# Suppose that X is a random variable with E[X] = Var[X] = . What does Chebyshev’s inequality say about P(X > Tu)? (b) Imagine we have an algorithm….

**Question:**

Suppose that X is a random variable with E[X] = Var[X] = . What does Chebyshev’s inequality say about P(X > Tu)? (b) Imagine we have an algorithm for solving some decision problem (e.g., is a given number a prime?). Suppose that the algorithm makes a decision at random and returns the correct answer with probability 1+d, for some 8> 0 (which is just a bit better than a random guess). To improve the performance, we run the algorithm N times and take the majority vote. Show that, for any € E (0,1), the answer is correct with probability 1 – E, as long as N > (1/2)8-2 In(8-1). (Hint: Use Hoeffding’s inequality. This scheme is usually called “boosting randomized algorithms.”)

**Click the button below to view answer!**

If you happen to run into some problem while following the steps, please make sure to let us know in the comment section below, we’ll do our best to solve it. Apart from that, you can contact us on Facebook and Twitter, however we can’t guarantee a rapid reaction time over those platform

## 0 Comments