In: Statistics and Probability
(10) Considering the following time series data: (Tableau) A. Determine the least squares trend equation. Use a linear equation and any other nonlinear equation. Provide R-squared for both cases. B. Estimate the price of gold (ounce) for 2020. Does this seem like a reasonable estimate based on historical data? C. What is the quality of the forecast? Also, Provide Mean Absolute Error (MAE), and the Mean Absolute Percentage Error (MAPE).
Price of Gold (ounce) 2005 $513.00 2006 $635.70 2007 $836.50 2008 $869.75 2009 $1,087.50 2010 $1,420.25 2011 $1,531.00 2012 $1,664.00 2013 $1,204.50 2014 $1,199.25 2015 $1,060.00
CAN YOU PLEASE PROVIDE WITH STEPS ON TABLEAU. APPREICTAE IT THANK YOU
Solution:-
Given
x | y | |||
2005 | 513 | 25.00 | 336236.57 | 2899.30 |
2006 | 635.7 | 16.00 | 208994.43 | 1828.64 |
2007 | 836.5 | 9.00 | 65719.98 | 769.08 |
2008 | 869.75 | 4.00 | 49777.67 | 446.22 |
2009 | 1087.5 | 1.00 | 28.72 | 5.36 |
2010 | 1420.25 | 0.00 | 107184.81 | 0.00 |
2011 | 1531 | 1.00 | 191967.46 | 438.14 |
2012 | 1664 | 4.00 | 326201.94 | 1142.28 |
2013 | 1204.5 | 9.00 | 12463.69 | 334.92 |
2014 | 1199.25 | 16.00 | 11319.03 | 425.56 |
2015 | 1060 | 25.00 | 1079.72 | -164.30 |
total sum | 22110 | 12021.45 | 110 | 1310974.0 | 8125.20 |
mean | 2010.00 | 1092.86 |
sample size, n = 11
here,
estimated slope,
intercept,
So, regression line is
Predicted Y at X = 2020 is
damand | forcast | forecast error=demand value - forecast value | absolute forecast error | squared forcast error | Abs %error |
Dt | Ft | et=Dt-Ft | |et| | |et/Dt| | |
513 | 723.5318 | -210.53 | 210.53 | 44323.65 | 41.04% |
635.7 | 797.397 | -161.70 | 161.70 | 26146.01 | 25.44% |
836.5 | 871.263 | -34.76 | 34.76 | 1208.45 | 4.16% |
869.75 | 945.128 | -75.38 | 75.38 | 5681.87 | 8.67% |
1087.5 | 1018.994 | 68.51 | 68.51 | 4693.12 | 6.30% |
1420.25 | 1092.859 | 327.39 | 327.39 | 107184.81 | 23.05% |
1531 | 1166.725 | 364.28 | 364.28 | 132696.61 | 23.79% |
1664 | 1240.590 | 423.41 | 423.41 | 179276.03 | 25.45% |
1204.5 | 1314.455 | -109.96 | 109.96 | 12090.20 | 9.13% |
1199.25 | 1388.321 | -189.07 | 189.07 | 35747.81 | 15.77% |
1060 | 1462.186 | -402.19 | 402.19 | 161753.87 | 37.94% |
forecast error=demand value-forecast value | absolute forecast error | squared forcast error | Abs %error | |
et=Dt-Ft | |et| | |et/Dt| | ||
total sum = | 0.00 | 2367.17 | 710802.418 | 220.72% |
n = | 11 | 11 | 11 | 11 |
average = | 0.00 | 215.20 | 64618.40 | 20.07% |
MAD/MAE = = 215.20
MAPE = = 20.07%
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