SUMMARY
The discussion centers on determining the probability density function (pdf) of the random variable Y, defined as Y = h(X) = max(X, 1-X), where X follows a uniform distribution on the interval [0,1]. The pdf is established as follows: for x > 0.5, pdf = x; for x < 0.5, pdf = 1-x. The cumulative distribution function (CDF) F(y) is derived, showing F(y) = 0 for y < 0.5, F(y) = 2x - 1 for 0.5 ≤ y ≤ 1, and F(y) = 1 for y > 1. The conclusion is that Y is uniformly distributed between 0.5 and 1.
PREREQUISITES
- Understanding of uniform distribution and its properties
- Knowledge of probability density functions (pdf) and cumulative distribution functions (CDF)
- Familiarity with the concept of maximum of random variables
- Basic skills in mathematical reasoning and probability theory
NEXT STEPS
- Study the derivation of probability density functions for transformed random variables
- Learn about the properties of uniform distributions in detail
- Explore the concept of cumulative distribution functions and their applications
- Investigate the implications of maximum functions in probability theory
USEFUL FOR
Mathematicians, statisticians, and students in probability theory who are looking to deepen their understanding of uniform distributions and their transformations.