DAILY HIGH and ICE CREAM SALES The owner of a large chain of ice cream would lik
ID: 3184087 • Letter: D
Question
DAILY HIGH and ICE CREAM SALES The owner of a large chain of ice cream would like to study the effect of atmospheric temperature on sales of ice cream during the summer season. A sample of 21 consecutive days is selected with the following results: Daily High Temperature Degrees F Sales Per Store (Thousands of Dollars) Day 70 73 75 80 1.52 1.68 1.80 2.05 2.25 2.68 2.90 3.06 3.24 1.92 3.40 3.28 3.17 2.83 2.58 2.86 2.26 2.14 1.98 10 91 12 13 14 100 92 87 16 17 19 80 82 76 21 A simple linear regression of the form Y +b bX, with DAILY HIGH as the explaining (independent) variable, and SALES as the explained (dependent variable). The computer output (results) is found below. Use the output to respond to the questions MODEL: SALES=b,+ b *DAILYHIGHExplanation / Answer
Solutiona:
Regression eq is
sales=-2.46010+0.05986(daily high)
Solutionb:
yintercept=b0=-2.46010
slope=b1=0.05986
slope=0.05986
intrepreation for slope:
y/x=0.05986
when For unit increase in daily high temperature,sales per store increases by 0.05986
Intrepretaion for y intercept:
when x=0 y=-2.46010
when daily high temperature is 0 deg F,sales per store is 2.46 Dollars
Solutionc:
There exists a strong positive relationship between daily high temperature and sales per store.
yes it makes sense
since r sq=0.935555
r=sqrt(0.935555)
r=0.967
and also the coefficient of slope is positve which says taht relationship is positive
Solutiond:
R sq=0.93555
=93.56% variation is sales per store is explained by daily high temperature.
Solutione:
when temperature is 0
sales=-2.46010
It does not make sense. since it is negative
Solutionf:
F statistic=275.826
p=0.0000
p<0.05
Model is significant.
There exists a linear realtionship between daily high temperature and sales per store.
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.