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# Reminders - PowerPoint PPT Presentation

Reminders. HW 3 Posted HW 1 Graded and Posted Grading appeal process. MGTSC 352. Lecture 6: Forecasting Wrap-up of Forecasting Holdout strategy Debugging Forecasting Models Monte Carlo Simulation Playing Roulette with Excel Bard Outside example. 95% Prediction Interval.

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Presentation Transcript

• HW 3 Posted

• HW 1 Graded and Posted

### MGTSC 352

Lecture 6: Forecasting

Wrap-up of ForecastingHoldout strategyDebugging Forecasting Models

Monte Carlo SimulationPlaying Roulette with ExcelBard Outside example

• Technically correct formula;

• Forecast + Bias + 2 x Std Error

• Heuristic for use in this class;

• Forecast  2  SE

Steps in a Forecasting Project

-1: Collect data

0: Plot the data (helps detect patterns)

1: Decide which models to use

• level – SA, SMA, WMA, ES

• level + trend – SLR, DES

• level + trend + seas. – TES, SLR w SI, ...

2: Use models

3: Compare and select (one or more)

4: Generate forecast and range (prediction interval)

More on selection

Nonlinear (ex. power)

linear

S-curve (ex. any CDF)

Number of calls / month

Trend?

Seasonality?

Number of calls / month

Avg. # of calls / hr., 2004

How to select a model?

• Look at performance measures

• Use holdout strategy

• Example: 4 years of data

• Use first 3 years to fit model(s)

• Forecast for Year 4 and check the fit(s)

• Select model(s)

• Refit model(s) adding Year 4 data

• If you have more than one good model...

• COMBINE FORECASTS

TES vs. SLR w SI Dealers (Both optimized to minimize SE)

Which method would you choose?

One possibility: Dealers Combining Forecasts

TES

SLR w SI

weight

+ (1 - weight)

Minimize SE of the combined forecast to find the best weight

Holdout Strategy Dealers

• Ignore part of the data (the “holdout data”)

• Build models using the rest of the data

• Optimize parameters

• Forecast for the holdout data

• Calculate perf. measures for holdout data

• Choose model that performs best on holdout data

• Refit parameters of best model, using all data

holdout Dealers period

TES vs. SLR w/ SI…in holdout period

TES vs. SLR w SI … Dealers … in holdout period

Now which method would you choose?

Holdout Strategy Recap Dealers

• Performance during holdout period: a.k.a. “out of sample” performance

• In other words: how well does the method perform when forecasting data it hasn’t “seen” yet?

• Question: Why is SE during holdout period worse than SE during “training period”?

• Forecasting software survey

• http://lionhrtpub.com/orms/surveys/FSS/FSS.html

• General statistics program

• Minitab, NCSS, SAS, Systat

• Dedicated forecast software

• AutoBox, Forecast Pro (MGTSC 405)

Do Spreadsheet Models Dealers Have Errors?

• What are the consequences of spreadsheet errors?

• Incorrect financial statements

• Bad publicity, loss of investor confidence

• Lawsuits

• Loss of election

• See http://www.eusprig.org/stories.htm for more

• Before entering a formula:

• Pause and predict the result

• After entering a formula:

• Double-click to see where numbers are coming from

• Try simple test values: 0, 1

• ctrl+~ – use to look for breaks in patterns

To Excel

Playing roulette with Excel Dealers

To Excel …

Game 1 Dealers

• Spin the spinner once

• Payoff = (spinner outcome)  (\$1 Million)

• Q1: What would you pay to play this game?

• Q2: Suppose the game were played 10,000 times. What do you think the payoff distribution will look like?

Game 2 Dealers

• Spin the spinner twice

• Payoff = (\$1 Million) x (spinner outcome 1 + spinner outcome 2)/2 Q1: What would you pay to play this game?

• Q2: Suppose the game were played 10,000 times. What do you think the payoff distribution will look like?

• Simulate one spin: =RAND()

• Repeat 10,000 times

• Plot histogram

• To Excel

Pg. 43 Dealers

Excel Details

• Using Data tables to replicate a simulation

• Enter replication numbers (1, …, n) in leftmost column

• Enter formulas for outputs in top row

• Highlight table

• Data  Table …

• Column input cell: any empty cell

“Freezing” simulated values: Dealers

Copy the values

Paste special …  values

Generate sample

Enter “bins” values

Highlight range where frequencies should be calculated

=FREQUENCY(sample, bins)

“Ctrl + shift + enter” instead of just “enter.”

More Excel Details

Bard Outside Dealers

• The Bard Outside theatre group puts on plays by Shakespeare 20 times every summer in a 200-seat outdoor theatre.

• Data:

• Attendance and weather (rain / no rain) for last five seasons (5 x 20 = 100 shows)

• Revenue = \$10 per customer

• Cost = \$1,600 per show

• Question: how much would profit increase if the number of seats were increased?

Data Analysis Dealers

• What’s the probability of rain?

• What is the mean and standard deviation of demand when it rains?

• How about when it doesn’t rain?

• How can we simulate demand?

To Excel …

Simulating Profit per show Dealers

• Simulate weather

• Simulate demand

• Make sure 0 ≤ demand ≤ capacity

• Calculate revenue

• Subtract cost

• Replicate!

• Remember: freeze tables of simulation results

Final results Dealers