# Level II Quantitative Methods

## p vs. α

Candidates galore have problems (nightmares, really . . . but let’s not rub it in) with p-values.  I’m here to tell you that understanding p-values is easy.  Seriously: easy. A p-value is nothing more nor less than a level of significance, just like α.  The best description I’ve heard is that α is the chosen […]

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## R² vs. Adjusted R²

There’s a lot more to R2 and adjusted R2 than appears in the CFA curriculum.  I’ll discuss what you need to know for the exam; the rest you can get from a statistics textbook if you’re interested. R2 Whether for a simple (i.e., single) regression or a multiple regression, R2 is the percentage of the […]

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## Degrees of Freedom

Suppose that, for reasons known only to yourself and your therapist, you need to know the average height of all giraffes in the world.  Desperately.  You face a number of obstacles, not the least of which is that there are estimated to be about 80,000 giraffes in the world, and giraffes are notoriously difficult to […]

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## Durbin-Watson Statistic (Test)

The Durbin-Watson (DW) statistic is used in a test for serial correlation of residuals (i.e., error terms) in several types of regression models: Simple regression models Multiple regression models Time-series trend models DW is not appropriate for testing for serial correlation of residuals in autoregressive (AR) models.  The CFA curriculum doesn’t specify exactly why DW […]

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## Dummy Variables

The idea of a dummy variable is fairly simple: it’s a variable that can take on a value of 0 or 1; it simply shows the absence (0) or presence (1) of some characteristic.  Nevertheless, there are some important rules you need to remember about dummy variables. How Dummy Variables are Used Imagine that you’re […]

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