Statistics Problem regarding conditional probabilities

In summary, the conversation discusses a problem involving a delivery service and the probability of a package being sent by standard delivery given that it did not arrive the next day. The attempt at a solution involves using conditional probabilities and verifying a rule. While the first statement is true, the second statement is false.
  • #1
wolfmanzak
26
0

Homework Statement



A certain delivery service offers both express and standard delivery. Eighty-five percent of parcels are sent by standard delivery and 15% are sent by express. Of those sent standard, 80% arrive the next day, and of those sent express, 95% arrive the next day. A record of parcel delivery is chosen at random from the company’s files.

Given that the package did not arrive the next day, what is the probability that is was sent standard?

Homework Equations



Not entirely sure, possibly the statistics probability rule of multiplication or another.

The Attempt at a Solution



To begin I made Express Delivery= to the variable "E"
Standard delivery = "S"
Next day = "N"

From here I tried to use the relation P(S|N^c)=(P(N^c|S)P(S))/(P(N^c)) but the P(N^c|S) is one term that I don't have an actual probability for. So I'm going back and forth with one equation and two unknowns. I know the numerical value of the answer already, but I'm trying to follow the steps for the solution to the above listed problem. If someone could show me what the setup is for this solution I'd really appreciate the help.
 
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  • #2
They give you P(N|S), so isn't P(Nc|S) just 1-P(N|S)?
 
  • #3
I'm with you now I think. But is it true that:

P(A^c|B)=1-P(A|B) as well as P(A|B^c)=1-P(A|B)? My book only has the first equation and I wanted to verify that the second was true as well. It works just as you said but I just wanted to make sure that I knew exactly why and that I'm not making up my own rules.

Thank you.
 
  • #4
I'm with you now I think. But is it true that:

P(A^c|B)=1-P(A|B) as well as P(A|B^c)=1-P(A|B)? My book only has the first equation and I wanted to verify that the second was true as well. It works just as you said but I just wanted to make sure that I knew exactly why and that I'm not making up my own rules.

Thank you.
 
  • #5
The first statement is true, but the second is false. Deal one card from a normal pack. It's an ace. What is the probability that the next card dealt is an ace? What is the probability that it is not? That is an example of p(A|B)=1-p(Ac|B). However, draw a card and a second. What is the probability that the second is an ace given that the first was an ace? And given that the first was not an ace? Your relation doesn't hold here.
 

Related to Statistics Problem regarding conditional probabilities

What is a conditional probability?

A conditional probability is the likelihood of an event occurring given that another event has already occurred. It is denoted by P(A|B), where A and B are events.

How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of the joint occurrence of two events (P(A ∩ B)) by the probability of the first event (P(B)). This can be written as P(A|B) = P(A ∩ B) / P(B).

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 joint probability.

What is the importance of conditional probabilities in statistics?

Conditional probabilities are important in statistics because they allow us to make more accurate predictions and decisions by taking into account the relationship between two events. They also help us to understand the impact of one event on another.

What are some real-life examples of conditional probabilities?

Some real-life examples of conditional probabilities include predicting the likelihood of a person having a certain disease given their age and gender, or the likelihood of a student passing a test given their study habits. They can also be used in marketing to predict the likelihood of a customer purchasing a product based on their demographic information.

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