| | |1. Smith Machine Parts |Forecasting | | | |2. Independent Questions |Forecasting | | | |3. Product X |Forecasting | | | |4. Seaside Inc
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9/5/14 Chapter 5 Forecasting To accompany Quantitative Analysis for Management‚ Tenth Edition‚ by Render‚ Stair‚ and Hanna Power Point slides created by Jeff Heyl © 2008 Prentice-Hall‚ Inc. © 2009 Prentice-Hall‚ Inc. Introduction n Managers are always trying to reduce uncertainty and make better estimates of what will happen in the future n This is the main purpose of forecasting n Some firms use subjective methods n Seat-of-the pants methods‚ intuition‚ experience n There are also
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"Patton is not remembered because he was a coward‚ or passive‚ he is remembered because he was an exceptional general with strong character and an aggressive nature." Patton the Legend By: Christopher Klein. Though now his name is synonymous with fighting on the European front. Patton’s aggressive tendencies made headlines when he was caught slapping his soldiers for being cowards‚ this created enemies among American generals. On December 6‚ 1945‚ a truck ran into Patton‚ leaving him paralyzed. He
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your data and processes. ERP also streamline every department workflows for better decision making and growth. An ERP software package can help your business in many ways some of them are as follows: • ERP helps in streamlining your Business Process and Workflows • It helps you in better customer support and services • You gain real time data from various departments allowing quick and powerful decision making • Reduce paper work‚ duplication of entries and Manual entries. To summarize ERP system
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5/7/08 4:42 PM Page 52 C H A P T E R Forecasting Models 5 TEACHING SUGGESTIONS Teaching Suggestion 5.1: Wide Use of Forecasting. Forecasting is one of the most important tools a student can master because every firm needs to conduct forecasts. It’s useful to motivate students with the idea that obscure sounding techniques such as exponential smoothing are actually widely used in business‚ and a good manager is expected to understand forecasting. Regression is commonly accepted as a tool
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Content Introduction 1 Part 1. Examine the data‚ looking for seasonal effects‚ trends and cycles 2 Part2. Dummy Variables Model 3 Linear trend model 3 Quadratic trend model 5 Cubic trend model 7 Part 3. Decomposition and Box-Jenkins ARIMA approaches 8 First difference: 10 a. Create an ARIMA (4‚ 1‚ 0) model 10 b. Create an ARIMA (0‚ 1‚ 4) model 11 c. Create an ARIMA (4‚ 1‚ 4) 11 d. Model overfitting 12 Second difference 13 Forecast based on ARIMA (0‚ 1‚ 4) model 13 Return
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1) Raw data‚ not seasonalized 2) Seasonal Adjustment used: Census II X-12 multiplicative (MASA): Used because of the presence of seasonal variations that are increasing with the level of my series. Increasing degree of variability overtime… TX non seasonalized and seasonalized 3) Combined seasonally adjusted with non-seasonally adjusted De-seasonalizing the data helped with the removal of seasonal component that creates higher volatility in model. Now‚ variations
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General Patton was removed from command in Sicily and secretly brought to England. General Eisenhower‚ Supreme Commander of the Allied forces‚ had two jobs for Patton to do. Eisenhower had selected Patton to command the Third Army‚ which was still in the United States. He was to make the Third Army combat ready for deployment in France after the invasion. Patton’s command of the Third Army was kept secret. Eisenhower also wanted General Patton to be the commander of the First United States Army Group
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c. ratio scale d. interval scale 2. Data obtained from a nominal scale a. must be alphabetic b. can be either numeric or nonnumeric c. must be numeric d. must rank order the data 3. In a post office‚ the mailboxes are numbered from 1 to 4‚500. These numbers represent a. qualitative data b. quantitative data c. either qualitative or quantitative data d. since the numbers are sequential‚ the data is quantitative 4. A tabular summary of a set of data showing the fraction of the total number
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discussed and all concluded that data analysis methods help us understand facts‚ observe patterns‚ formulate explanations‚ and try out the hypotheses. Not only does it help us understand facts‚ but they we also discovered that data analysis is used in science and business‚ and even administration and policy-making processes. We’ve found out the data analysis can be carried out in all fields‚ including medicine and social sciences. Once an analysis is conducted the data that is carried out is documented
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