Consider the following data:Jan-12 Feb-12Profit ($) 6,500 6,253MonthMonthly Profit of a GymMar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-125,514 5,357 5,425 6,278 8,119 6,390 6,090Step 1 of 5: Determine the three-period moving average for the next time period. If necessary, round your answer to one decimal place.

The provided information is as follows: MonthProfit…

Answered: Consider the following data: Monthly…

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:Monthly Profit of a Gym Month Jan-12 Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 Profit ($) 5,9015,901 5,6535,653 5,1545,154 4,8774,877 5,2455,245 5,7985,798 6,9196,919 6,2346,234 5,9585,958 Step 1 of 5 : Determine the three-period moving average for the next time period. If necessary, round your answer to one decimal place.
A company has the following monthly sales for the past year. Plot the data points on a line graph and describe the results. Month Sales 1 145 2 146 3 145 4 150 5 148 6 150 7 156 8 160 9 158 10 153 11 152 12 154
Use the border crossings data below and a = = 0.3 and ẞ = 0.2. Truck Crossings Month February 113,691 March 139,204 April 121,498 May 127,511 June 131,500 July 105,245 August 126,606 Copy Data Step 2 of 2: Calculate the adjusted exponential smoothing forecast for September 2011. Assume the forecast component for February 2011 to be the actual truck crossing value minus the initial trend. Let the initial trend be 10,000 trucks. Round your answer to two decimal places.
A Laspeyres price index for each year?
Month Actual 3 month moving average 6 month moving average ( 4,3,2,1,1,1) August September 19 20 October 18 November 16 December 16 January February March 14 16 After computing for the MAD, what should be the better forecasting to use? a. 6-month weighted moving average O b. Exponential smoothing O c. Naive O d. 3-month moving average
Suppose seafood price and quantity data for the years 2000 and 2009 follow. Use 2000 as the base period. 2000 2000 Price ($/lb) 2009 Seafood Qty. (Ib) Price ($/lb) Halibut 75,090 2.01 2.33 Lobster 83,180 3.62 3.09 Tuna 50,779 1.87 1.97 (a) Compute a price relative for each type of seafood. (Round your answers to one decimal place.) Seafood Price Relative Halibut Lobster Tuna (b) Compute a weighted aggregate price index for the seafood catch. (Round your answer to one decimal place.) I 2009 - Comment on the change in seafood prices over the nine-year period. (Enter your percentage as a positive value. Round your answer to one decimal place.) Seafood prices have --Select--- v by % over the 9-year period according to the index.
Use the gas prices data set below to calculate a 3-month Weighted Moving Average (WMA) forecast for the average gas prices and predict the average retail gasoline price for February 2015. Use the weights of 0.6, 0.3, and 0.1 for the 3-month WMA, where the first weight is used for the most recent month and the last weight is used for the least recent month. Round your answer to two decimal places, if necessary. Month-Year Jun-14 Jul-14 Aug-14 Sep-14 Oct-14 Nov-14 Dec-14 Jan-15 Average Gas Price $3.766 $3.688 $3.565 $3.484 $3.255 $2.997 $2.632 $2.208 Copy Data
Which of the following is not a good interpretation of a seasonal index of 1.26 for fall quarter sales? O a. Fall quarter sales are 26 perbent higher than the annual average. O b. Fall quarter sales represents 1.26 times the annual average. O c. Fall quarter sales represents an increase of 26 percent over last year's annual average. O d. Fall quarter sales average 126 percent of annual sales.
Please help with the corrected answers in details: The following time series shows the sales of a particular product over the past 12 months. Month Sales 1 105 2 135 3 120 4 105 5 90 6 120 7 145 8 140 9 100 10 80 11 100 12 110 What type of pattern exists in the data? The data appear to follow a trend pattern. The data appear to follow a horizontal pattern. The data appear to follow a cyclical pattern.The data appear to follow a seasonal pattern. (b) Use ? = 0.2 to compute the exponential smoothing values for the time series. (Round your answers to two decimal places.) Month t Time Series Value Yt Forecast Ft 1 105 2 135 3 120 4 105 5 90 6 120 7 145 8 140 9 100 10 80 11 100 12 110 (c) Use a smoothing constant of ? = 0.4 to compute the exponential smoothing forecasts. (Round your answers to two decimal places.) Month t Time Series Value Yt Forecast Ft 1 105 2 135…
Following shows the numbers of Amazon Prime members in the millions, each quarter from 2016 to 2021. Quarter 2016 2017 2018 2019 2020 2021 1 26 36 48 62 81 98 2 27 37 50 65 83 103 3 29 40 53 69 86 109 4 33 44 57 74 93 117 Construct a line chart using the data. Describe the relationship between the time and number of subscribers.
You collect data of average annual returns for Amazon Stock and Microsoft Stock and make the following table: (This data can be copied into Excel.) Year Amazon Return Microsoft Return 2013 0.5896 0.1221 2014 -0.2218 0.2416 2015 1.1778 0.1944 2016 0.1095 0.1200 2017 0.5596 0.3766 2018 0.2843 0.1874 2019 0.3216 0.5526 You use this data to answer the research question: are true population Amazon Returns greater than true population Microsoft Returns?
Graph the following table of values

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