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Get Started Now- Intro Lesson6:06
- Lesson: 1a5:54
- Lesson: 1b10:59
- Lesson: 2a13:20
- Lesson: 2b18:37
- Lesson: 316:45

Recall:

• Multiplication Rule: $P(A \;and\;B)=P(B) \cdot P(A|B)$

• Conditional Probability: $P(B|A)$ $=$ $\frac{P(A \;and\; B)}{P(A)}$

• Law of Total Probability: $P(A)=P(B_1)P(A|B_1)+P(B_2)P(A|B_2)+ \cdots+P(B_n)P(A|B_n)$

Combining all these equations we get Bayes’ Rule:

$P(B|A)$ $=$ $\frac{P(A \;and\; B)}{P(A)}= \frac{P(B) \cdot P(A|B)}{P(A)}$

$=\frac{P(B) \cdot P(A|B)}{P(B_1)P(A|B_1)+P(B_2)P(A|B_2)+ \cdots+P(B_n)P(A|B_n)}$

• Multiplication Rule: $P(A \;and\;B)=P(B) \cdot P(A|B)$

• Conditional Probability: $P(B|A)$ $=$ $\frac{P(A \;and\; B)}{P(A)}$

• Law of Total Probability: $P(A)=P(B_1)P(A|B_1)+P(B_2)P(A|B_2)+ \cdots+P(B_n)P(A|B_n)$

Combining all these equations we get Bayes’ Rule:

$P(B|A)$ $=$ $\frac{P(A \;and\; B)}{P(A)}= \frac{P(B) \cdot P(A|B)}{P(A)}$

$=\frac{P(B) \cdot P(A|B)}{P(B_1)P(A|B_1)+P(B_2)P(A|B_2)+ \cdots+P(B_n)P(A|B_n)}$

- IntroductionDeriving Bayes’ rule
- 1.
**Bayes' Rule**

I am going to ask my boss to be my reference after applying to another job. If she gives me a good recommendation there is a 0.75 probability that I will get the job. While if she gives me a bad recommendation there is only a 0.25 probability that I will get the job. There is a 60% chance she will give me a good reference and a 40% chance she will give me a bad reference.a)What is the probability that I will get the job?b)Given that I got the job what is the probability that she gave me a good reference - 2.I have 3 bags that each contains 5 marbles.

Bag A:

Bag B:

Bag C:

2 Green

4 Green

5 Green

3 Red

1 Red

0 Red

I roll a fair die to decide which bag I will draw from. If I roll a 1,2,3 I will draw a marble from Bag A. If I roll a 4,5 I will draw from Bag B. And if I roll a 6, then I will draw a marble from bag C.a)What is the probability that I draw a red marble?b)Suppose that I drew a green marble from a bag. What is the probability that I rolled a 6? - 3.
**False Positives**

A blood test is 95% effective when diagnosing a diseased person. However this blood test also incorrectly diagnoses a healthy person 5% of the time. If 0.1% of the population actually has this disease, then what is the probability that a person has the disease given that they tested positive?

I like this, gives you hope if you get diagnosed for a serious disease

Make note of how many healthy people and how many diseased people get diagnosed. Also make a tree diagram illustrating this.

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