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= Chegg Books Study Writing Flashcards Math Solver Internships V Part 2: (40 points) Use the Credit data to perform the following tests using Linear Regression settings: A. Perform the following steps: (20 points) Continue to post 11 questions remaining i. Attach the Credit data to the R environment. (5 points) ii. Observe the number of rows in the Credit data. Observe the dimension of the Credit data. (5 points) iii. Provide a summary stat for the variables in Credit data. (5 points) iv. What is the percentage of Student in the Credit data? What is the percentage of Female in the Credit data? (5 points) Snap a photo from your phone to post a question We'll send you a one-time download link B. Construct a linear regression model as follows: (20 points) 888-888-8888 Response variable: Credit Card Balance Predictors: Credit Rating, Student, Credit Rating * Student (interaction terms) Provide a summary of the model using summary() function Provide answer in R code. Please. Thank you so much Text sent to Credit card Data Income Limit Rating Cards Age Education Gender Student Married Ethnicity Balance By providing your phone number, you agree to receive a one-time automated text message with a link to get the app. Standard messaging rates may apply. 1 14.891 3606 283 2 34 11 Male No Yes Caucasian 333 2 106.025 6645 483 3 82 15 Female Yes Yes Asian 903 3 104.593 7075 514 4 71 11 Male No No Asian 580 My Textbook Solutions 4 148.924 9504 681 3 36 11 Female No No Asian 964 Solutions Solutions Solutions Chem- Sur 5 55.882 4897 357 2 68 16 Male No Yes Caucasian 331 by Chegg 6 80.18 8047569 4 77 10 Male No No Caucasian 1151 by Chegg Bond Markets... 9th Edition ALLY by Chegg Chemistry Oth Edition Investments 11th Edition 7 20.996 3388 259 2 37 12 Female No No 203 African American View all solutions = Chegg Books Study Writing Flashcards Math Solver Internships V Part 2: (40 points) Use the Credit data to perform the following tests using Linear Regression settings: A. Perform the following steps: (20 points) Continue to post 11 questions remaining i. Attach the Credit data to the R environment. (5 points) ii. Observe the number of rows in the Credit data. Observe the dimension of the Credit data. (5 points) iii. Provide a summary stat for the variables in Credit data. (5 points) iv. What is the percentage of Student in the Credit data? What is the percentage of Female in the Credit data? (5 points) Snap a photo from your phone to post a question We'll send you a one-time download link B. Construct a linear regression model as follows: (20 points) 888-888-8888 Response variable: Credit Card Balance Predictors: Credit Rating, Student, Credit Rating * Student (interaction terms) Provide a summary of the model using summary() function Provide answer in R code. Please. Thank you so much Text sent to Credit card Data Income Limit Rating Cards Age Education Gender Student Married Ethnicity Balance By providing your phone number, you agree to receive a one-time automated text message with a link to get the app. Standard messaging rates may apply. 1 14.891 3606 283 2 34 11 Male No Yes Caucasian 333 2 106.025 6645 483 3 82 15 Female Yes Yes Asian 903 3 104.593 7075 514 4 71 11 Male No No Asian 580 My Textbook Solutions 4 148.924 9504 681 3 36 11 Female No No Asian 964 Solutions Solutions Solutions Chem- Sur 5 55.882 4897 357 2 68 16 Male No Yes Caucasian 331 by Chegg 6 80.18 8047569 4 77 10 Male No No Caucasian 1151 by Chegg Bond Markets... 9th Edition ALLY by Chegg Chemistry Oth Edition Investments 11th Edition 7 20.996 3388 259 2 37 12 Female No No 203 African American View all solutions