Question Onea) Calculate the determinant of matrix A. Show your work in steps:A =2013-2--2 1 3 2 -11 0 1 2 33-12 4 -31 1 3 2 0b) Prove row linear independence is necessary and sufficient to column linearindependence in the same matrix.c) Derive the inverse matrix of matrix B. Show your work in steps:[3 20 014300B =00 6 5LO0 7 6]

Answered: Image /qna-images/answer/dbf0e69a-b3d3-4d01-bb1f-5c8733c93e63.jpg

Answered: Question One a) Calculate the…

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter5: Business And Economic Forecasting

Section: Chapter Questions

Problem 1.4CE

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Plot the logarithm of arrivals for each transportation mode against time, all on the same graph. Which now appears to be growing the fastest?
Logarithms are especially useful for comparing series with two divergent scales since 10 percent growth always looks the same, regardless of the starting level. When absolute levels matter, the raw data are more appropriate, but when growth rates are whats important, log scales are better.
The Questor Corporation has experienced the following sales pattern over a 10-year period: Compute the equation of a trend line (similar to Equation 5.4) for these sales data to forecast sales for the next year. (Let 2004=0,2005=1, etc., for the time variable.) What does this equation forecast for sales in the year 2014? Use a first-order exponential smoothing model with a w of 0.9 to forecast sales for the year 2014.
Estimate the double-log (log linear) time trend model for log cruise ship arrivals against log time. Estimate a linear time trend model of cruise ship arrivals against time. Calculate the root mean square error between the predicted and actual value of cruise ship arrivals. Is the root mean square error greater for the double log non-linear time trend model or for the linear time trend model?
Metropolitan Hospital has estimated its average monthly bed needs as N=1,000+9X where X=timeperiod(months);January2002=0 N=monthlybedneeds Assume that no new hospital additions are expected in the area in the foreseeable future. The following monthly seasonal adjustment factors have been estimated, using data from the past five years: Forecast Metropolitans bed demand for January, April, July, November, and December 2007. If the following actual and forecast values for June bed demands have been recorded, what seasonal adjustment factor would you recommend be used in making future June forecasts?
What is the difference between a series of economic data over time measured in nominal terms versus the same data series over time measured in real terms?

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