The table below shows manufacturing hourly earnings for a region over a period of8 months. Use the Holt-Winters procedure with smoothing constants α = 0.4 andB = 0.4 to obtain forecasts for the next 3 months.Month12344567c8Hourly Earnings10.5410.6710.4310.5910.6710.7810.7610.84CFind the forecasted values for the next three months. Complete the tablebelow.Month910Hourly Earnings11(Round to two decimal places as needed.)

Given the data as Month Hourly Earnings 1 10.54 2 10.67 3 10.43 4 10.59 5 10.67 6…

Answered: The table below shows manufacturing…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Consider the following data: Month Jan-14 Feb-14 Profit ($) 16,113 16,263 Monthly Profit of an Auto Repair Shop Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 15,055 17,117 18,763 17,210 19,141 18,468 20,254 Step 3 of 4: Determine the exponential smoothing forecast for the next time period using a smoothing constant of 0.35. If necessary, round your answer to one decimal place.
Suppose that a regression line is found to be ý = 0.5470x +7.7000 What is the predicted value for a = 7? O a. 11.53 O b. 54-45 C. 53-35 O d. -3.87
Given the following data, calculate the three-month moving average forecasts formonths 4, 5, 6, and 7
Given the number of calls per week received by a dental clinic, what is the forecasted number of calls for week 12 considering that the forecast for week 1 was 47 and a smoothing constant a -0.2? CALLS 52 35 25 36 45 35 44 WEEK 1 2 3 4 5 6 7 869 10 34 calls 35 calls 33 calls 38 calls 30 35 25
None
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A 18.2% B 15.7% C 22.2% D 4.4%
Period 1 2 3 4 5 6 7 Actual 42 41 39 43 45 F ? ? 2 2. Using the same table above, compute the weighted moving average forecast for demand for four latest period. With data using a weight of .40 for the most recent, .30 for the next recent, .20 the next, and .10 for the oldest. Assume actual demand for period 6 is 44, what is the forecast for period 7?
The figure below illustrates monthly data over 10 years. What method would you expect would perform the best at forecasting the data series in period 121? Explain the (i) strengths of your selected method for this data and the (ii) weaknesses of alternative methods for this data. Consider the concepts of level, seasonality, trend, and noise in your answer.
In the following data, x is the average number of hours the student spent working on math each week and y is the final grade in a math class. hours/week Grade X y 4 50.6 6. 59.4 9. 69.6 11 83.4 11 82.4 11 76.4 14 86.6 17 89.8 20 98 20 99 The line of best fit is y = 2.79 · x + 45.23. What is the predicted value for the final grade when a student spends an average of 13 hours each week on math? Grade = Round to 1 decimal place.
Define on empirical way and a statistical way to choose the best forecasting model for your time series data. Consider the following situations: 1. The data has no trend or seasonality 2. The data has trend but not seasonality 3. The data presents trend and seasonality but negligible noise 4. The data presents trend, seasonality and significant noise.
In Excel create a 4 period moving average with additive trend in excel using the below excel data. Optimize the model for the value of x that minimizes the MSE. Calculate the MSE for the model and next years prediction. What is the MSE for this model? (use 2 decimal places). Below is the excel data and the moving average that excel gave me. Just need to optimize the model for x and minimize MSE?

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