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Analyze some Data

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Αναρτήθηκε περίπου 7 χρόνια πριν

$10-30 USD

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Consider the data on new orders for computers and electronic products and the M1 money supply for the years 2011 through 2014. Year Month New Orders for Computers and Electronic Products M-1 Money Supply 2011 1 19222 1855.6 2011 2 20727 1874.7 2011 3 24893 1892.0 2011 4 19375 1897.8 2011 5 20152 1934.3 2011 6 25075 1947.0 2011 7 18615 2001.5 2011 8 21289 2112.9 2011 9 27014 2126.0 2011 10 22179 2137.4 2011 11 20761 2172.0 2011 12 27818 2168.2 2012 1 19447 2202.3 2012 2 23043 2212.2 2012 3 26734 2228.7 2012 4 21897 2245.3 2012 5 22403 2251.0 2012 6 24942 2262.3 2012 7 19365 2314.6 2012 8 20240 2346.5 2012 9 25478 2383.6 2012 10 20790 2415.5 2012 11 20362 2423.2 2012 12 27841 2457.7 2013 1 17393 2467.6 2013 2 18725 2470.4 2013 3 22919 2474.8 2013 4 19560 2511.0 2013 5 20333 2522.0 2013 6 24619 2517.9 2013 7 18065 2545.6 2013 8 18487 2557.3 2013 9 24877 2578.8 2013 10 20410 2620.2 2013 11 20194 2622.2 2013 12 24955 2654.5 Using the data for computer and electronic products, develop a three-period MA(3), four-period MA(4), and five-period MA(5) moving average forecasts. Using the same data, develop a weighted moving average forecast where the weight of the most recent data (t-1) is 0.55, 0.20 for period (t-2), 0.15 for period (t-3), and 0.10 for period (t-4). Using the same data, develop exponential smoothing forecasts with an alpha (α) of 0.75 and 025. Assume the first month forecast is the same as the actual data. Using the same data, develop a time-series trend forecast using regression analysis. Using the same data, develop a causal model forecast using the M1 Money Supply data as the independent variable. Using either MSE or MAD, determine which forecast is best. Extra Credit - This extra credit is worth an additional 20 points on this assignment. It must be entirely correct. No partial credit will be given. Develop a time series decomposition forecast for the computer and electronic products. You must first determine the seasonal (monthly indexes) and then divide the data by these indices. Then using the deseasonalized data, determine the trend. Finally, you must re-seasonalize the data.
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Greetings sir, i am an expert freelancer for this job and your 100% satisfaction is assured if you allow me to serve. Here is the reason. Why you should pick me? a) I am a very expert and have the same kind of experience of 5 years. b) I work very hard (16+ hours a day and 7 days a week) and also very fast so... it will be done very soon than most of the other providers c) And most important part is my policy: "I will give you (to my client) life time support (as long as you keep relation with me). And fix any bugs/problem without any cost. So, don't ever worry about me” Please sir, leave a reply ASAP, as I am waiting for your kind reply
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I know what do you want and i have more skill about your project. So contact with me about your project done in time with your budget.
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A proposal has not yet been provided
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Dear Hiring Manager, I have gone trough a bid to your job and very much interested to work with you. I am also very expert in this field. I hope I will be the right candidate for your job. Awaiting an affirmative response from you. Best Regards Rabiul Islam
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I just don't know the casual loop forecasting and you need to explain extra work part more clearly. Other parts I can accomplish. Best
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Being a graduate from one of the top 5 premier MBA colleges of India, XLRI Jamshedpur, I have gained enough expertise in Microsoft office. I can do all sorts of analysis in excel which includes commands such as Vlookup, Hlookup etc along with Data solver, goal seek and Data analysis. I am fairly comfortable with techniques such as correlation, regression, logistic regression etc What your project demands is basic operations management techniques which can be easily done in 1 day.
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