Question

need 5-9 please

Jason believes that the sales of his coffee shop depend upon the weather. He has taken a sample of 5 days Below you are given the results of the sample Temp Cups of coffee sold 700 50 60 500 70 400 80 200 100 90 -You are going to conduct a simple linear regression analysis using this data I. What is the dependent variable? Options-weather,temperature,coffee shops days,cups of coffiee 2. First calculate the value of bl. If necessary round off to the nearest integer 3. Next calculate the value of bO. If necessary round off to the nearest integer 4. Use your answer to the previous two questions to give the equation for the sample linear regression linc. Be sure to put it in equation form that will allow jason to predict the estimated number of cups sold for any given temperature. 5. Compute the value of r 2. Give three decimal places in your answer 6 Write a sentence that explains the meaning of r2 value you calculated in the previous question 7. Now we are going to conduct a hypothesis test to see if there is a significant relationship between sale of coffee and temperature Hypothesis are HOBI-o Ha:B10 Calculate the standard error of the estimate Se. give two decimal places in answer 8. What is the standard error of bl? Give two decimal places in answer if necessary 9. Find value of the t statistic. Give two decimal places in your answer if necessary 10. We use a 05 level of significance is the p value greater or less than 0 05 11. Conclusion in statistical term Options Fail to reject HO Reject HO Reject Ha Accept HO Fail to reject Ha

Answer 1

X	Y	(x-x̅)²	(y-ȳ)²	(x-x̅)(y-ȳ)
50	700	400.000	102400.000	-6400.000
60	500	100.000	14400.000	-1200.000
70	400	0.000	400.000	0.000
80	200	100.000	32400.000	-1800.000
90	100	400.00	78400.000	-5600.00

	ΣX	ΣY	Σ(x-x̅)²	Σ(y-ȳ)²	Σ(x-x̅)(y-ȳ)
total sum	350	1900	1000.000	228000.00	-15000
mean	70.00	380.00	SSxx	SSyy	SSxy

5)

R² =    (Sxy)²/(Sx.Sy) =    0.9868

6)

98.68% variation in variable y, is explained by varible x

7)

SSE=   (SSxx * SSyy - SS²xy)/SSxx =    3000.000
      
std error ,Se =    √(SSE/(n-2)) =    31.62

8)

estimated std error of slope =Se(ß1) = Se/√Sxx =    31.623   /√   1000   =   1.00

9)

t stat = estimated slope/std error =ß1 /Se(ß1) =    -15.0000   /   1.0000   =   -15.00

10)

Degree of freedom ,df = n-2=   3  
p-value =    0.0006  
decison :    p-value<α , reject Ho  

11)

Reject Ho