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### Course: AP®︎/College Statistics > Unit 7

Lesson 3: Conditional probability- Conditional probability and independence
- Conditional probability with Bayes' Theorem
- Conditional probability using two-way tables
- Calculate conditional probability
- Conditional probability and independence
- Conditional probability tree diagram example
- Tree diagrams and conditional probability

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# Conditional probability using two-way tables

Researchers surveyed $100$ students on which superpower they would most like to have. This two-way table displays data for the sample of students who responded to the survey:

Superpower | Male | Female | TOTAL |
---|---|---|---|

Fly | |||

Invisibility | |||

Other | |||

TOTAL |

A student will be chosen at random.

## Want to join the conversation?

- How did you get your answer that 62% of females chose invisibility as their superpower. I saw up above, it was 44.(0 votes)
- 44 is the TOTAL number of people who chose invisibility. Out of those, 32 are female, therefore 32 is the condition that satisfies our probability question (the numerator in the probability formula).

52 is the total number of people who are female in this experiment.

32/52 is about 0.62 or 62%(25 votes)

- I might need to practice this more at home and to read my notes more carefully. It's not easy, but I'll take it as a challenge!(34 votes)
- I think It is easy to you now, after 5 years.(11 votes)

- What is the quickest way to calculate probability?(3 votes)
- in a bag with six things in which two things are pens, what is the probability of you hitting a pen by putting your hand on the bag without looking at it's inside?

you just need to divide the number of pens from the number of things, that is gonna be 2/6 # two pens divided by six things, or you can simplify and you get 1/3, so you have 1/3 probability of hitting a pen.(1 vote)

- Is there any formula for conditional probability, or is it simply common sense? (in general questions)(2 votes)
- In general, if A and B are events such that P(B) is nonzero, then

P(A given B) = P(A and B) / P(B).

Have a blessed, wonderful day!(11 votes)

- I honestly don't understand this, Thank you for making all this content available.(6 votes)
- Are there harder ways to do this type of question?(2 votes)
- I think Bayes' Theorem questions can get a lot harder than this. We're being given all the information here, so it's easy to calculate any kind of probability, but it gets harder when you don't have all the information and you have to extrapolate.(4 votes)

- Why shouldn't we apply Bayes theorem in question 3 (P(male ∣ fly))?(2 votes)
- Bayes' Theorem says

P(male | fly) = P(fly | male) ∙ P(male)∕P(fly)

But we don't know what P(fly | male) is, so we can't use this formula.(3 votes)

- The second question is worded a little weird. It seems like tis connected to the first one because it says “the student” as i the one from the last question instead of “a student”. Thank you.(2 votes)
- In Problems 1 and 2, a student was chosen at random, but we don't know anything about the student. We are just calculating the probability that they would have a specific trait (that they chose flying as their superpower in Problem 1, or that they were male in Problem 2). Hope this clears up your confusion!(2 votes)

- 1-what is the difference between P(I ∣ F) and P(F ∣ I) when I Interpret the meaning?

2-what the difference in meaning between P(I ∣ F) and

P(I and F) ?

can anyone help me to understand these questions?(1 vote)- Difference is similar to this:

"If I will get home I will sleep" or "If I will sleep I will get home"

Writing P(A | B) is "If B happens, how likely is A to happen".

Writing P(B | A) is "If A happens, how likely is B to happen".(3 votes)

- the last one means the same thing to me idk maybe im illiterate(0 votes)
- Well, A is stating that 62% of women chose invisibility while B says that 62% of both men and women who CHOSE Invisibility are female which would be: P(F given I) not P(I given F)(5 votes)