How Do You Determine Conditional Probabilities in Practical Scenarios?

In summary, the speaker is looking for someone to answer a past exam paper accurately in order to practice and prepare for an upcoming exam. The topics that the speaker is specifically interested in are descriptive statistics, probability, probability distributions, sampling and sampling distributions, interval estimation, and hypothesis tests. They are willing to pay for this service and ask interested individuals to contact them through inbox or by replying to the thread.
  • #1
Retro95
6
0
I can easily solve a problem if the probabilities are already defined in the question.. such as P(A|B)
But I always get confused about how to actually define the probability from an application exercise.

E.g..
Market research shows that (A)75% if customers want text messages on their phone, (B)80% want photo capability, (AnB)65% want both.

What are the probabilities that a person who wants text messages also wants photo capability?

Would the formula be
P(A|B)=answer
or
P(B|A)=answer

Also could you please explain in detail how I would know which letter goes first since I always get it confused.
 
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  • #2
P(B|A), B is the variable which has the probability. A is the condition.
Your expression is a little imprecise the way it is worded. A is the event a customer wants text mesages and P(A) = .75, etc.

In formal terms you are asking what is the probability that a person wants photo capability under the condition the person wants text messages.
 
  • #3
mathman said:
P(B|A), B is the variable which has the probability. A is the condition.
Your expression is a little imprecise the way it is worded. A is the event a customer wants text mesages and P(A) = .75, etc.

In formal terms you are asking what is the probability that a person wants photo capability under the condition the person wants text messages.

Yeah thanks I eventually figured it out after a lot of application question practice.
************************************

Also I have an exam in 2 days but my stupid lecturer decided not to give us the answer sheet to a previous past paper for us to practice and check our answers on.

So basically I have a past question paper PDF and I'm willing to pay someone to answer it 100% accurately so that I can see which parts I need to improve on before the exam

Inbox me or reply to this thread if anyone reading this is extremely confident in the following topics..
Descriptive Statistics,
Probability, Probability Distributions,
Sampling and Sampling Distributions,
Interval Estimation,
Hypothesis Tests
 

Related to How Do You Determine Conditional Probabilities in Practical Scenarios?

1. What is conditional probability?

Conditional probability is a mathematical concept that measures the likelihood of an event occurring given that another event has already occurred. It is expressed as P(A|B), where A is the event of interest and B is the condition or event that has already occurred.

2. How is conditional probability calculated?

Conditional probability is calculated by taking the probability of the intersection of the two events (P(A∩B)) and dividing it by the probability of the condition event (P(B)). This can also be written as P(A|B) = P(A∩B) / P(B).

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

Conditional probability measures the likelihood of an event occurring given that another event has already occurred, while joint probability measures the likelihood of two events occurring together. Conditional probability is calculated using the intersection of two events, while joint probability is calculated using the union of two events.

4. How can conditional probability be used in real-life situations?

Conditional probability can be used in real-life situations to make predictions or decisions based on previous information. For example, it can be used in weather forecasting to predict the likelihood of rain given the current temperature and humidity.

5. What are some common misconceptions about conditional probability?

One common misconception about conditional probability is the belief that if two events are related, they must be dependent. However, two events can be related and still be independent. Another misconception is the assumption that if two events are independent, they must be unrelated. In reality, independence only means that the probability of one event occurring does not affect the probability of the other event occurring.

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