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    Linear Regression (example problem)

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    Linear Regression (example problem)

    Boeing and McDonnell Douglas from the United States, and Airbus Industrie, the European consortium, dominate the global aerospace industry. During the early 1990's, the end of the cold war with the Soviet Union led to a dramatic downshifting in orders for military related purchases at the same time a global recession cut sharply into the commercial demand for aircraft. Against this backdrop, a number of financial analysts began to question the wisdom and profitability of the industry's massive long-term investments in research and development (R&D).

    The following table shows sales revenues, profit, and R&D data for a sample of firms taken from the U.S. aerospace industry. Data are for the most recent fiscal year reported as of May 18, 1993, and are limited to those companies reporting sales of $58 million or more and R&D expenditures of at least $1 million. R&D expenditures are the dollar amount of company sponsored R&D during the most recent fiscal year, as reported to the Securities and Exchange Commission on Form 10-K. Excluded from such numbers is R&D under contract to others, such as U.S. government agencies. All figures are in millions of dollars.

    Company Name Sales Profits R&D Expense
    Abex 728.4 194.0 1.6
    Boeing 30,184.0 2,256.0 1,846.0
    Curtiss-Wright 179.7 32.7 1.6
    GenCorp 1,937.0 37.0 36.0
    General Dynamics 3,472.0 227.0 66.0
    K&F Industries 782.9 29.0 14.1
    Kaman 295.5 (14.7) 14.1
    Lockheed 10.100.0 549.0 420.0
    Martin Marietta 5.954.3 512.4 200.0
    McDonnell Douglas 17,373.0 1,086.0 509.0
    Northrop 5,550.0 180.0 93.0
    OEA 88.1 23.1 2.6
    Orbital Sciences 174.6 5.4 6.0
    Pacific Scientific 172.6 8.1 8.2
    Sequa 1,868.3 43.8 17.6
    Sunstrand 1,672.7 130.1 115.4
    Thiokol 1,311.7 101.8 14.2
    United Technologies 21,641.0 200.0 1,219.0
    Woodward Governor 374.2 33.0 16.0

    Required:

    1. Using Excel generate a simple regression model with sales revenue as the dependent
    Y-variable and R&D expenditures as the independent X- variable

    2. Based on the model generated, forecast revenues for a firm with R&D expenditures of $300.0

    3. Evaluate the predictability of the model.

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    <br>
    <br>1. Using Excel generate a simple regression model with sales revenue as the dependent
    <br> Y-variable and R&D expenditures as the independent X- ...

    Solution Summary

    Linear Regression example problem is examined thoroughly.

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