Expert Answers

CIS 360 assignment: Excel Pivots and Charts

Pivot Tables and Charts
Introduction
Excel allows you to create cross-tab (or cross-tabulation) analysis in what it calls a Pivot Table.
Pivot tables can be one, two or three-dimensional. You can use multiple statistical analysis and summary options tools. You can include data from multiple worksheets, and you can modify them dynamically.
Creating a Pivot Table
1. Open ExcelPivotsWorksheetCIS360.xlsx, found on Canvas.
2. Click on the Expenses tab.
3. Click on cell A2.
4. On the Insert tab click on the [PivotTable] button.
5. The Create Pivot Table box opens:

Assignment 7: Logistic Regression

Quiz Instructions

• Read the Assignment Instructions.

Actions

• Start with datafile: SchoolAdmission.jmp
• Change the file name to: YourFirstName_YourLastName_Assignment7.jmp
• You must use JMP to answer the following multiple-choice questions. 
• Note: When you are asked to submit a screen capture, you need to make sure that your name is part of the capture. 

 Question 1        2.5 pts

Since we are interested in understanding ADMITTED students, change the Value Order in "Column Properties" of the "ADMIT" column so that 1 (admitted) appears first in graphics and analyses. Show the screenshot to provide the evidence of this step.

Question 2        2.5 pts

Execute a contingency analysis to find out the relationship between ‘Admit’ and “Rank’ of the students. Which of the following statements is correct based on your analysis?

Group of answer choices

• 76.9% of Rank-2 students didn’t get admitted
• 45.9% of Rank-1 students didn’t get admitted.
• 35.8% of Rank-4 students didn’t get admitted.
• 17.9% of Rank-3 students got admitted

 Question 3        2.5 pts

Execute a simple logistic regression analysis to test if ‘Admit’ is significantly related to ‘GPA’.  Based on your analysis, which of the following statements is correct? [save the script to the datafile]

Group of answer choices

• ’Admit’ is significantly related to the independent variable ‘GPA’ because the p-value is less than 0.05
• ‘Admit’ is not related with ‘survived’ because one of them is categorical variable
• ‘Admit’ is not related to the dependent variable ‘GPA’ because the p-value is more than 0.05
• As ‘GPA’ increases, ‘Admit’ decreases.

Question 4        2.5 pts

Share an appropriate screenshot to support your answer in Question 3. Make sure you use different colors and different markers for students who got admitted and who didn’t.

Question 5        2.5 pts

Develop a simple logistic regression analysis to test if ‘Admit’ is significantly related to ‘GRE’. Based on your analysis, which of the following statements is correct?

Group of answer choices

• GRE is significantly related to the dependent variable ‘Admitted’
• GRE is not related to the dependent variable ‘Admit’
• As GRE increases, the Admit decreases.
• GRE is related to ‘Admit’ but is it not significant

 Question 6        2.5 pts

Share a screenshot of the Logistic Fit Plot to support your answer in Q5. Make sure you use different colors and different markers for students who got admitted and who didn’t.

 Question 7        2.5 pts

Use Analyze-> Fit Model to perform a 'stepwise' fit for “ADMIT” using all relevant predictors in the data. Use Minimum BIC (as stopping rule), Forward (as direction), and Whole Effects (as Rules) in the model. Run the logistic regression model using the selected variables in the previous step. Which of the following variables is/are significant in the model to predict when students get admitted?  [save the script to the data file]

Group of answer choices

• GPA
• None of the variables are significant
• GRE
• Both GRE and GPA

 Question 8        2.5 pts

Submit the parameter estimate table from the above model in Question 7.

Upload 

 Question 9        2.5 pts

Submit the final equation of the model (the resulting logit of the probability model, saved as Lin[1] in the data table). [save script to the data file]

Upload 

 Question 10      2.5 pts

Submit the JMP data file with saved script for all the analysis to answer questions from this assignment.

WPC300 Quiz 7: Clustering

Started: Feb  2021

Quiz Instructions

Question 1        1 pts

Which of the following is a step of agglomerative hierarchical clustering?

Group of answer choices

• By separating cluster into two finer groups
• By joining two clusters that not at a Euclidean distance
• By joining two clusters that are closest to each other
• By joining two clusters farthest away from each other 

Question 2        1 pts

Which of the following is true about k-means clustering

Group of answer choices

• The cluster analysis will give us an optimum value for k
• We choose the value for k before doing the clustering analysis
• A tree diagram is used to illustrate the steps in the clustering analysis
• It is a type of hierarchical clustering

Question 3        1 pts

Which of the following is true of hierarchical clustering?

Group of answer choices

• All clusters must have the same number of data
• All clusters must have more than one object in it
• No single cluster can have all data
• The data partition does not occur in a single step

Question 4        1 pts

In a cluster analysis, the distance between the clusters should be:

Group of answer choices

• Minimized
• Even
• Maximized
• Zero

 Question 5        1 pts

Which of the following is not an application of clustering analysis?

Group of answer choices

• Crime prediction analysis
• Web click stream analysis
• Market segmentation analysis
• Collaborating filtering analysis

 Question 6        1 pts

In the Target story discussed in the lecture, why did Target send the teen daughter maternity ads?

Group of answer choices

• Target analytic model confused her with an older woman with a similar name
• Target was using special promotion that targeted all teens in her geographical area
• Target analytics model suggested she was pregnant based on her buying habit
• Target was sending ads to all women in a particular neighborhood

Question 7        1 pts

Which of the following category of data mining you would use for Spam filtering of emails?

Group of answer choices

• Supervised
• Unsupervised
• Heuristics
• Both supervised and unsupervised

Question 8        1 pts

Which of the following statements below is false about supervised/unsupervised data analysis?

Group of answer choices

• The data is not labeled for unsupervised
• Data is not labeled for supervised analysis
• For unsupervised analysis, the goal is to find cases that are similar to each other
• The data is labeled for supervised analysis

Question 9        1 pts

Which of the following is a false statement?

Group of answer choices

• The k-means algorithm is a method for doing partitional clustering
• Reducing SSE (sum of squared error) within cluster increases cohesion
• To predict sales from transactional data one should perform clustering analysis.
• In the cluster analysis, the objects within clusters should exhibit an high amount of similarity

Question 10     1 pts

Which of the following is a definition of distance between two clusters in a complete linkage clustering?

Group of answer choices

• The sum of square of the distance between clusters
• The distance between the least distant pair of objects, one from each group
• The distance between the most distant pair of objects, one from each group
• The average of distance between all pairs of objects, where each pair is made up of one object from each group

• Lab 7: Logistic
• Started: Feb
• Quiz Instructions
• Start with datafile:
• titanicpassengers-bbm.jmp
• Change the file names to: YourFirstName_YourLastName_titanicpassengers.jmp
• Review what we did in the lab.
• You must use JMP to answer the following multiple-choice questions. 
• Note: When you are asked to submit a screen capture, you need to make sure that your name is part of the capture. 

Question 1        2 pts

Based on the available data sample, what percentage of the 3rd class passengers were on board that survived the accident?

Group of answer choices

• 74.5%
• 25.5%
• 43%
• 62%

Question 2        2 pts

What percentage of male on board did not survive the accident?

Group of answer choices

• 72.3%
• 19.1%
• 27.3%
• 80.9%

 Question 3        2 pts

Develop a simple logistic regression model to test if ‘Age’ is a significant predictor of the outcome ‘survived’.  Based on your analysis, which of the following statements is correct?

Group of answer choices

• As 'Age' increases, the survival rate also increases.
• Age is not a significant predictor of the dependent variable ‘survived’
• Age is a significant predictor of the dependent variable ‘survived’
• As 'Age' decreases, the survival rate decreases.

 Question 4        2 pts

Share a screenshot to support your answer in Q3. Make sure you use different colors and different markers for passengers who survived and who didn’t.

Upload 

 Question 5        2 pts

Develop a simple logistic regression model to test if ‘Fare’ is a significant predictor of the outcome ‘survived’.  Based on your analysis, which of the following statements is correct?

Group of answer choices

• Fare is not correlated with the dependent variable ‘survived’ because the p-value is more than 0.05
• Fare is not correlated with ‘survived’ because one of them is a categorical variable
• As Fare increases, the survival rate decreases
• Fare is a significant predictor of the dependent variable ‘survived’ because the p-value is less than 0.05

 Question 6        2 pts

Share a screenshot to support your answer in Q5. Make sure you use different colors and different markers for passengers who survived and who didn’t.

Upload 

 Question 7        2 pts

As shown in the lab, develop a multiple logistic regression model (use stepwise regression) to predict survival. Which of the following variables is most significant in predicting survival?

Group of answer choices

• Age
• Port
• Sex
• Passenger class

 Question 8        2 pts

As shown in the lab, develop a multiple logistic regression model (use stepwise regression) to predict survival. Which of the following variables is not significant to predict survival?

Group of answer choices

• Parents and children
• Age
• Port
• Passenger class

 Question 9        2 pts

Provide a screenshot of appropriate table to support your answer in Q7 & Q8

Upload 

 Question 10   2 pts

Provide the screenshot of the equation of the final model (the resulting logit of the probability model, saved as Lin[Yes] in the data table).

Quiz 6: Logistic

Started: Feb

Quiz Instructions

Question 1        1 pts

In classification analysis, we are determining the probability of an observation ________.

Group of answer choices

• To be undefined
• To be one
• To be part of a certain class or not
• To be zero

Question 2        1 pts

A loan officer wants to know if the next customer is likely to default or not on a loan. How can she assess the risk of extending the loan to that customer?

Group of answer choices

• By utilizing a simple linear regression model developed by an in-house analyst
• By asking his colleague if he knows the person
• By asking the customer if he is planning to default the loan or not
• By utilizing a multiple logistic regression model developed by an in-house analyst

Question 3       1 pts

In classification analysis, we typically split the data into two mutually exclusive sets, known as ________, to investigate the strength of the developed model.

Group of answer choices

• Training and Binary
• Training and validation/testing
• Binary and numeric
• Testing and validation

Question 4       1 pts

Odds ratio is defined as ________, where p is the probability of success.

Group of answer choices

• p/1-p
• 1/p-1
• p/p-1
• 1/1-p

Question 5         1 pts

The ________ is often used to describe the performance of a classification model applied to a set of test data for which the true outcomes are known.

Group of answer choices

• Effect summary table
• ANOVA table
• Parameter estimates table
• Confusion matrix

Question 6       1 pts

If you want to find out if body weight, calorie intake, fat intake and age have an influence on the probability of having a heart attack (yes or no), which of the following kind of analysis will help determine the answer?

Group of answer choices

• Multiple logistic regression
• Simple logistic regression
• Simple linear regression
• Multiple linear regression

Question 7          1 pts

In classification problems, the primary source for accuracy estimation of the model is ________.

Group of answer choices

• Probability of success
• Logit
• Confusion matrix
• Odds ratio

Question 8     1 pts

In logistic regression analysis, instead of Y as a dependent variable, we use a function of Y called ________.

Group of answer choices

• Logit
• Odds
• Odds ratio
• Log of Y

Question 9       1 pts

Logistic regression is a specialized type of regression analysis that is designed to predict ________ variables.

Group of answer choices

• independent
• numeric dependent
• a binary numeric
• a binary categorical

Question 10        1 pts

In logistic regression, the dependent variable y is defined as:

Group of answer choices

• Log (p/1-p)
• Log(1/p)
• Log (1/1-p)
• Log (1-p)

Assignment 6: Linear Regression

Started: Feb

Quiz Instructions

• Read the Assignment Instructions.

Actions

• Start with datafile: CarsData.jmp
• Change the file name to: YourFirstName_YourLastName_Assignment6.jmp
• You must use JMP to answer the following multiple-choice questions. 
• Note: When you are asked to submit a screen capture, you need to make sure that your name is part of the capture. 

Question 1        2.5 pts

You have been asked to test if 'city mileage' of a car can be predicted based on the 'Fuel Tank capacity'. Which of the following statements is correct?

Group of answer choices

• Dependent variable ‘Fuel Tank Capacity’ is negatively correlated with independent variable ‘City Mileage of Car’
• The test shows that the variables are significantly correlated. Dependent variable ‘City mileage car’ is predicted as City Mileage (MPG) = 45.587166 - 1.3934743*Fuel Tank Capacity
• The test shows that both variables are correlated. The dependent variable ‘Fuel Tank Capacity’ is predicted as Fuel Tank Capacity = 45.587166 + 1.3934743*City Mileage of Car.
• The test shows that both variables are not correlated. Dependent variable City mileage car is predicted as City Mileage (MPG) = 45.587166 + 1.3934743*Fuel Tank Capacity

Question 2         2.5 pts

What is the coefficient of determination between 'City Mileage' and 'Weight'? [Save the script to the data file]

Group of answer choices

• 47.05
• 0.71
• -0.008
• 0.66

Question 3        2.5 pts

The team wants to find out if there are any other variables that are significantly correlated, with a correlation coefficient greater than +0.8 or less than -0.8. Execute an appropriate analysis to answer this question. Which of the following combinations of variables satisfy this condition? [Save the script to the data file]

Group of answer choices

• Luggage Capacity and weight
• Fuel Tank Capacity & Weight
• Weight & Maximum Horsepower
• Maximum Horsepower & Engine Size

Question 4       2.5 pts

Use the least square method to develop a linear model to predict the city mileage of a car using all other variables in the data file as independent variables, except ‘Model’ & ‘Manufacturer’. Remove the insignificant parameters from the model one by one by checking the log(worth) of each parameter and removing the least important parameter first from the model. Which of the following variables remain significant in the final model? [Save Script to the datafile]

Group of answer choices

• Maximum Horsepower & Fuel Tank Capacity
• Vehicle category & Weight
• Luggage capacity & Weight
• Rear seat room & Weight

Question 5        2.5 pts

What is the coefficient of determination of model equation obtained from Question 4?

Group of answer choices

• 0.43
• 0.64
• 0.78
• 0.80

Question 6           2.5 pts

The team also asked you to check for any multi-collinearity effects in your model obtained from Question 4. After testing for any multi-collinearity effects (using VIF), what did you find out?

Group of answer choices

• ‘Passenger capacity’ and ‘Length’ variables show multi-collinearity effects in the model
• ‘Passenger capacity’ and ‘Weight’ variables show multi-collinearity effects in the model
• ‘Fuel Tank Capacity’, ‘Width’ and ‘Weight’ variables show multi-collinearity effects in the model
• ‘Vehicle Category’ and ‘Engine Size’ variables show multi-collinearity effects in the model

Question 7        2.5 pts

If you discovered multi-collinearity effects in the model, remove the variables in question one at a time (starting from the highest VIF) from the model and then stop when you don’t need to remove any further variable(s) from the model based on accepted VIF and p-values. After this process, submit the screenshot of the ‘Effect Summary’ of the final model. 

Upload 

Question 8            2.5 pts

Based on the model in question 7,  what are the strongest and weakest variables in predicting the city mileage of a car?

Group of answer choices

• Passenger Capacity (strongest) and Weight (weakest)
• Vehicle Category (strongest) and Passenger Capacity (weakest)
• Weight (strongest) and ‘Length’ (weakest)
• Fuel Tank Capacity (strongest) and Passenger Capacity (weakest)

Question 9          2.5 pts

What is the model equation for the final model in Question 7 to predict City mileage of a car? [Save script] Submit a screenshot.

Question 10       2.5 pts

Submit the JMP data file with saved script for all the analysis to answer questions from this assignment.

Upload

WPC300

Lab 6: Linear Reg

Quiz Instructions

• Start with datafile:
  • housingprices.jmp
• Change the file names to: YourFirstName_YourLastName_housingprices.jmp
• Review what we did in the lab.
• You must use JMP to answer the following multiple-choice questions. 
• Note: When you are asked to submit a screen capture, you need to make sure that your name is part of the capture. 

Question 1   2 pts

In a simple linear regression model that predicts home price based on the number of bedrooms, the coefficient of determination is:

Group of answer choices

None of the given answers is correct

0.44

0.98

0.46

Question 2       2 pts

Is the linear model obtained in the previous question significant? Support your answer with an appropriate screenshot from JMP analysis.

Upload 

Question 3         2 pts

When you develop a prediction model for home-price, based on the beds, baths, and square feet as independent variables, which, if any, of the following independent variables is significant in the model?

Group of answer choices

All of the other answers are correct

Square footage

Baths

Beds

Question 4           2 pts

In a final model (after removing all the non-significant predictors) to predict the home price based on other variables available in the data file, the most important predictor that contributes significantly is:

Group of answer choices

• Square feet
• Acres
• Baths
• Miles to base

Question 5       2 pts

What is the model equation based on multiple regression analysis to predict home price? (reference Q4). Provide a screenshot from JMP output to show the model question.

Upload 

Question 6      2 pts

What is the coefficient of determination for the final model in previous question?

Group of answer choices

• 0.61
• 0.78
• -0.34
• 0.80

Question 7       2 pts

In the final model (reference Q4), do you have any multicollinearity issue to be addressed?

Group of answer choices

• Need additional information such as ‘residual’ to answer this question
• Need more data to answer this question
• No
• Yes

Question 8       2 pts

Share a screenshot of the appropriate table to support your answer in Q7. 

Upload 

Question 9        2 pts

Based on the final regression equation, if all variables remain the same, for an additional bath in the house, the home price wil:

Group of answer choices

• Increase by $197 K
• Increase by $59.2 K
• Decrease by $3.8 K
• Increase by $5.00 K

Question 10        2 pts

Create a frequency distribution (with summary statistics) of the residual ( Observed value - Predicted value) to show how well the model predicts the actual home price. Share the screenshot of this plot. 

WPC 300

Assignment 5 : Inferential Statistics

Feb 2021 Update

Score  25 out of 25

Question 1                       2.5 pts 
What statistical test would perform to test your hypothesis: average time to deliver pizza, once the order is placed, is less than or equal to 25 minutes in the population. 

• No test is necessary
• ANOVA
• T-test
• Z-test 

Question 2                       2.5 pts 
The null hypothesis for the statistical test for Question 1 is: 

• Mean delivery time is less than or equal to 25 minutes
• None of the other answers are correct
• Mean delivery time is less than 0.05
• Mean delivery time is more than 25 minutes 
   

Question 3                                       2.5 pts 
Based on the sample, is there sufficient evidence in the data to conclude that the population average time to deliver a pizza, once the order is placed, is greater than 25 minutes? Based on the statistical analysis (with margin of error = 5%) what is your conclusion? Pave the script to the data file] 

• We could not conclude anything
• We accept the null hypothesis and hence conclude that the delivery time is more than 25 min
• We reject the null hypothesis, and hence conclude that the delivery time is more than 25 min
• We could not reject the null hypothesis, and hence conclude the mean delivery time is less than or equal to 25 min 

Question 4                                   2.5 pts 
Submit a screenshot of an appropriate analysis table to support your answer in Question 3. 

Upload _________
 

Question 5                                 2.5 pts 
Given the sample data, what kind of statistical test would you perform in order to find out if the days of the week have an effect on Use mean delivery time? 

• Z-test 
• T-test
• ANOVA
• Descriptive 

Question 6                           2.5 pts 
Based on executing the test in Question 5, what would you conclude, given a margin of error of 5%? 

• We reject the null hypothesis; the mean delivery time is different for every day of the week 
• We reject the null hypothesis; the mean delivery time is different at least on one of the days of the week 
• We could not reject the null hypothesis; the mean delivery time is not different for different days of the week 
• We accept the null hypothe week; the mean delivery time is not different for different days of the week
   

Question 7                              2.5 pts 
Execute an appropriate follow-up test to determine on which days of the week the an delivery time is different. What is your conclusion? [Save the script to the data file] 

• Mean delivery times on Tuesday and Wednesday are different
• Mean delivery times on Friday and Thursday are different
• Mean delivery times on Saturday and Thursday are different
• All of the answers are correct 
   

Question 8                             2.5 pts 
Execute an appropriate statistical test, with a margin of error of 5%, to determine if hour of the day has an effect on the mean delivery time. What is your conclusion? [Save the script to the data file] 

• Mean delivery time is different on the 9th and 10th hour of the day
• Nothing can be concluded as additional information is necessary
• Mean delivery time does not vary by the hour of the day
• Mean delivery time is different at every hour of the day 

Question 9                    2.5 pts 
Based on your analysis, what action would you recommend to the owner of Pizza Perk to improve their operation? 

• The owner should focus on reducing the mean delivery time to 20 minutes. 
• The owner should collect additional delivery time data to make better recommendation on pizza delivery operation
• The owner should consider hiring you full time
• The owner should consider hiring more staff on Friday and Saturday to reduce wait timeon those days. 
   

Question 10                                                2.5 pts 
Submit the JMP data file with the saved scripts for all the analyses to answer questions from this assignment. 
Upload _______

Lab 5: Inferential

Quiz Instructions

• Start with datafiles:
  • Salary-ANOVA.jmp
  • pricequotes.jmp
• Change the file names to: YourFirstName_YourLastName_XXXX.jmp
• Review what we did in the lab.
• You must use JMP to answer the following multiple-choice questions. 
• Note: When you are asked to submit a screen capture, you need to make sure that your name is part of the capture. 

Question 1       2 pts

Refer data: pricequote.jmp

Using descriptive statistics, what can you conclude? 

Group of answer choices

• Mary’s pricing is more reasonable than that of Barry.
• Barry’s average price is lower than Mary’s average price
• Variation in Mary’s price is higher than Barry’s price
•  Barry’s average price is higher than Mary’s average price

Question 2     2 pts

Use a box plot to compare overall all difference in price quoted by Barry and Mary.  What is your conclusion?

Group of answer choices

• Barry’s price has larger spread in the population
• Mary’s price has a larger spread in the sample
• Mary’s price has larger spread in the population
• Barry’s price has a larger spread in the sample

 Question 3     2 pts

Interquartile range in Mary’s price quote is from:

Group of answer choices

• $133 to $114
• $114 to $105
• $125 to $105
• $133 to $97

 Question 4             2 pts

Based on a two-tailed statistical test to infer about the population, what is your conclusion?

Group of answer choices

• Overall, Mary’s prices are significantly higher than Barry’s prices
• Nothing can be inferred as the sample size is really small
• Overall, Barry’s prices are similar to Mary’s prices
• Overall, Barry’s prices are not the same as Mary’s prices.

 Question 5      2 pts

To develop a two-tailed statistical test to find the answer to Q4, what is the null hypothesis?

Group of answer choices

• Overall, Barry’s prices are at least $9 higher than Mary’s prices
• Overall, Barry’s prices are the same as Mary’s prices.
• Overall, Barry’s prices are less than Mary’s prices
• Overall, Barry’s prices are more than Mary’s prices

Question 6        2 pts

The conclusion inferred in Q4 is supported by t-test where the obtained p-value is.

Group of answer choices

• More than 0.0284
• Less than 0.986
• Less than 0.05
• Equal to 2.52

 Question 7            2 pts

Refer data:SalaryANOVA.jmp. 

What is the null hypothesis of the ANOVA analysis of Salary data across majors,

Group of answer choices

• Average salaries of all college majors are very different
• Average salaries of all college majors are the same
• None of the selection is correct
• Average salaries of all college majors are slightly different

 Question 8           2 pts

Based on the results obtained from the ANOVA analysis of Salary data across majors, 

Group of answer choices

• You reject the null hypothesis
• You reject the alternative hypothesis
• You could not reject the null hypothesis
• You accept the null hypothesis

 Question 9        2 pts

Based on the connecting letter report, salaries of which college majors are significantly different?

Group of answer choices

• Language and music
• Social science and music
• Social science and special education
• Science and music

Question 10          2 pts

Support your answer for Q9 by providing an appropriate screenshot. 

Upload 

Wpc300

Quiz 5: Regression 

The score for this quiz: 10 out of 10

Question 1

1 / 1 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 a negative relationship between profit and sales. 
•   There is a linear relationship between profit and sales that can be either positive or negative. 
•   There is no linear relationship between profit and sales. 
•   There is a positive relationship between profit and sales. 

Question 2

1 / 1 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 linear variable 
•   an independent variable 
•   a continuous variable 
•   a dependent variable

 Question 3

1 / 1 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. 
•   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.
•   A unit point change in reading label will increase IQ by 5.6 point. 

Question 4

1 / 1 pts

The value of R-Squared always falls between ________ and ________, inclusive.

•   -infinity to + infinity 
•   0 and 1
•   -1 and +1 
•   0 and -1

Question 5

1 / 1 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 repair cost will be explained by the age of the vehicle 
•   90% of the money spent on repair is 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
•   81% of money spent on repairs is explained by the age of the vehicle 

Question 6

1 / 1 pts

Which of the following is true about multi-collinearity?

•   The effect of an independent variable on the dependent variable becomes easy to isolate.
•    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. 

Question 7

1 / 1 pts

The unexplained variance in the regression analysis is also known as:

•   Total variance
•   Residual variance 
•   Predicted variance 
•   Regression variance 

Question 8

1 / 1 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:

•   The entrance exam is a good predictor of success. 
•   They should hire a new statistician. 
•   The exam is a poor predictor of success.
•   Students who do best on this exam will make the worst students.

Question 9

1 / 1 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:

•   $7400 
•   $3850 
•   $2090 
•   $6900

Question 10

1 / 1 pts

Which of the following assumptions is not true for multiple linear regression?

•   The independent variables are not correlated. 
•   The relationship between dependent and independent variables is linear. 
•   There will be a multi-collinearity effect. 
•   The residuals are normally distributed.