Finite Math Examples

xP(x)20.230.370.180.2110.2
Step 1
Prove that the given table satisfies the two properties needed for a probability distribution.
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Step 1.1
A discrete random variable x takes a set of separate values (such as 0, 1, 2...). Its probability distribution assigns a probability P(x) to each possible value x. For each x, the probability P(x) falls between 0 and 1 inclusive and the sum of the probabilities for all the possible x values equals to 1.
1. For each x, 0P(x)1.
2. P(x0)+P(x1)+P(x2)++P(xn)=1.
Step 1.2
0.2 is between 0 and 1 inclusive, which meets the first property of the probability distribution.
0.2 is between 0 and 1 inclusive
Step 1.3
0.3 is between 0 and 1 inclusive, which meets the first property of the probability distribution.
0.3 is between 0 and 1 inclusive
Step 1.4
0.1 is between 0 and 1 inclusive, which meets the first property of the probability distribution.
0.1 is between 0 and 1 inclusive
Step 1.5
0.2 is between 0 and 1 inclusive, which meets the first property of the probability distribution.
0.2 is between 0 and 1 inclusive
Step 1.6
For each x, the probability P(x) falls between 0 and 1 inclusive, which meets the first property of the probability distribution.
0P(x)1 for all x values
Step 1.7
Find the sum of the probabilities for all the possible x values.
0.2+0.3+0.1+0.2+0.2
Step 1.8
The sum of the probabilities for all the possible x values is 0.2+0.3+0.1+0.2+0.2=1.
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Step 1.8.1
Add 0.2 and 0.3.
0.5+0.1+0.2+0.2
Step 1.8.2
Add 0.5 and 0.1.
0.6+0.2+0.2
Step 1.8.3
Add 0.6 and 0.2.
0.8+0.2
Step 1.8.4
Add 0.8 and 0.2.
1
1
Step 1.9
For each x, the probability of P(x) falls between 0 and 1 inclusive. In addition, the sum of the probabilities for all the possible x equals 1, which means that the table satisfies the two properties of a probability distribution.
The table satisfies the two properties of a probability distribution:
Property 1: 0P(x)1 for all x values
Property 2: 0.2+0.3+0.1+0.2+0.2=1
The table satisfies the two properties of a probability distribution:
Property 1: 0P(x)1 for all x values
Property 2: 0.2+0.3+0.1+0.2+0.2=1
Step 2
The expectation mean of a distribution is the value expected if trials of the distribution could continue indefinitely. This is equal to each value multiplied by its discrete probability.
Expectation=20.2+30.3+70.1+80.2+110.2
Step 3
Simplify the expression.
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Step 3.1
Simplify each term.
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Step 3.1.1
Multiply 2 by 0.2.
Expectation=0.4+30.3+70.1+80.2+110.2
Step 3.1.2
Multiply 3 by 0.3.
Expectation=0.4+0.9+70.1+80.2+110.2
Step 3.1.3
Multiply 7 by 0.1.
Expectation=0.4+0.9+0.7+80.2+110.2
Step 3.1.4
Multiply 8 by 0.2.
Expectation=0.4+0.9+0.7+1.6+110.2
Step 3.1.5
Multiply 11 by 0.2.
Expectation=0.4+0.9+0.7+1.6+2.2
Expectation=0.4+0.9+0.7+1.6+2.2
Step 3.2
Simplify by adding numbers.
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Step 3.2.1
Add 0.4 and 0.9.
Expectation=1.3+0.7+1.6+2.2
Step 3.2.2
Add 1.3 and 0.7.
Expectation=2+1.6+2.2
Step 3.2.3
Add 2 and 1.6.
Expectation=3.6+2.2
Step 3.2.4
Add 3.6 and 2.2.
Expectation=5.8
Expectation=5.8
Expectation=5.8
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 [x2  12  π  xdx ] 
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