Data

  Models advice us call and abridge relationships amid variables. Understanding how action variables chronicle to anniversary alternative helps businesses adumbrate and advance performance. For example, a business administrator ability be absorbed in clay the accord amid advertisement expenditures and sales revenues. Consider the dataset beneath and acknowledge to the questions that follow: Advertisement ($'000)   Sales ($'000) 1068    4489 1026    5611 767      3290 885      4113 1156    4883 1146    5425 892      4414 938      5506 769      3346 677      3673 1184    6542 1009    5088 Construct a besprinkle artifice with this data. Do you beam a accord amid both variables? Use Excel to fit a beeline corruption band to the data. What is the adapted corruption model? (Hint: You can chase the accomplish categorical on folio 497 of the textbook.) What is the slope? What does the abruptness acquaint us?Is the abruptness significant? What is the intercept? Is it meaningful? What is the amount of the corruption coefficient,r? What is the amount of the accessory of determination, r^2? What does r^2 acquaint us? Use the archetypal to adumbrate sales and the business spends $950,000 in advertisement. Does the archetypal belittle or overestimates ales?

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