Expected value problem (probability)

In summary, the problem involves finding the expected value and variance of the sum of two integer values, Y1 and Y2, within given constraints. The solution involves using the formulas for expectation and variance of a discrete random variable, which involves taking the sum of each value multiplied by its probability. The solution also involves defining a new variable, U, as the sum of Y1 and Y2, and using the given formulas for expectation and variance of a sum of random variables.
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Homework Statement


Given Y1 and Y2 are integer values, where 0[tex]\leq[/tex]Y1[tex]\leq[/tex]3, 0[tex]\leq[/tex]Y2[tex]\leq[/tex]3, 1[tex]\leq[/tex]Y1+Y2[tex]\leq[/tex]3

p(Y1, Y2) = [tex]\frac{{4 \choose y_1}{3 \choose y_2}{2 \choose {3-y_1-y_2}}}{{9 \choose 3}}[/tex]

Find E(Y1+Y2) and V(Y1+Y2)

Homework Equations


E(Y1+Y2) = E1(Y1)+E2(Y2)

E1(Y1) = [tex]\int_{-{\infty}}^{\infty} y_1 f(y_1) dy_1[/tex]

But that's for continuous variables, so I have no idea how to deal with discrete. Some guy tried explaining it to me, but it was just so unclear I didn't understand any of it.

Required use of these theorems:

Given U1 = [tex]\sum_{i=1}^n a_i*Y_i[/tex]
E(U1) = [tex]\sum_{i=1}^n a_i*E_i (Y_i)[/tex]

V(U1) = [tex]{\sum_{i=1}^n {a_i}^2*E_i (Y_i)}+2{\sum{\sum_{1{\leq{i}}<j{\leq{n}}} {a_i}^2*E_i (Y_i)}}[/tex]


The Attempt at a Solution


Well, first I did it the slow counting way involving counting,
P(Y1+Y2=1)

= [tex]\frac{{4 \choose 0}{3 \choose 1}{2 \choose {2}}}{{9 \choose 3}}[/tex] + [tex]\frac{{4 \choose 1}{3 \choose 0}{2 \choose {2}}}{{9 \choose 3}}[/tex]

= [tex]\frac {3+4}{84}[/tex]

= [tex]\frac {7}{84}[/tex]

P(Y1+Y2=2)

= [tex]\frac{{4 \choose 0}{3 \choose 2}{2 \choose {1}}}{{9 \choose 3}}[/tex] + [tex]\frac{{4 \choose 1}{3 \choose 1}{2 \choose {1}}}{{9 \choose 3}}[/tex] + [tex]\frac{{4 \choose 2}{3 \choose 0}{2 \choose {1}}}{{9 \choose 3}}[/tex]

= [tex]\frac {3(2)+4(3)(2)+6(2)}{84}[/tex]

= [tex]\frac {42}{84}[/tex]

P(Y1+Y2=3)

= [tex]\frac{{4 \choose 0}{3 \choose 3}{2 \choose {0}}}{{9 \choose 3}}[/tex] + [tex]\frac{{4 \choose 1}{3 \choose 2}{2 \choose {0}}}{{9 \choose 3}}[/tex] + [tex]\frac{{4 \choose 2}{3 \choose 1}{2 \choose {0}}}{{9 \choose 3}}[/tex] + [tex]\frac{{4 \choose 3}{3 \choose 0}{2 \choose {0}}}{{9 \choose 3}}[/tex]

= [tex]\frac {1+4(3)+6(3)+4)}{84}[/tex]

= [tex]\frac {35}{84}[/tex]


E(Y1+Y2) = P(Y1+Y2=1)+2P(Y1+Y2=2)+3P(Y1+Y2=3)

= [tex]{(1)}{\frac {7}{84}}+{(2)}{\frac {42}{84}}+{(3)}{\frac {35}{84}}[/tex]

= [tex]\frac {196}{84}[/tex]

= [tex]\frac {7}{3}[/tex]


But I'm supposed to be using the formula I listed above. So I have no idea how to deal with that.
 
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  • #2
well, expectation is the same for discrete as for random variables. If you think about it, integration is a really awesome way to take sums (ie riemann sums), so the expectation of discrete random variables is just the sum over all i of x(i)times the probability of x(i)

also, you need to define U(i) as a new variable Y(1)+Y(2), and do the calculation on U. then you can use your formulas
 

FAQ: Expected value problem (probability)

What is expected value?

Expected value is a mathematical concept in probability that represents the average outcome of a random event over a large number of trials. It is calculated by multiplying each possible outcome by its probability and then summing all of the products together.

How is expected value used in decision making?

Expected value can be used to make decisions by comparing it to the potential outcomes of a decision. If the expected value is positive, then the decision is considered favorable. If the expected value is negative, then the decision is considered unfavorable.

Can expected value be negative?

Yes, expected value can be negative. This means that the average outcome of a random event is a loss or a cost. It is important to consider both positive and negative expected values when making decisions.

How is expected value different from actual value?

Expected value is a hypothetical value based on probabilities, while actual value is the real outcome of a random event. Expected value is used to make predictions and decisions, while actual value is what actually happens.

How can expected value be calculated?

Expected value can be calculated by multiplying each possible outcome by its probability and then summing all of the products together. This can be done using a formula or by creating a table and manually calculating the expected value.

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