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A firm recorded its sales (Qt) in monthly observations from January 2013 to August 2014. The data collected is shown in the table below: Sales

A firm recorded its sales (Qt) in monthly observations from January 2013 to August 2014. The data collected is shown in the table below: 

Sales ($ Thousands)

Qt

Jan-13

46

Feb-13

56

Mar-13

72

May-13

67

Jun-13

77

Aug-13

66

Sep-13

69

Oct-13

79

Dec-13

88

Jan-14

91

Mar-14

94

Apr-14

104

Jun-14

100

Jul-14

113

Aug-14

120


a. Below is the output:


Regression Statistics
Multiple R0.960795768
R Square0.923128508
Adjusted R Square0.917215316
Standard Error6.064850994
Observations15
ANOVA     
 dfSSMSFSignificance F
Regression15742.2285715742.228571156.11340821.28554E-08
Residual13478.171428636.78241758  
Total146220.4   
Dependent var: QtCoefficientsStandard Errort StatP-value
Intercept46.573.3014.132.87E-09
t4.530.3612.491.29E-08


b. The intercept (a) is 46.57. It tells us the value of Sales that is not dependent on time.

c. The slope term (b) is 4.53. It tells us the change in Sales when the time increases by 1 month.

d.

140 y 4.5286x + 46.571 R2 0.9231 100 80 60 40 20 0 1 2 3 45 6 789 10 11 12 13 14 15 16 Months


 

e. Forecast the level of sales in August 2015. Show your result in the chart.

f. Forecast the level of sales for August 2018. Don’t need to show it in the chart.

g. Which forecast is more reliable, 2015 or 2018? Why? Explain.


140 y= 4.5286x + 46.571 120 R= 0.9231 100 80 60 40 20 3 4 6. 7 10 11 12 13 14 15 16 Months Sales

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