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Statistics for Decision- Making in Business - Maricopa Community ...

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Probability<br />

0.18<br />

0.16<br />

0.14<br />

0.12<br />

0.10<br />

0.08<br />

0.06<br />

0.04<br />

0.02<br />

0.00<br />

Probability Distribution <strong>for</strong> S<strong>in</strong>gle Die Roll<br />

1 2 3 4 5 6<br />

Die Value<br />

In words, the probability of gett<strong>in</strong>g any one face value on a die roll is about 0.17 or 1/6. The<br />

distribution is uni<strong>for</strong>m.<br />

If we found the expected value (the average), we would get:<br />

, - ( ) ( ) ( ) ( ) ( ) ( )<br />

(NOTE: This is the same as<br />

s<strong>in</strong>ce each event is equally likely)<br />

The variance of this population requires us to use the population standard deviation <strong>for</strong>mula<br />

(remember, division by occurs if we are deal<strong>in</strong>g with a sample, so that we have an<br />

unbiased estimate <strong>for</strong> the population standard deviation). That is:<br />

, -<br />

∑( )<br />

Us<strong>in</strong>g Excel we f<strong>in</strong>d that:<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

=VAR.P(A2:A7)<br />

which give:<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

2.916666667<br />

<strong>Statistics</strong> <strong>for</strong> <strong>Decision</strong>-<strong>Mak<strong>in</strong>g</strong> <strong>in</strong> Bus<strong>in</strong>ess © Milos Podmanik Page 182

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