OPR1010 Operations Management (Winter 2010) In-class Assignment 2: Forecasting Directions: ( We will check the answers during the supplemental session on Feb. 18. (Participation points will be considered for volunteers. (This is not a take-home assignment. You do not have to turn in the answers. (Use MS-Excel for Questions 1 through 4. Q-1. The Polish General’s Pizza Parlor is a small restaurant catering to patrons with a taste for European Pizza. One of its specialties is Polish Prize
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risks of material misstatement of accounting estimates made in the current period financial statements. However‚ the review is not intended to call into question the judgments made in the prior periods that were based on information available at the time. A42 The auditor may judge that a more detailed review is required for those accounting estimates that were identified during the prior period audit as having high estimation uncertainty‚ or for those accounting estimates that have changed significantly
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Review 4 Analysis 5 Conclusion 8 Appendix 9 Introduction The purpose of this project is to investigate the co-movements of Jamaica and Trinidad and Tobago Treasury bill rates‚ as well as to investigate whether the US Treasury bill rate Granger Cause the movement of the Treasury bill rates of both Caribbean islands. To study the co-movements between the Treasury rates‚ we will determine if there is a long run relationship between the two series using co-integration
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FORECASTING FUNDAMENTALS Forecast: A prediction‚ projection‚ or estimate of some future activity‚ event‚ or occurrence. Types of Forecasts * Economic forecasts * Predict a variety of economic indicators‚ like money supply‚ inflation rates‚ interest rates‚ etc. * Technological forecasts * Predict rates of technological progress and innovation. * Demand forecasts *
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Introduction Examples • Why forecast? • Why understand uncertainty of forecast? • What information to use in forecast? STAT 443: Forecasting Example: Accidental deaths Reza Ramezan Introduction Examples • Many examples are time series– forecast what happens in future • Example: monthly number of accidental deaths in USA- 1973-79 • Look at structure of data STAT 443: Forecasting Example: Accidental deaths
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Types of Forecasts: Judgmental Time Series Associative Models Judgmental Forecasts: Executive opinions Sales force Composite Consumer surveys Outside opinion Opinions of managers/staff Delphi technique Time Series Forecasts Level-Long-term “base” of the data Trend- long-term upward or downward movement in data Seasonability- short-term regular variations in data at constant time intervals Cyclicity- long term variations due to economic cycle Random variations- Caused by chance. Unpredictable-
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averages‚ assign a value of 1 to the data for 20X2‚ a value of 2 to the data for 20X3‚ and a value of 3 to the data for 20X4. Forecast personnel expenses for fiscal year 20X5 using moving averages‚ weighted moving averages‚ exponential smoothing‚ and time series regression. Moving Averages Fiscal Year Expenses 20X2 $5‚500‚000 20X3 $6‚000‚000 20X4 $6‚750‚000 20X2-4 $18‚250‚000 20X5 $18‚250‚000/3 = $6‚083‚333 Weighted Averages Fiscal
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Index Cover Page 1 1. Executive Summary 3 2. Background 3 3. Issue Statement 4 4. Analysis of the problem 4-9 1. Moving Average 4-6 2. Holt Winters’ Exponential Smothing 6-7 3. Simple Average 7 3. Exponential Smothing 8-9 5. Recommandations 10 6. References 11 Executive Summary In the given case study‚ Snow the revenue manager of the Hamilton hotel has to make a decision which is to accept the group of not for 22nd August. As it is a business hotel and generally it
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PERENCANAAN & PENGENDALIAN PRODUKSI TIN 4113 Pertemuan 2 • Outline: – – – – – Karakteristik Peramalan Cakupan Peramalan Klasifikasi Peramalan Metode Forecast: Time Series Simple Time Series Models: • Moving Average (Simple & Weighted) • Referensi: – Smith‚ Spencer B.‚ Computer Based Production and Inventory Control‚ Prentice-Hall‚ 1989. – Tersine‚ Richard J.‚ Principles of Inventory and Materials Management‚ Prentice-Hall‚ 1994. – Pujawan‚ Demand Forecasting Lecture Note‚ IE-ITS‚ 2011
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Eight Steps to Forecasting • Determine the use of the forecast □ What objective are we trying to obtain? • Select the items to be forecast • Determine the time horizon of the forecast □ Short time horizon – 1 to 30 days □ Medium time horizon – 1 to 12 months □ Long time horizon – more than 1 year • Select the forecasting model(s) |Description |Qualitative Approach |Quantitative Approach
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