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PROBLEM: LINEAR REGRESSION: QUALITATIVE INDEPENDENT VARIABLES IN THE DATA BELOW YOU ARE GIVEN WEEKLY SALES OF OREO COOKIES AT A WALMART STORE. ALSO, YOU ARE TOLD THAT FOR EACH WEEK THERE WAS A PRICE CUT (YES / NO) AND WHETHER OR NOT THERE WAS A DISPLAY SIGN (YES / NO) A) USE A REGRESSION MODEL TO EXPLAIN HOW PRICE AND DISPLAY AFFECT OREO COOKIE SALES ? B) ARE BOTH PRICE CUT AND DISPLAY STATISTICALLY SIGNIFICANT ? IF NOT, RE-RUN YOUR REGRESSION MODEL WITH ONLY A STATISTICALLY SIGNIFICANT INDEPENDENT VARIABLE. C) DURING A WEEK IN WHICH THE PRODUCT IS ON DISPLAY AND THE PRICE IS CUT, YOU ARE 95% SURE THAT WEEKLY SALES WILL BE BETWEEN AND Sales Price Cut? Week 1 On Display? No 817 No 2 1150 No yes 3 886 No No 4 817 yes No 5 713 No No 6 769 yes No 7 1099 No yes 8 744 yes No 9 1150 No yes 10 881 No No 11 780 No No 12 816 yes No 1120 yes yes 13 14 763 No yes No 15 857 No PROBLEM: LINEAR REGRESSION: QUALITATIVE INDEPENDENT VARIABLES IN THE DATA BELOW YOU ARE GIVEN WEEKLY SALES OF OREO COOKIES AT A WALMART STORE. ALSO, YOU ARE TOLD THAT FOR EACH WEEK THERE WAS A PRICE CUT (YES / NO) AND WHETHER OR NOT THERE WAS A DISPLAY SIGN (YES / NO) A) USE A REGRESSION MODEL TO EXPLAIN HOW PRICE AND DISPLAY AFFECT OREO COOKIE SALES ? B) ARE BOTH PRICE CUT AND DISPLAY STATISTICALLY SIGNIFICANT ? IF NOT, RE-RUN YOUR REGRESSION MODEL WITH ONLY A STATISTICALLY SIGNIFICANT INDEPENDENT VARIABLE. C) DURING A WEEK IN WHICH THE PRODUCT IS ON DISPLAY AND THE PRICE IS CUT, YOU ARE 95% SURE THAT WEEKLY SALES WILL BE BETWEEN AND Sales Price Cut? Week 1 On Display? No 817 No 2 1150 No yes 3 886 No No 4 817 yes No 5 713 No No 6 769 yes No 7 1099 No yes 8 744 yes No 9 1150 No yes 10 881 No No 11 780 No No 12 816 yes No 1120 yes yes 13 14 763 No yes No 15 857 No