Source: Time Series Data Library www.datamarket.com MONTHLY MINNEAPOLIS PUBLIC DRUNKENNESS INTAKES JAN.’66-JUL’78 Meghan Burke.

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Source: Time Series Data Library MONTHLY MINNEAPOLIS PUBLIC DRUNKENNESS INTAKES JAN.’66-JUL’78 Meghan Burke

GOALS  Provide a descriptive analysis of this time series  Develop the best models to forecast future monthly Minneapolis public drunkenness intakes  Understand the time series structure

INITIAL TIME SERIES PLOT

TIME SERIES COMPARISON Initial Adjusted

TIME SERIES COMPARISON Initial Adjusted

MODEL COMPARISONS  Best Smoothing Models:  Seasonal Exponential Smoothing  Winters Method  ARIMA (0, 0, 1)

SEASONAL EXPONENTIAL SMOOTHING

WINTERS METHOD

ARIMA (0,0,3)

FORECAST PREDICTIONS FROM THE EXPONENTIAL SMOOTHING MODELS

COMPARING FORECAST PREDICTIONS  Best Smoothing Model  Seasonal Exponential Smoothing ModelMAPEMAE Seasonal Exponential Smoothing % Winters Method % ARIMA (0,0,3) %

CITATION  David E. Aaronson, C. Thomas Dienes, and Michael C. Musheno,Changing the Public Drunkenness Laws: The Impact of Decriminalization, 12Law & Soc'y Rev.405 (1977), Available at: