Actually I should have divided by 99 instead of 100, but with

That's the Greek letter *sigma* . is called the **probability model variance** and its square root
is called the **probability model standard deviation** . It is the center of gravity along the horizontal axis of the graph of the probability model. So in this example, assuming the spinner is fair, .6611 is an estimate of
and its square root, .8131, is an estimate of
.

Three other parameters of interest are the median and quartiles of the probability model. These are used more for the continuous probability models, so we will present them later.

- 1.
- Let S denote the sum of two numbers spun on a fair spinner with the numbers 1, 2, and 3 on it. The range of S is 2, 3, 4, 5, 6. Determine the probability
model
**variance**of S. - 2.
- Let X denote the number of aces in a 2 card hand drawn without replacement from a
*well shuffled*standard deck 0f 52 cards. Then the range of X is {0, 1, 2}. Determine the probability model**variance**of X. - 3.
- Repeat the last problem under sampling with replacement.
- 4.
- In the urn problem (with the balls well mixed ) discussed above, let Z denote the number of red balls in the sample (without replacement) of size 3. Determine the probability model
**variance**of Z.