The beta lives on , so it models proportions: the fraction of a claim paid, a loss ratio, a probability that is itself uncertain. The exam hands you the density and asks you to integrate it, the one skill worth drilling.
on the interval :
The leading constant is whatever makes the density integrate to 1. The moments are simple ratios:
HIGH-FREQUENCY: The exam always gives you the density, often without naming it "beta." Recognize the shape, read off and , and either use the moment formulas or integrate directly. For integer powers the integral is elementary.
Since the support is and the density is a polynomial (for integer ), any moment is a routine polynomial integral. To get you integrate ; to get a probability you integrate from 0 to .
Common mistakes
- Not recognizing the beta from its density. A density proportional to on is beta. The exam often omits the name.
- Misreading the powers. has (so ) and (so ), not , .
- Using where is needed. The variance needs the second moment , a separate integral from the mean.
Bottom line
- Beta() on : density proportional to .
- Mean: . Variance: , or get it from .
- Read off the density: the power on is ; the power on is .
- A probability is , integrated only over since the density is 0 outside the unit interval.
Exam shortcut
Spot the shape, read and , then either apply or integrate directly. For probabilities, integrate the polynomial density over , it is always elementary for integer parameters. "Powers plus one give and ." "Mean leans toward the bigger parameter." Symmetric only when .
The full lesson (about 1,711 words, 11 min read) adds 2 worked examples, all 6 common mistakes, a self-check, free in the app.
Learning objectives
- 2a
- 2b
- 2c
- 2d
- 2e
- 2f
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