Passenger miles flown on Northeast Airlines, a commuter firm serving the Boston hub, are shown for the past 12 weeks:Week12 3 4 5 6Actual Passenger Miles (in thousands) 15 20 16 21 16 15a) Assuming an initial forecast for week 1 of 15,000 miles, use exponential smoothing to compute miles for weeks 2 through 12. Use a = 0.25 (round your responses to two decimal places).17892 3 410 11 1215.00 15.00 16.25 16.19 17.39 17.04 16.53 16.65 16.49 17.62 17.46 15.85Week123456WeekForecasted PassengerMiles (in thousands)b) The MAD for this model = 2.61 thousand (round your response to two decimal places).c) Compute the Cumulative Forecast Errors, cumulative MAD in thousands, and tracking signals (round your responses to two decimal places).CumulativeForecastCumulativeForecastErrorsErrors0.006.605.005.954.7510.469.569.848.176.13MAD0.002.501.752.522.292.25TrackingSignal2.002.713.803.572.7356717Week78910118 916 2110 11 1217 11 21MAD1.991.832.121.97TrackingSignal3.313.264.924.98

The time series is the method used for analysis when the data is time-dependent. The observation…

Answered: Passenger miles flown on Northeast…

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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Suppose that you are a researcher and wish to construct a linear mathematical (statistical) model that relates the number of years and the corresponding exports (million U.S.$) of a country. The constructed model may use to forecasts the future values. You have obtained the relevant data for the during of 1990 to 1995 and you have listed the data in Table 5. Table 5. Shows the list of the amount that have earned on exports Year No. 1 2 3 4 5 6 Exports 4954 6131 6904 6813 6803 8137 (a) Construct a suitable graph that explains the relationship between the number of years and the corresponding exports. (b) Construct a mathematical (Statistical) model by using least square method between number of years and the corresponding sales. (c) Interpret the slope of the estimated linear model (d) Forecast the value of exports by using the estimated linear model for the year of 2000
Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPI) and the cost of a slice of tuna. We would like to build a model using the CPI to predict the cost of a slice of pizza in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 Cost of a slice of tuna(y) 0.15 0.35 1.00 1.25 1.75 2.00 Plot the data. Are we justified in creating a Linear Regression model to predict the price of a pizza slice using the CPI? Why or why not? Calculate the descriptive statistics. Calculate the sums of squares Calculate the slope, intercept, and correlation. What is this correlation value telling us? Assemble the prediction equation, and interpret the slope within the context of the problem. State the hypotheses for the hypothesis test for regression.
A soda company is monitoring the number of cases of soda it produces as a function of time. A manager checked the line several times a day for a week. She then graphed the combined data. Assume that we should see a linear (best straight line) relationship between time and production. What is the best estimate of the number of cases that will be produced in 1 hr on a typical day? 8. 7 1 0.5 1.5 2 2.5 Time in hours Select one: а. 1 b. 2 C. 2.5 d. 4.5 е. 7 Cases of soda produced
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
Month Actual demand Forecasted Demand 1 950 1000 2 1070 1000 3 1100 1000 4 960 1000 5 1090 1000 6 1050 1000 For the dataset above, compute the overall MAPE.
Use the most accurate method to forecast the revenues of licenses, permits, and fees in Years 9, 10, and 11. Use the Year 8 actual figure instead of the forecast figure (Year 8 was $23,210,218). Also, consider three incremental changes in forecasting.
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.) You use this data to answer the research question: are true population Amazon Returns greater than true population Microsoft Returns? What is your point estimate of the difference in Amazon Returns and Microsoft Returns? Enter your answer as a positive number. Round your answer to four decimal places.
Using the photo attached, One Stop Car Repairs ollects data on the actual demand for its services and uses this data to make forecasts. The actual number of transmissions that were repaired for the last ten periods IS ATTACHED IN THE PHOTO answer the following. 1. Using the trend projection manual method, forecast demand for transmission repairs for periods 11 and 12

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