Math Problem Statement

Consider the following data:

Monthly Profit of a GymMonth

Jan-12

Feb-12

Mar-12

Apr-12

May-12

Jun-12

Jul-12

Aug-12

Sep-12

Profit ($)

5,3505,350

5,1035,103

4,8244,824

4,4374,437

5,0805,080

5,3585,358

5,8195,819

6,0916,091

5,8375,837

Step 2 of 5 :  

What are the MAD, MSE and MAPE scores for the three-period moving average? Round any intermediate calculations, if necessary, to no less than six decimal places, and round your final answer to one decimal place.

Solution

To calculate the Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE) for a three-period moving average, we'll proceed with the following steps:

1. Calculate the Three-Period Moving Average:

The three-period moving average is calculated by averaging the profits of the previous three months. Since the first three months (Jan, Feb, and Mar) do not have three previous months to average, we start calculating the moving average from the fourth month (Apr-12).

Moving Average for Apr-12=(5,350+5,103+4,824)3=15,2773=5,092.333333\text{Moving Average for Apr-12} = \frac{(5,350 + 5,103 + 4,824)}{3} = \frac{15,277}{3} = 5,092.333333

Similarly, we calculate for the other months:

  • May-12: (5,103+4,824+4,437)3=14,3643=4,788.000000\frac{(5,103 + 4,824 + 4,437)}{3} = \frac{14,364}{3} = 4,788.000000
  • Jun-12: (4,824+4,437+5,080)3=14,3413=4,780.333333\frac{(4,824 + 4,437 + 5,080)}{3} = \frac{14,341}{3} = 4,780.333333
  • Jul-12: (4,437+5,080+5,358)3=14,8753=4,958.333333\frac{(4,437 + 5,080 + 5,358)}{3} = \frac{14,875}{3} = 4,958.333333
  • Aug-12: (5,080+5,358+5,819)3=16,2573=5,419.000000\frac{(5,080 + 5,358 + 5,819)}{3} = \frac{16,257}{3} = 5,419.000000
  • Sep-12: (5,358+5,819+6,091)3=17,2683=5,756.000000\frac{(5,358 + 5,819 + 6,091)}{3} = \frac{17,268}{3} = 5,756.000000

2. Calculate Errors:

For each month starting from Apr-12, calculate the error, which is the difference between the actual profit and the moving average.

Error=Actual ProfitMoving Average\text{Error} = \text{Actual Profit} - \text{Moving Average}

  • Apr-12: 4,4375,092.333333=655.3333334,437 - 5,092.333333 = -655.333333
  • May-12: 5,0804,788.000000=292.0000005,080 - 4,788.000000 = 292.000000
  • Jun-12: 5,3584,780.333333=577.6666675,358 - 4,780.333333 = 577.666667
  • Jul-12: 5,8194,958.333333=860.6666675,819 - 4,958.333333 = 860.666667
  • Aug-12: 6,0915,419.000000=672.0000006,091 - 5,419.000000 = 672.000000
  • Sep-12: 5,8375,756.000000=81.0000005,837 - 5,756.000000 = 81.000000

3. Calculate MAD (Mean Absolute Deviation):

MAD is the average of the absolute errors.

MAD=655.333333+292.000000+577.666667+860.666667+672.000000+81.0000006=3,138.6666676=523.1111\text{MAD} = \frac{| -655.333333 | + | 292.000000 | + | 577.666667 | + | 860.666667 | + | 672.000000 | + | 81.000000 |}{6} = \frac{3,138.666667}{6} = 523.1111

MAD ≈ 523.1

4. Calculate MSE (Mean Squared Error):

MSE is the average of the squared errors.

MSE=(655.333333)2+(292.000000)2+(577.666667)2+(860.666667)2+(672.000000)2+(81.000000)26=1,801,825.6666676=300304.2778\text{MSE} = \frac{(-655.333333)^2 + (292.000000)^2 + (577.666667)^2 + (860.666667)^2 + (672.000000)^2 + (81.000000)^2}{6} = \frac{1,801,825.666667}{6} = 300304.2778

MSE ≈ 300304.3

5. Calculate MAPE (Mean Absolute Percentage Error):

MAPE is the average of the absolute percentage errors. For each month:

MAPE=655.3333334,437×100+292.0000005,080×100++81.0000005,837×1006\text{MAPE} = \frac{| \frac{-655.333333}{4,437} | \times 100 + | \frac{292.000000}{5,080} | \times 100 + \cdots + | \frac{81.000000}{5,837} | \times 100}{6}

MAPE=14.767296+5.748032+10.793493+14.791356+11.033986+1.3883636=9.7534\text{MAPE} = \frac{14.767296 + 5.748032 + 10.793493 + 14.791356 + 11.033986 + 1.388363}{6} = 9.7534

MAPE ≈ 9.8%

Final Results:

  • MAD: 523.1
  • MSE: 300304.3
  • MAPE: 9.8%

Would you like further details or have any questions?

Related Questions:

  1. What are the implications of a high MSE in this context?
  2. How does MAPE differ from MAD and MSE in practical use?
  3. Can you explain the advantages of using a three-period moving average?
  4. What might cause large errors in the moving average predictions?
  5. How would the calculations change if a four-period moving average was used?

Tip:

Always check for outliers or significant changes in your data when calculating moving averages, as these can distort your results.

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Math Problem Analysis

Mathematical Concepts

Statistics
Time Series Analysis

Formulas

Mean Absolute Deviation (MAD)
Mean Squared Error (MSE)
Mean Absolute Percentage Error (MAPE)
Moving Average

Theorems

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Suitable Grade Level

Advanced High School