Using simple exponential smoothing and the following time series data, respond to each of the items. PeriodDemand11042132314341375146615071018126911610115Show work, please. Thank you! b. Compute all possible forecasts using a smoothing coefficient (a) of 0.3. (Negative amounts should be indicated by a minus sign.Round your answers to 1 decimal place.)ExponentialŚmoothPeriodDemandErrorAbsolute Error110421323143413714615071011261161011511c. Compute the MAD. (Round your answer to 2 decimal places.)MADd. What is the forecast demand for period 11? (Round your answer to 1 decimal place.)Period 11 forecast

Given data: Period Demand 1 104 2 132 3 143 4 137 5 146 6 150 7 101 8 126 9 116…

Using simple exponential smoothing and the following time series data, respond to each of the items. Period Demand 1 104 2 132 3 143 4 137 5 146 6 150 7 101 8 126 9 116 10 115 Show work, please. Thank you!

Using simple exponential smoothing and the following time series data, respond to each of the items. Period Demand 1 104 2 132 3 143 4 137 5 146 6 150 7 101 8 126 9 116 10 115 Show work, please. Thank you!

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Suppose that index model for Stocks A and B is estimated from excess returns with the following results : Ra 0.04 +0.6Rm+ea , Rb = - 0.04 + 1.3Rm + eb Risk on the market is 30% , R-squared of A is 30%R - squared of B is 40% , security A residual variance is
A researcher hypothesizes that in a certain country the net annual growth of private sector purchases of government bonds, B, is positively related to the nominal rate of interest on the bonds, NI, and negatively related to the rate of inflation Π: Bt = a0 + a1NIt + a2Π t + ut Note that it may be hypothesized that B depends on the real rate of interest on bonds, R, where R = NI – Π. Using a sample of 56 annual observations, s/he estimates the following equations: (1) Bt = 0.43 + 0.90NIt - 0.97Πt R21 = 0.962, SSR1 = 2.20, QRESET(F1,52) = 16.6 (3.58) (8.80) (-1.05) (2) Bt = 0.44 + 0.94Rt R22 = 0.960, SSR2 = 2.22, QRESET(F1,53) = 0.9 (9.70) (16.7) (3) Bt = 0.44 + 1.14NIt SSR3 = 9.20, QRESET(F1,53) = 59.9 (8.84) (36.1) (4) NIt = 0.08 + 0.94Πt R24 = 0.997, SSR4 = 0.18, QRESET(F1,53) = 1.4…
The values of Alabama building contracts (in $ millions) for a 12 -month period follow. 240 350 240 260 280 320 220 310 240 310 240 240 A. Compare the three-month moving average approach with the exponential smoothing forecast using a=0.2 (to 2 decimals). MSE (3-Month) _______ MSE ( a=0.2) __________ Using only the errors for months 4 to 12, the MSE for exponential smoothing is: MSE ( a=0.2) __________ C. Using the approach that provides more accurate forecasts based on MSE, what is the forecast for the next month (to the nearest whole number)? $ _______million
a. In the Petroco Service Station problem, compute an exponentially smoothed forecast with an α value of .30. According to the result from Excel and/or POM-QM, the forecast for the month of August b.In the Petroco Service Station problem, for the exponentially smoothed forecast with an α value of .30, compute the mean absolute deviation (MAD) via Excel and/or POM-QM c. In the Petroco Service Station problem, compute an exponentially smoothed forecast with an α value of .50. According to the result from Excel and/or POM-QM, the forecast for the month of January would be d.In the Petroco Service Station problem, compute an exponentially smoothed forecast with an α value of .50. According to the result from Excel and/or POM-QM, the forecast for the month of August
Compute the forecasted values for Yt for July and August in 2020 by using the modelsstated in (c) and (d)
A researcher wants to examine the relationship between time spend on social media (variable X) and loneliness (variable Y) in young adults. A randomly sample of n = 52 young adults was asked how much time in average they spend on social media each day and how lonely day feel on a typical day. The partial computations of collected data produced the following results: SP = -14 MX = 10 SSx = 36 MY = 16 SSY = 49 A. Based on these results, is there a significant correlation between time spend on social media and loneliness among young adults? Use a Pearson correlation test with p < .05, 2-tails to answer this research question. Follow the steps of hypothesis testing and insert your answers below. In your calculations,round all numbers to two decimal places to avoid rounding errors. ANSWER H0: H1: Computed Pearson r = df for decision about H0: Critical r-value used for decision about H0: Decision about H0 (i.e., reject or fail to…
For the Hawkins Company, the monthly percentages of all shipments received on time over the past 12 months are 80, 82, 84, 83, 83, 84, 85, 84, 82, 83, 84, and 83. a. Compute for a 3 month moving average forecast. b. Compute for the exponential smoothing forecast for a=0.2. c. Which provides the better forecast using MSE as the measure of model accuracy? d. What is the forecast for next month?
Respond to each of the items using the following time series data. Period Demand 1 20 2 46 3 20 4 9 5 17 6 8 7 19 8 34 9 39 10 4 11 32 12 23 13 10 14 27 Click here for the Excel Data Fileb. Compute all possible forecasts using exponential smoothing with a smoothing coefficient (α) of 0.3. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.) c. Compute all possible forecasts using exponential smoothing with a smoothing coefficient (α) of 0.7. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.) d. Compute the MADs for each forecast model. (Round your answers to 3 decimal places.) e. Which forecast model would you choose? Why?
With the gasoline time series data from the given table, show the exponential smoothing forecasts using = 0.1. Week Sales (1000s of gallons) 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of = 0.1 or = 0.2 for the gasoline sales time series? Do not round your interim computations and round your final answers to two decimal places. = 0.1 = 0.2 MSE fill in the blank 1 fill in the blank 2 Prefer: 01. or 0.2 2. Are the results the same if you apply MAE as the measure of accuracy? Do not round your interim computations and round your final answers to two decimal places. = 0.1 = 0.2 MAE fill in the blank 4 fill in the blank 5 Prefer: 0.1 or 0.2 3. What are the results if MAPE is used? Do not round your interim computations and round your final answers to two decimal places. = 0.1 = 0.2 MAPE fill in…
Pink Table, a snack shop has recorded sales for its best-selling cold drink, shown as follows: Day 1 2 3 4 5 6 7 8 9 10 Jasmine Slush (12 oz) 125 136 127 123 142 148 139 140 154 158 a. Predict the sales for Jasmine Slush using the following forecasting methods: naïve (use simple naive method, forecast this period=actual value of last period); 3-day moving average method; weighted average method using the following weights: 45%,30%,25%; exponential smoothing with smoothing constant alpha equal to 10%, assume forecast for day 1 for each of the 3 products is the sales for day1; linear trend line. b. Using the results in a), compute the error ( MSE, MAD, and MAPE) for each of the methods used. c. Which forecasting technique will you recommend fo predict the sales of Jasmine Slush Explain and support your answer quantitatively.
According to Deloitte, through January 25,2006, the majority of companies reporting profits had beaten estimates. Now suppose that for the 4th quarter of 2012, 170 of a random sample of 280 companies reported profits that had beaten estimates. Does the data indicate the proportion of companies in the 4th quarter of 2012 that beat estimates is greater than 56% at α=0.05?