c. Interpret the quarterly compound growth rate. d. Interpret the first quarterl
ID: 3222924 • Letter: C
Question
c. Interpret the quarterly compound growth rate.
d. Interpret the first quarterly multiplier.
e. What are the forecasts for 2012-Q3, 2012-Q4, and all four quarters of 2013?
*Can you please explain step by step how to do this on Excel or MiniTab? I don't know where to start on Part B.
Quarter Coded_Quarter Revenue Q1 Q2 Q3 1996-Q1 0 1490 1 0 0 1996-Q2 1 1589 0 1 0 1996-Q3 2 1742 0 0 1 1996-Q4 3 4535 0 0 0 1997-Q1 4 1626 1 0 0 1997-Q2 5 1740 0 1 0 1997-Q3 6 1906 0 0 1 1997-Q4 7 4689 0 0 0 1998-Q1 8 2024 1 0 0 1998-Q2 9 2041 0 1 0 1998-Q3 10 2180 0 0 1 1998-Q4 11 4983 0 0 0 1999-Q1 12 2140 1 0 0 1999-Q2 13 2196 0 1 0 1999-Q3 14 2460 0 0 1 1999-Q4 15 5116 0 0 0 2000-Q1 16 2320 1 0 0 2000-Q2 17 1984 0 1 0 2000-Q3 18 2258 0 0 1 2000-Q4 19 4853 0 0 0 2001-Q1 20 2074 1 0 0 2001-Q2 21 1991 0 1 0 2001-Q3 22 2154 0 0 1 2001-Q4 23 4687 0 0 0 2002-Q1 24 2081 1 0 0 2002-Q2 25 2094 0 1 0 2002-Q3 26 2280 0 0 1 2002-Q4 27 4784 0 0 0 2003-Q1 28 2137 1 0 0 2003-Q2 29 2127 0 1 0 2003-Q3 30 2274 0 0 1 2003-Q4 31 4834 0 0 0 2004-Q1 32 2025 1 0 0 2004-Q2 33 2034 0 1 0 2004-Q3 34 2212 0 0 1 2004-Q4 35 5170 0 0 0 2005-Q1 36 2155 1 0 0 2005-Q2 37 2070 0 1 0 2005-Q3 38 2147 0 0 1 2005-Q4 39 4783 0 0 0 2006-Q1 40 2384 1 0 0 2006-Q2 41 2455 0 1 0 2006-Q3 42 2563 0 0 1 2006-Q4 43 5822 0 0 0 2007-Q1 44 2608 1 0 0 2007-Q2 45 2609 0 1 0 2007-Q3 46 2778 0 0 1 2007-Q4 47 5783 0 0 0 2008-Q1 48 2751 1 0 0 2008-Q2 49 2766 0 1 0 2008-Q3 50 2721 0 0 1 2008-Q4 51 5507 0 0 0 2009-Q1 52 2467 1 0 0 2009-Q2 53 2590 0 1 0 2009-Q3 54 2702 0 0 1 2009-Q4 55 5816 0 0 0 2010-Q1 56 2649 1 0 0 2010-Q2 57 2593 0 1 0 2010-Q3 58 2750 0 0 1 2010-Q4 59 5948 0 0 0 2011-Q1 60 2685 1 0 0 2011-Q2 61 2673 0 1 0 2011-Q3 62 2736 0 0 1 2011-Q4 63 5925 0 0 0 2012-Q1 64 2660 1 0 0 2012-Q2 65 2515 0 1 0 The accompanying data are quarterly revenues (in $millions) for a certain toy store chain from 1996-Q1 hrough 2012-Q2. Complete parts (a) through (e) below. EEE Click the icon to view the data table. O B. O D. Coded Quarter Coded Quarter Coded Quarter Coded Quarter and Q1, Q2, and Q3 are the quarter 1, 2, and 3 dummy variables, is of revenue, Xi is the it h coded quarter, b. Develop an exponential end forecasting equation with quarterly c In this equation Yi the ith value respectively ogYi (Round to four decimal olaces as needed.)Explanation / Answer
Here we have to find regression equation.
Response variable : Revenue
Explanatory variables : coded quarter,, Q1,Q2 and Q3.
Now we have to fit regression of revenue on coded quarter, Q1, Q2 amd Q3.
This we can done in MINITAB.
steps :
ENTER data into MINITAB sheet --> STAT --> Regression --> Regression --> Response : log(revenue)--> Predictors : select all the three variables --> Results : select second option --> ok --> ok
————— 4/18/2017 11:11:59 AM ————————————————————
Regression Analysis: log(revenue) versus Coded_Quarter, Q1, Q2, Q3
The regression equation is
log(revenue) = 8.34 + 0.00633 Coded_Quarter - 0.840 Q1 - 0.850 Q2 - 0.786 Q3
Predictor Coef SE Coef T P
Constant 8.34353 0.02487 335.53 0.000
Coded_Quarter 0.0063292 0.0004891 12.94 0.000
Q1 -0.84007 0.02636 -31.87 0.000
Q2 -0.85013 0.02636 -32.26 0.000
Q3 -0.78574 0.02676 -29.37 0.000
S = 0.0756684 R-Sq = 96.4% R-Sq(adj) = 96.2%
Analysis of Variance
Source DF SS MS F P
Regression 4 9.3493 2.3373 408.22 0.000
Residual Error 61 0.3493 0.0057
Total 65 9.6986
First quartelry multiplier = -0.840
Interpretation : If we fixed all the variables except Q1 then one unit change in Q1 will be -0.840 decrease in log(revenue).
e. What are the forecasts for 2012-Q3, 2012-Q4, and all four quarters of 2013?
These forecasts we can find using regression equation.
The regression equation is
log(revenue) = 8.34 + 0.00633 Coded_Quarter - 0.840 Q1 - 0.850 Q2 - 0.786 Q3
forecast for 2012-Q3 is :
plug coded quarter = 2, Q1=0, Q2 = 0 and Q3=1
log(revenue) = 8.34 + 0.00633*2- 0.840 *0 - 0.850*0 - 0.786*1
= 7.57
forecast for 2012-Q4 is :
plug coded quarter = 3, Q1=0, Q2 = 0 and Q3=0
log(revenue) = 8.34 + 0.00633*3- 0.840 *0 - 0.850*0 - 0.786*0
= 8.36
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