Exam 2 Review

March 7, 2017 at 10:00 am  •  Posted in s17-busad360 by  •  3 Comments

Tue, Mar 7



  • Exam 2 Review Topics
    • Scatterplots
    • Simple Regression
    • t-test of slope
    • F-test of overall model
    • Multiple Regression
    • Regression Output Interpretation
    • Multicollinearity
    • Binary Variables


  • Study for Exam 2



  1. Beldar - / March 7, 2017 at 9:34 pm / Reply

    Greeetings, Earthlings!

    Good luck on your test, I recommend reviewing the material relating to the topics of discussion this semester.

    8 more weeks after this week, one is Spring Break and another is finals… Much taco-espresso smoothies.

  2. Rique Lucero / March 8, 2017 at 5:29 pm / Reply

    Hello, Professor Holdman.

    I’ve got a quick question, when is it acceptable to have a negative coefficient? I believe it was that if you could boost your Rsquared number, while having a low P score, it would be acceptable to have a negative coefficient. I’m probably making this harder that what it is, but I want this to come out perfect.

    Rique Lucero

    • Justin / March 10, 2017 at 9:19 am / Reply

      Hi Rique,
      Sorry I didn’t reply to this question in time for exam 2. There’s nothing wrong with having a negative coefficient. But, it should make sense in the context of the problem you’re trying to solve. The real estate data example with a negative coefficient for number of bedrooms was a result of multicollinearity. But the reason it isn’t appropriate to utilize such a model is because it doesn’t make sense to reduce a selling price estimate for every additional bedroom, not because the coefficient is negative. Make sense?

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