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There are a lot of problems we face in programming that deal with uncertainty, statistics, and probabilities. Unfortunately, the majority of the general-purpose languages that we use on a daily basis don’t provide a great approach to solving them.

This is particularly the case in C# with the System.Random class. The implementations of this class have been pretty poor for some time. System.Random in C# regularly leads to unexpected, buggy outcomes.

If you’re a C# fan who’s looking for new ways to use the language, then this course is for you. It proposes different approaches to improving the System.Random class, providing a number of powerful techniques that solve problems more efficiently and with fewer lines of code.

Fixing Random: Techniques in C#

In the [previous lesson](https://www.educative.io/courses/fixing-random-techniques-in-c-sharp/what-is-the-average-value-as-the-number-of-samples-increases), we showed why our naïve implementation of computing the expected value could be fatally flawed: there could be a "black swan" region where the "profit" function `f` is different enough to make a big difference in the average, but the region is just small enough to be missed sometimes when we’re sampling from our distribution `p`

In this lesson, we will try to find a better estimate of the expected value in the continuous case.

Better Estimation of the Expected Value

Introduction to System.Random in C#

Introduction to Fixing Random

Fixing Random - Discrete Distribution

Fixing Random - Continuous Distribution

Conclusion

Appendix

Better Estimation of the Expected Value