PROBABILITY AND STATISTICS

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PROBABILITY AND

STATISTICS

WEEK 8

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Skewness

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Pearson's skewness coefficient

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Example

• It’s been understood that, in a hosptial patients’ average hospital stay is 28, median is 25 and mode is 23 (days). And the standard deviation calculated as 4,2.

Define the skewness type, find the pearson coefficient and interpret it.

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Joint Probability Distributions

Discrete Random Variables (two and multiple)

Continious Random Variables (two and multiple)

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Two Discrete Random Variables

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Example

A large insurance agency services a number of customers who have purchased both a homeowner’s policy and an automobile policy from the agency. For each type of policy, a deductible amount must be specified. For an automobile policy, the choices are $100 and $250, whereas for a homeowner’s policy, the choices are 0, $100, and $200.

Suppose an individual with both types of policy is selected at random from the agency’s files. Let X the deductible amount on the auto policy and Y the deductible amount on the homeowner’s policy.

Suppose the joint pmf is given in the accompanying joint probability table:

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Example

• P(Y ≥100)=?

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Marginal Probability Mass Function

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Example

Let us obtain the marginal pmf of X evaluated at, x=100 and x=250.

Let us obtain the marginal pmf of Y.

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Remember

We already know!

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Conditional Probability Mass Function

Recall: P(A/B)=P(A

B)/P(B)

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Example

Opinion about school (X) and teachers (Y) surveyed for students as follows:

1

1

30

Teachers Scores

2

10

3

20

2 50 30 10

3 10 10 30 a) Determine the joint probability distribution of X and Y.

b) Find the probability student give 1 point for school and 2 or above point for teachers?

c) Find the marginal probability distribution, mean and variance of school scores.

d) Determine the conditional probability distribution of teacher scores given that school score is 2. And find the (conditional) mean and variance of Y given X=2.

e) Check if school opinions and teacher opinions are independent.

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Two Continuous Random Variables

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Example

A bank operates A and B facilities. On a randomly selected day, let X the proportion of time that A in use and Y the proportion of time that the B in use. Then the set of possible values for ( X, Y) is the rectangle

D = {(x, y): 0≤ x ≤ 1, 0 ≤ y ≤ 1}.

Suppose the joint pdf of (X, Y) is given by, a) Verify that this is a legitimate pdf.

b) Find the probability that neither facility is busy more than onequarter of the time.

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Marginal Probability Density Function

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Example

Find the marginal pdf of X and Y for previous question.

• Find P(1/4≤Y ≤3/4)=?

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Example

A nut company markets cans of deluxe mixed nuts containing almonds, cashews, and peanuts. Suppose the net weight of each can is exactly 1 lb, but the weight contribution of each type of nut is random. Because the three weights sum to 1, a joint probability model for any two gives all necessary information about the weight of the third type. Let X = the weight of almonds in a selected can and Y = the weight of cashews.

Verify that this is a legitimate pdf.

To compute the probability that the two types of nuts together make up at most 50% of the can,

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Conditional Probability Mass Function

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Example

The sizes of college books are under study in terms of width (X) and height (Y).

Suppose that the joint p.d.f of X and Y is modeled as f (x,y)=cxy, 2<x<5 and x+ 1 <y<x+3 (unit:inch)

Determine the value of c.

Determine the marginal probability distribution of X. Find also the mean and variance of X.

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Covariance

Covariance and correlation between x and y?

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Covariance

Shortcut formula:

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Correlation

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Example

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