Passenger kilometres (pax-km) flown on Golden Airlines, a commuter firm serving theJohannesburg – Cape Town route, are as follows for the past 12 weeks:Passenger kilometresWeek(1 000)172211942318616208.189.22102011151222The company needs to determine aircraft capacity requirement for week 13. To this endpax-km forecasts for week 13 are required. Assist the company and establish the weeklyforecasts by using the following methods:• A four-week moving average• A four-week weighted moving average (weight = 0.45, 0.35, 0.15 & 0.05 from the mostrecent week)• Exponential smoothing with a = 0.2. (Assuming an initial forecast for week 1 of 17,000pax-km)• Trend regressionWhich of these techniques would you recommend that the company use?What is the pax-km forecast for week 15?

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Answered: Passenger kilometres (pax-km) flown on…

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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4 pts Problem #1a: Use a two-month moving average to create a forecast for May. Calculate the forecast errors associated the moving average forecasts. Month Demand January 18 February 23 March 20 April 16 May ??? Edit View Insert Format Tools Table | в I U 12pt v Paragraph v MacBook Pro &
a) Find the equation of the line which is the best fit for the data, with x equal to the number of years after 1999 and y equal to the millions of people b) Ise the model to estimate the number of people who took trips in 2008.
Your younger brother, a fourth form practical geography student wishes to test whether there could be some relationship between annual visits to a local market by all residents surrounding that market. After a well-designed field study he obtains the following figures: Number of visits per year 21 13 19 18 17 17 14 20 10 11 Residence distance from market (KM) 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 From the information above, what is the dependent variable and what is the explanatory variable? Using (i) above, obtain the regression equation of Yi on Xi. Hence, estimate the residence distance from the market (in KM) if the number of visits are 16 visits Sketch your results in (ii) above. What conclusion can you draw from your sketch?
Please answer the following including the conditions that need to be met and how to compute the answer using a graphing calculator. Thank you.
Compare the primary types of forecasting methods used to determine demand.
For the following line graph, State at least one type of conclusion that could be made from the data provided for the KPI. Suggest one other data source that would provide more information to make data-driven decisions. Explain what information that source would supply. I used the line graph btw. Examples: 1)The KPI webpage for South Texas College provides information on the proportion of graduates who find employment. According to the data, over the past five years, the proportion of graduates who find work has risen annually. Data on the percentage of students who are employed in their field of study after graduation, the percentage of students who are employed full-time after graduation, and the percentage of students who are satisfied with their job after graduation would also be useful in making decisions about post-graduation success. This information would shed light on the factors that are causing the rise in the proportion of graduates who find employment. 2)The…
The forecasts generated by two forecasting methods and actual sales have been collected in the Microsoft Excel Online file attached. Use the Microsoft Excel Online file attached to develop forecast accuracy and answer the following questions. 1. What is the MAD, the MSE, the MAPE, the RSFE, and the tracking signal for each forecasting method? Do not round intermediate calculations. Round your answers to two decimal places. Use the minus sign to enter negative values, if any. 2. What can be concluded about the quality of the forecasts 2? Assume that the control limit for the tracking signal is ±3. The results indicate (bias or no bias) in the forecasts 2, and that the tracking signal (is not or is) within the control limits of ±3.
For the following line graph, State at least one type of conclusion that could be made from the data provided for the KPI. Suggest one other data source that would provide more information to make data-driven decisions. Explain what information that source would supply. (I used the clustered bar chart) Examples: 1) The completion KPI measures the percentage of South Texas College students who finished their degree or certificate program within six years. From the line graph, it can be seen that the completion rates have remained nearly constant through the years. Data from the THECB was used in this case. 2) Information about the percentage of students who receive credit for attempted courses is available on the South Texas College KPI webpage. According to the data, over the past five years, an increasing number of students have been receiving credit for courses they have attempted. Data on the percentage of students who complete courses, the percentage of students who withdraw…
Name the forecasting methods
An engineer wants to determine how the weight of a gas powered car, x, affects gas mileage, y. The accompanying days represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. weight Miles per (pounds), x Gallon, y 3797 16 3897 16 2704 24 3608 20 3360 22 3040 22 3787 17 2618 24 3509 18 3798 16 3399 17 interpret the slope y-intercept, if appropriate. Choose the correct answer below for y hat = -0.00661x + 41.80 a) A weightless car will get ____ miles per gallon, on average. It is not appropriate to interpret the slope. b) for every pound added to the weight of the car, mileage in the city will…
If a forecaster wanted to choose a forecasting model that avoided having a large forecasting error in any given period, which error metric should they use when evaluating their forecasting options? CFE O AFE MAD MAPE O MSE

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