the following data relate to the size of the electricity bill sent to seven randomly selected cistomers and the time the customers took to pay the bills

AutoSave OFF S Ch. 10 HW View Comments Formulas A A WA Home Insert Draw Page Layout Calibri (Body) 11 Peste 3 BIUR O 441 x fx Data = = Review = = General 2 Wraa Text Merge & Center - E Q- Search Sheet Share E 2Y- O Xv Filter Select 3- X Insert $ % % Delete Format Formatting as Table Styles Format Shape 1 cuestion 10 3 customer time to size of bill 100 Fill SUMMARY OUTPUT Line Regression Statistics Multiple 088978738 RSquare 0.79172159 Adjusted Rs 0.7500G59 a ndard Erro 11445392 Observacions No line Solid line Graciunt line 12 All calculator to find pearsons correlation for the data 0.89978738 13 B using the least squares regression ecuscioni predict it will takexxex long to pay this size of bill xxxlong to this size of abill 14 C Interpret 15 D. drewline 16 E.use equation to predict how long it will take to pay a bill far 17 1125 will take long for customer to pay 18 000 will takex long for a customer ta pay 19 F. The coefficient of determination for this data is 79.2% interpret this valucasx ANOVA of Regression Residual SS MS F Significance 1 184.358027 184.358027 19.00632RS 0.00729283 S45.4991162 9.69982323 6 232.857143 Chart Title Intercept X Variable. Cocients Trundara' Frror Stor! Pwlup Tower 95% per 95% Power 05.0X Ioner 95.0% 11.1285516 2.78719064 3.9927831 0.01039752 3.95395999 18.2933632 3.96395999 18.2933632 0.04036616 0.00925909 4.35962451 0.00729283 0.0165649 0.06416241 0.01656491 0.00416741 me to pay 0 100 200 400 500 600 300 of bil question 8 question 8 Question 10 Question 12 Question 13 + # 2 - - - + 100% AutoSave OFF S Ch. 10 HW View Comments Formulas A A WA Home Insert Draw Page Layout Calibri (Body) 11 Peste 3 BIUR O 441 x fx Data = = Review = = General 2 Wraa Text Merge & Center - E Q- Search Sheet Share E 2Y- O Xv Filter Select 3- X Insert $ % % Delete Format Formatting as Table Styles Format Shape 1 cuestion 10 3 customer time to size of bill 100 Fill SUMMARY OUTPUT Line Regression Statistics Multiple 088978738 RSquare 0.79172159 Adjusted Rs 0.7500G59 a ndard Erro 11445392 Observacions No line Solid line Graciunt line 12 All calculator to find pearsons correlation for the data 0.89978738 13 B using the least squares regression ecuscioni predict it will takexxex long to pay this size of bill xxxlong to this size of abill 14 C Interpret 15 D. drewline 16 E.use equation to predict how long it will take to pay a bill far 17 1125 will take long for customer to pay 18 000 will takex long for a customer ta pay 19 F. The coefficient of determination for this data is 79.2% interpret this valucasx ANOVA of Regression Residual SS MS F Significance 1 184.358027 184.358027 19.00632RS 0.00729283 S45.4991162 9.69982323 6 232.857143 Chart Title Intercept X Variable. Cocients Trundara' Frror Stor! Pwlup Tower 95% per 95% Power 05.0X Ioner 95.0% 11.1285516 2.78719064 3.9927831 0.01039752 3.95395999 18.2933632 3.96395999 18.2933632 0.04036616 0.00925909 4.35962451 0.00729283 0.0165649 0.06416241 0.01656491 0.00416741 me to pay 0 100 200 400 500 600 300 of bil question 8 question 8 Question 10 Question 12 Question 13 + # 2 - - - + 100%