The score of a student on a certain exam is going to be a number between 0 and 1. Think of it as the percentage of correct answers on the exam. Suppose the student passes the exam if their score S is at least 0.60 and fails otherwise. If the probability density function of a student score S is given by 4x f(x) = 4 4x <<1. 0. otherwise If the student passes the exam, what is the probability that their score S was at least 0.75?
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
Trending now
This is a popular solution!
Step by step
Solved in 4 steps
