehicle speed is determined…

Inferential and Predictive Statistics for Business | Online Course Support

Henry wants to predict the stock price of companies on the basis of using historical data using a multiple regression model. The companies can be broadly classified into: Tech, Construction, Services, and Financial Sector. After running the model, the coefficient obtained for the dummy variables are as follows:

8. Question 8 Henry wants to predict the stock price of companies on the basis of using historical data using a multiple regression model. The companies can be broadly classified…

Inferential and Predictive Statistics for Business | Online Course Support

For a multiple regression model predicting life expectancy, smokers and non-smokers are considered as two distinct categories. The non-smokers were coded as “1” in a dummy variable (x_5x5​). The regression equation is :

7. Question 7 For a multiple regression model predicting life expectancy, smokers and non-smokers are considered as two distinct categories. The non-smokers were coded as “1” in a dummy variable…

Inferential and Predictive Statistics for Business | Online Course Support

In order to predict the number of heart attacks caused in a year in Illinois, a multiple regression model is used with the following explanatory variables. The coefficients of each of the variables are: Hypertension (yes/no) (4.67), Smoker (yes/no) (1.98), Moderate exercise three times per week (yes/no) (2.67), Bi-annual health check-ups (yes/no) (0.16). Which of these explanatory variables have the maximum impact on the response variable?

4. Question 4 In order to predict the number of heart attacks caused in a year in Illinois, a multiple regression model is used with the following explanatory variables. The…

Inferential and Predictive Statistics for Business | Online Course Support

For a given multiple regression model with three independent variables, the value of the adjusted R2 is _________ less than R2.

2. Question 2 For a given multiple regression model with three independent variables, the value of the adjusted R2 is _________ less than R2. 1 point   Always   Sometimes…

Inferential and Predictive Statistics for Business | Online Course Support

In a study to determine the impact of gender on the sales of a laptop, a multiple regression model was used with the following results. Significance level was considered to be 0.01.

6. Question 6 In a study to determine the impact of gender on the sales of a laptop, a multiple regression model was used with the following results. Significance level…

Inferential and Predictive Statistics for Business | Online Course Support

To predict the probable number of applicants to the iMBA program the admissions team uses a multiple regression model. The R-Squared value is 0.8456, and the Adjusted R-Squared value is 0.7938. What percentage of variations of the response variables can be explained by this model?

3. Question 3 To predict the probable number of applicants to the iMBA program the admissions team uses a multiple regression model. The R-Squared value is 0.8456, and the Adjusted…