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Quantitative Methods, Statistics, and Regression Interpretation

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Case study concerning interpretation of:
- Logit regression
- Explanatory variables
- Dummy variables
- Statistical tests

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This solution discusses quantitative methods, statistics and regression interpretations.

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Logistic Regression Equation: a formula with a natural logarithm in it:
P = EXP(a + b X ) / [1+EXP(a + b X)]
This formula shows the relationship between the regression equation (a + bx), which is a straight line formula, and the logistic regression equation. The formula involves the probability, p, that y equals 1 and the natural logarithm, a mathematical function abbreviated.

Now, let's turn to the project at hand.
Logit coefficients correspond to the b (unstandardized regression) coefficients in ordinary least squares (OLS) regression. Logits are the natural log of the odds. They are used in the logistic regression equation to estimate (predict) the log odds that the dependent equals 1.

If the logit for a given independent variable is b1, then one ...

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