Conditional Probability question

In summary, the probability of a student getting a good grade if they did not participate in class is 0.1379, based on the given information and the relation between the conditional probabilities of getting a good grade and participating in class.
  • #1
Juanriq
42
0

Homework Statement


Students who actively participate in class are 4 times more likely to get a good grade than those who don't. 15% of students actively participate in class; 20% of students get a good grade. A person did not participate in class, what is the probability that he got a good grade?


Homework Equations





The Attempt at a Solution



Well, I define P(G): student got a good grade; P(P): student participates. Obviously, P(G) = .2 and P(P) = .15. I also know that P(G|P) = 4P(G| not P). I am looking for the conditional probability P(G| not P). I would imagine that I need to find P(G|P) / 4, but this would mean that I need [itex] P(G \cap P) P(P) [/itex] and alas, I do not believe that I have [itex] P(G \cap P) [/itex]. ANy ideas? Anything I am missing? Thanks!
 
Physics news on Phys.org
  • #2
Note that

[tex]P(G) = P(G \cap P) + P(G \cap P^c) = P(G|P)P(P) + P(G|P^c) P(P^c)[/tex]

You know everything except [itex]P(G|P)[/itex] and [itex]P(G|P^c)[/itex], and you know a relation between those two which should allow you to solve for [itex]P(G|P)[/itex].
 
  • #3
I must be doing something wrong... I have

[itex].2 = (.15)P(G|P) + (.85)P(G|P^c) = (.15)P(G|P^c)/4 + (.85)P(G|P^c)[/itex]

and upon simplification I get [itex]P(G|P^c) = .225[/itex], but the answer is supposed to be .16.
 
  • #4
Here is what I get. Write [itex]x = P(G | P^c)[/itex]. Then

[tex]0.2 = (0.15) (4x) + (0.85) x = 1.45x[/tex]

so

[tex]x = 0.2 / 1.45 = 0.1379...[/tex]

which doesn't match either of your answers.

P.S. You know .225 has to be wrong, since P(good grade) = 0.2 and surely the probability shouldn't go up for students who don't participate!
 
  • #5
Thanks for all the help! It wouldn't be the first typo in the notes...
 

Related to Conditional Probability question

1. What is conditional probability?

Conditional probability is a mathematical concept that refers to the likelihood of an event occurring based on the knowledge of another event happening. In other words, it is the probability of event A happening, given that event B has already occurred.

2. How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of both events occurring together by the probability of the second event occurring. This can be represented as P(A|B) = P(A and B) / P(B).

3. What is the difference between conditional probability and regular probability?

The main difference between conditional probability and regular probability is that conditional probability takes into account the occurrence of a previous event, while regular probability does not consider any prior events. Regular probability is used to calculate the likelihood of a single event occurring, while conditional probability is used to calculate the likelihood of an event occurring given that another event has already occurred.

4. How is conditional probability used in real life?

Conditional probability is used in various fields, such as statistics, finance, and medicine. In real life, it can be used to predict the likelihood of an event happening based on past data or to make informed decisions based on the occurrence of a previous event. For example, it can be used to determine the probability of a patient developing a certain disease based on their medical history.

5. What are some common misconceptions about conditional probability?

One common misconception about conditional probability is that it is the same as regular probability. As explained earlier, these two concepts are different and serve different purposes. Another misconception is that conditional probability always follows the same rules as regular probability, which is not always the case. There are specific rules and formulas that apply only to conditional probability calculations.

Similar threads

Replies
1
Views
1K
Replies
4
Views
1K
Replies
1
Views
942
Replies
6
Views
1K
Replies
30
Views
4K
Back
Top