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Economics 105: Statistics Any questions? Go over GH 3 & 4

Economics 105: Statistics

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Economics 105: Statistics. Any questions? Go over GH 3 & 4. Discrete Random Variables. Take on a limited number of distinct values Each outcome has an associated probability We can represent the probability distribution function in 3 ways function ƒ(x i ) = P(X = x i ) graph table - PowerPoint PPT Presentation

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Page 1: Economics 105: Statistics

Economics 105: Statistics• Any questions?• Go over GH 3 & 4

Page 2: Economics 105: Statistics

Discrete Random Variables• Take on a limited number of distinct values• Each outcome has an associated probability• We can represent the probability distribution function in 3 ways

– function ƒ(xi) = P(X = xi)

– graph– table

• Bernoulli distribution– graph & table ?

• Cumulative distribution function

Page 3: Economics 105: Statistics

Discrete Random Variable Summary Measures

• Expected Value (or mean) of a discrete distribution (Weighted Average)

–Example: Toss 2 coins, X = # of heads, compute expected value of X:

E(X) = (0 x 0.25) + (1 x 0.50) + (2 x 0.25) = 1.0

X P(X)

0 0.25

1 0.50

2 0.25

Page 4: Economics 105: Statistics

• Variance of a discrete random variable

• Standard Deviation of a discrete random variable

where:E(X) = Expected value of the discrete random variable X

Xi = the ith outcome of XP(Xi) = Probability of the ith occurrence of X

Discrete Random Variable Summary Measures

(continued)

Page 5: Economics 105: Statistics

–Example: Toss 2 coins, X = # heads, compute standard deviation (recall E(X) = 1)

Discrete Random Variable Summary Measures

(continued)

Possible number of heads = 0, 1, or 2

Page 6: Economics 105: Statistics

Properties of Expected Values• E(a + bX) = a + bE(X), where a and b are constants

• If Y = a + bX, then var(Y) = var(a + bX) = b2var(X)

Page 7: Economics 105: Statistics

Example• Let C = total cost of building a pool • Let X = days to finish the project• C = 25,000 + 900X• X P(X = xi)

10 .1 Find the mean, std dev, and

11 .3 variance of the total cost.

12 .3

13 .2

14 .1

Page 8: Economics 105: Statistics

Permutations and Combinations• Need to count number of outcomes• Number of orderings

– x objects must placed in a row – can only use each once– x! = (x)(x-1)(x-2) … (2)(1) called “x factorial”

• Permutations– suppose these x ordered boxes can be filled with n objects– n > x– What is the number of possible orderings now? – Permutations of n objects chosen x at a time = nPx

– nPx = n(n-1)(n-2) … (n-x+1) = n!/(n-x)!

Page 9: Economics 105: Statistics

Permutations and Combinations• How many ways to arrange, in order, 2 letters selected from A through E?• What if order doesn’t matter?

• CombinationsnCx = nPx/x! = n!/ [(n-x)! * x!]

• Eight people (5 men, 3 women) apply for a job. Four

employees are needed. If all combinations are equally likely to be hired, what is the probability no women will be hired?

Page 10: Economics 105: Statistics

The Binomial Distribution

Binomial

Poisson

Probability Distributions

Discrete Probability

Distributions

Hypergeometric

Bernoulli

Page 11: Economics 105: Statistics

Binomial Distribution• Binomial distribution is composed of repeated Bernoulli trials •Let X1, X2, …, XN be Bernoulli r.v.’s, then B is distributed binomially

•Probability of x successes in N trials is

where p is the prob of “success” on a given trial

Page 12: Economics 105: Statistics

Binomial Distribution• Let B ~ binomial, with p = prob of success, N = number of trials• Find E[B] and Var[B] … but first a couple more rules on the mathematics of expectations with more than 1 r.v.

Page 13: Economics 105: Statistics

Two Random Variables• Expected Value of the sum of two random variables:

• Variance of the sum of two random variables:

• Standard deviation of the sum of two random variables:

Page 14: Economics 105: Statistics

• Let B ~ binomial and now find E[B] and Var[B]• McCoy’s Tree Service in Mocksville, NC removes dead trees from commercial and residential properties. They have found that 40% of their invoices are paid within 10 working days. A random sample of 7 invoices is checked. What is the probability that fewer than 2 will be paid within 10 working days?

Binomial Distribution