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MCA Computing Least Squares Regression Estimates

MCA handles several daily commuter flights. The budget officer compiled the following data regarding airport costs and activity over the past years:
Month Flights originating at MCA (000) Airport cost
January....................................11...................................................20.00
February......................................8...................................................17.00
March.........................................14................................................19.00
April...........................................9........................................................18.00
May............................................10................................................19.00
June..................................................12...............................................20.00
July................................................11...................................................18.00
August...........................................14.................................................24.00
September.....................................10...............................................19.00
October.........................................12............................................21.00
November..........................................9............................................17.00
December.....................................15...................................................21

1. Draw a scatter diagram of the airport costs
2.Compute the least spuares regression estimates of the variable and fixed cost components in the airport cost behavior pattern.
3.Write the least squares regression equation for the airport costs
4. Predict the airport costs during a month when 1,600 flights originate at the airport
5. Compute the coeficient of determination for the regression equation . Ineterpret R2

Solution Summary

Your tutorial is attached in excel where you see a scattergraph, a regression output tab, the equation, the prediction and an interpretation of the R square (coeffic of determination).

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