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Multiple Linear Regression

In: Statistics for Business and Financial Economics

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  • Cheng-Few Lee

    (Rutgers University Business School, Department of Finance and Economics)

  • John C. Lee

    (Center for PBBEF Research)

  • Alice C. Lee

Abstract

Chapters 13 and 14 examined in detail the simple regression model with one independent variable (such as amount of fertilizer) and one dependent variable (such as yield of corn). In many cases, however, more than one factor can affect the outcome under study. In addition to fertilizer, rainfall and temperature certainly influence the yield of corn. In business, not only rates of return for the stock market at large affect the return on General Motors or Ford stock. Other variables, such as leverage ratio, payout ratio, and dividend yield also contribute. Therefore, regression analysis with more than one independent variable is an important analytical tool.

Suggested Citation

  • Cheng-Few Lee & John C. Lee & Alice C. Lee, 2013. "Multiple Linear Regression," Springer Books, in: Statistics for Business and Financial Economics, edition 3, chapter 0, pages 739-792, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-5897-5_15
    DOI: 10.1007/978-1-4614-5897-5_15
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