6-7 Page Case study
Total worth: 40 points (+5 for enrichment)
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Elements |
Omitted |
Needs Improvement |
Acceptable |
Target |
Score |
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Develop a time series plot and identify seasonality Full Credit: (5 points) |
0 points Failed to attempt or effort adds no value |
1 point Paper is poorly written and time series is missing or very inaccurate. Does not address seasonality. |
3 points Writing is average and with the time series included and mostly correct. |
5 points Paper is well written with time series plot included (represented in yearly time frames to illustrate) and seasonality identified. |
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Exponential smoothing is illustrated and mentions appropriateness for data set is mentioned. Full Credit: (5 points) |
0 points Failed to attempt or effort adds no value |
1 point Exponential smoothing is missing / no explanation of its meaning. |
3 points Exponential smoothing included but computed incorrectly with faulty explanation. |
5 points The Exponential smoothing is included and correct with detailed, accurate explanation. |
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Use regression to build a linear trend model. Comment on the goodness-of-fit of this model. How well does R2 explain the variance in the data? Full Credit: (5 points) |
0 points Failed to attempt or effort adds no value |
1 point The regression or linear trend is missing/not included. Does not cover how R2 explains the variance in the data.
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3 points The regression / linear trend is included but has some errors with faulty description |
5 points The regression and linear trend is included and correct with detailed description. |
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Determine seasonality indices and apply them to the trend to form the final forecast for 2007 Full credit: (7 points) |
0 points Failed to attempt or effort adds no value |
1 point The seasonality indices are missing/computed incorrectly |
4 points The seasonality indices are added to the linear trend but has some errors with faulty description |
7 points The regression trend with seasonality is included and correct with detailed description. |
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Plot the predictions for both approaches and shows how the technique fit the data Full credit: (7 points) |
0 points Failed to attempt or effort adds no value |
1 point Incorrect answer but includes graph or description in attempt to partially answer the question. |
4 points Attempts to measure accuracy of the predictions using MAD, MSE or MAPE measures with some errors |
7 points Correct answer using one of the measures – MAD, MSE or MAPE - with detailed description. |
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Make forecasts for the next 12 months of 2007 using these techniques Full credit: (7 points) |
0 points Failed to attempt or effort adds no value |
1 point omitted with to no explanation. |
4 points info included but partly incorrect with limited description. |
7 points information is included and correct; detailed description in discussion. |
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Give recommendation on making accurate forecasts for 2007 based on MAPE. Full credit: (4 points) |
0 points Failed to attempt or effort adds no value |
1 point No recommendations included and/or poorly written descriptions. |
2 points Includes recommendation with minimal supporting evidence. |
4 points Thoughtful recommendation with strong evidence supporting the recommendation |
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Enrichment (+5) |
0 Points No submittal |
1 point No recommendations included and/or poorly written descriptions. |
3 points Includes recommendation with minimal supporting evidence. |
5 points … uses Solver properly to determine alpha while minimizing MSE |
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