Probability - Random Variables

In summary, the student is preparing for an oral exam and is concerned about having an "on" day or an "off" day. The probability of passing with each examiner on an "on" day is 0.8, while on an "off" day it is 0.4. The student believes they are twice as likely to have an "off" day. To pass the exam, the majority of examiners must pass. Comparing a group of 3 and a group of 5 examiners, the probability of passing is higher with 5 examiners. However, according to the book, the student has a better chance with a group of 3 examiners. To find the probability of passing, the student
  • #1
AsianMan
4
0
A student is getting ready to take an important oral examination and is concerned about the possibility of having an "on" day or an "off" day. He figures that if he has an on day, then each of his examiners will pass him independently of each other, with probability .8, whereas if he has an off day, this probability will be reduced to .4. Suppose that the student will pass the examinatorion if a majority of the examiners pass him. If the student feels that he is twice as likely to have an off day as he is to have an on day, should he request an examination wiht 3 examiners or 5?

_________
I thought this was a binomial probability distriubtion question, with possibility of success = .4*(2/3) + .8*(1/3) = 8/15

I totaled the probabilities for 3,4, and 5 successes for a 5 examiner group and 2 and 3 successes for a 3 man group and found the probability of success for the 5 man group was higher (.562315 vs .549926), but the book says you have a better chance of passing with a 3 man group.

This is the 2nd question in a row of this type I have screwed up and am desperate to see what I'm doing wrong.
 
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  • #2
You did the 2/3 vs 1/3 weighting at the beginning instead of the end.

Find prob of winning with n=5 and p=0.8.
Find prob of winning with n=5 and p=0.4.
Take weighted average of those two probabilities.

Repeat using n=3 instead of n=5.
 

What is probability and how is it related to random variables?

Probability is a numerical measure of the likelihood of a particular event occurring. It is related to random variables because random variables are used to represent uncertain or random events and their associated probabilities.

What is a random variable and how is it different from a regular variable?

A random variable is a numerical quantity that takes on different values depending on the outcome of a random event. It differs from a regular variable in that its value is not predetermined, but rather determined by chance.

What is the difference between discrete and continuous random variables?

Discrete random variables can only take on a finite or countable number of values, while continuous random variables can take on any value within a certain range. For example, the number of heads in a coin toss is a discrete random variable, while the height of a person is a continuous random variable.

How do you calculate the expected value of a random variable?

The expected value of a random variable is the sum of all possible values of the variable multiplied by their respective probabilities. For example, if a coin has a 50% chance of landing on heads and a 50% chance of landing on tails, the expected value of the number of heads in two tosses would be (0 x 0.5) + (1 x 0.5) + (1 x 0.5) + (2 x 0.5) = 1.5.

What is the central limit theorem and why is it important in probability?

The central limit theorem states that the sum of a large number of independent and identically distributed random variables will follow a normal distribution, regardless of the underlying distribution of the individual variables. This is important because it allows us to make predictions and draw conclusions about a population based on a sample, as long as the sample size is large enough.

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