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- Suppose a researcher aims to investigate the relationship of investment and growth of XYZ organization for the past 2.5 decades. Which type of time horizon should he used? a. a & b is correct b. Cross-sectional data c. Time Series data d. Panel dataFor the E-Commerce Retail Sales (Million$) data given in the table below, provide estimates from the 1st Quarter (Q1) of 2016 to the 3rd Quarter (Q3) of 2017 by using two models: 1) Single Exponential Smoothing with α=0.3 2) Moving Average with k=2. Calculate MAPE for each model. Quarter Year Actual Q1 2016 86802 Q2 2016 92004 Q3 2016 93795 Q4 2016 124651 Q1 2017 99491 Q2 2017 106590 Q3 2017 108291 Compare two models above (Single Exponential Smoothing and Moving Average) based on their accuracies. Which forecasting method appears to be better? Using the model you choose, provide forecast for the 4th Quarter (Q4) of 2017. Assuming that this model is overestimating, find the actual value of the Q4 of 2017 based on MAPE value. Some residual graphs from the first forecast model (including wider range of E-Commerce Retail Sales data) are given below. What do these graphs tell about the model? Explain each graph.d. Now based on regression analysis predict the number of patients that Dr. Fok will see in year 11 and 12 based on the forecasted Robbery Rate - year 11 is 117.1 and year 12 is 120.8. e. What is the MAD? f. What is the correlation Coefficient – r-value? % g. Based on the overall analysis, how well does each model fit the data?
- The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week of Pints Used August 31 360 September 7 370 September 14 412 September 21 383 September 28 371 October 5 371 a) The forecasted demand for the week of October 12 using a 3-week moving average= {__] Pints (round your response to two decimal places).The following table shows a tool and die company’s quarterly sales for the current year. What sales would you predict for the first quarter of next year? Quarter relatives are SR1 = 1.10, SR2 = .99, SR3 = .90, and SR4 = 1.01.Quarter 1 2 3 4Sales 88 99 108 141.4year quarterly sales (000 units) Q1 Q2 Q3 Q4 2016 1300 1500 1200 2000 2017 1600 1800 1100 2200 2018 1700 1900 1300 2300 2019 1800 2100 1400 2500 Using a simple regression analysis, determine the trend equation of the sales and use it to estimate the number of units of clothing sold throughout the fiscal year 2020. Assume that Q1 of 2016 is 1, Q2 of 2016 is 2, etc. Show all relevant cakculation detail
- Given the attached data. Answer the following questions for a 7 period moving average. t At 1 5477 2 3338 3 4799 4 2852 5 6332 6 8385 7 4382 8 4184 9 14229 10 10385 11 11676 12 5271 13 8938 14 9279 15 13990 16 2890 17 13027 18 8970 19 6700 20 7065 21 12491 22 8748 23 8396 24 6102 25 7559 26 7997 27 11981 28 10680 29 5783 30 2501 31 7620 32 10194 33 7908 34 11985 35 5863 36 3024 37 8758 38 1640 39 6569 40 11728 41 6659 42 2830 43 10018 44 8448 45 12409 46 2083 47 6374 48 7438 49 4576 50 4795 MAD = Average(|A-F|) TS =SUM(A-F)/MAD MSE = Average(A-F)2 1. Compute your forecast for period 51. The potential answers are: A: 11221.6 units. B: 12461 units. C: 8020.83 units. D: 4414 units. E: 6589 units.Johnson Plastics Inc. produces cases for CDs. The accounting manager has performed a regression analysis to determine future production costs. The regression estimate is $5,000, with anR-squared of .9, a t-value of 2.5, and a standard error (SE) of $400. Within what interval would shebe reasonably (67%) confident that the actual values will fall?Exercise III States of NatureAlternatives S1 S2 p 0.6 0.4Option 1 200 300Option 2 50 350 Compute EVPI.
- Mr. Ferdinand is a well known entrepreneur who sells fresh organic beef to persons in the localcommunity. Customers love the quality of meet that Mr. Ferdinand sells so they tend torecommend his product to other persons. Recently, Mr. Ferdinand has been running out of beefto sell to his customers. One customer suggests to him that he must use past sales records toforecast demand for his beef so that he can meet his customers demand.I. Using a numerical example, demonstrate to Mr. Ferdinand how he can use a threeweek and a four-week weighted moving average to forecast demand for his beef.II. Show how Mr. Ferdinand can test the accuracy of his forecast. III. Explain to Mr. Ferdinand two ways in which he can benefit from doing forecast forhis beef.Mr. Ferdinand is a well known entrepreneur who sells fresh organic beef to persons in the localcommunity. Customers love the quality of meet that Mr. Ferdinand sells so they tend torecommend his product to other persons. Recently, Mr. Ferdinand has been running out of beefto sell to his customers. One customer suggests to him that he must use past sales records toforecast demand for his beef so that he can meet his customers demand. I. Using a numerical example, demonstrate to Mr. Ferdinand how he can use a three week and a four-week weighted moving average to forecast demand for his beef.II. Show how Mr. Ferdinand can test the accuracy of his forecast. III. Explain to Mr. Ferdinand two ways in which he can benefit from doing forecast forhis beef.Chart and Regression analysis : What does the intercept predict? X: C16 (number of cars on the sales lot) versus Y: C17 (cars sold per day) Equation: y=2.9x + 14.5 Slope:2.9 Intercept:14.5 Does the intercept mean the intercept is 14.5 means that the cars sold per day( Y) predicted number of cars on sale lot(X) to be 14.5, but this intercept has no meaning. So, I will not use to predict cars sold per day?