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# Probability Distribution

## Probabilities associated with possible counting number

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Practice Probability Distribution
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Visualizing Probability Distribution

#### Objective

Here you will learn how to create a visual representation of a probability distribution.

#### Concept

Writing down all of the various probabilities of outcomes of an event is fine, but it can get a little tedious both to create and to read a long list of different probabilities. How else can we display the information from a probability distribution?

#### Watch This

This video is a quick lesson on how to create a discrete probability distribution in “Excel”, and the process is similar in any standard spreadsheet software. Statistics and spreadsheets go very much hand-in-hand, so I certainly recommend you begin practicing with one, if you have not already. If you do not have access to Excel, there is a very similar and free software called “OpenOffice” available online.

http://youtu.be/qSu-Rk-6apw ExcellsFun – Discrete Probability Chart

(This is video 46 in the series from “ExcellsFun”, if you would like a more detailed explanation on how to begin setting up the distribution, you may wish to watch the (much longer) video #45.)

#### Guidance

Probability distributions can convey a fantastic amount of useful information, but there may be so much information to view that the important points get lost in the data. Because of this, it is very common to create a graphical representation of the data to highlight important or interesting values.

Tables, histograms and bar charts in particular are excellent means of visualizing the data from discrete probability distributions. If you use a histogram or bar chart, by enumerating the various outcomes along the x\begin{align*}x\end{align*}-axis and the expected probability of occurrence on the y\begin{align*}y\end{align*}-axis, you create a very concise and easily read summary of the distribution of outcome probabilities.

Example A

Let C\begin{align*}C\end{align*} be a discrete random variable representing the number of heads that might result from flipping a coin three times. Create a bar chart to illustrate the probability distribution of C\begin{align*}C\end{align*}.

Solution: Start by identifying the possible outcomes of flipping a coin three times:

So we have 1 possibility with 0 heads: P(0)=18=0.125\begin{align*}P(0) = \frac{1}{8} = 0.125\end{align*}

Example B

Create a table showing the probability distribution of the possible outcomes of rolling two standard dice.

Solution: Let random variable S\begin{align*}S\end{align*} represent the sum of the pips showing on the roll of both dice. We know then than 2S12\begin{align*}2 \le S \le 12\end{align*}.

Find all of the possible outcomes of rolling two dice, as shown in the image on the below.

Create a table showing the probabilities of each possible outcome of S\begin{align*}S\end{align*}:

 S\begin{align*}S\end{align*} P(S)\begin{align*}P(S)\end{align*} S\begin{align*}S\end{align*} P(S)\begin{align*}P(S)\end{align*} 2 136\begin{align*}\frac{1}{36}\end{align*} 8 536\begin{align*}\frac{5}{36}\end{align*} 3 236\begin{align*}\frac{2}{36}\end{align*} 9 436\begin{align*}\frac{4}{36}\end{align*} 4 336\begin{align*}\frac{3}{36}\end{align*} 10 336\begin{align*}\frac{3}{36}\end{align*} 5 436\begin{align*}\frac{4}{36}\end{align*} 11 236\begin{align*}\frac{2}{36}\end{align*} 6 536\begin{align*}\frac{5}{36}\end{align*} 12 136\begin{align*}\frac{1}{36}\end{align*} 7 636\begin{align*}\frac{6}{36}\end{align*}

Example C

Create a probability histogram of the possible outcomes of rolling two dice. You may use your data from Example B.

Solution: In Example B, we created a table of the probabilities of each outcome of rolling two dice, designated as discrete random variable S\begin{align*}S\end{align*}. Let’s add one more column for each value so we can convert the fractional probability to decimal:

 S\begin{align*}S\end{align*} P(S)\begin{align*}P(S)\end{align*} P(S)\begin{align*}P(S)\end{align*} decimal S\begin{align*}S\end{align*} P(S)\begin{align*}P(S)\end{align*} P(S)\begin{align*}P(S)\end{align*} decimal 2 136\begin{align*}\frac{1}{36}\end{align*} .028 8 536\begin{align*}\frac{5}{36}\end{align*} .139 3 236\begin{align*}\frac{2}{36}\end{align*} .056 9 436\begin{align*}\frac{4}{36}\end{align*} .111 4 336\begin{align*}\frac{3}{36}\end{align*} .083 10 336\begin{align*}\frac{3}{36}\end{align*} .083 5 436\begin{align*}\frac{4}{36}\end{align*} .111 11 236\begin{align*}\frac{2}{36}\end{align*} .056 6 536\begin{align*}\frac{5}{36}\end{align*} .139 12 136\begin{align*}\frac{1}{36}\end{align*} .028 7 636\begin{align*}\frac{6}{36}\end{align*} .167

We can use this data to create a histogram, setting the y\begin{align*}y\end{align*}-axis to the probability and the x\begin{align*}x\end{align*}-axis to the values of S\begin{align*}S\end{align*}:

##### Concept Problem Revisited

Writing down all of the various probabilities of outcomes of an event is fine, but it can get a little tedious both to create and to read a long list of different probabilities. How else can we display the information from a probability distribution?

Tables, histograms, bar graphs and pie charts are the most common visual representations of probability distributions.

#### Vocabulary

A histogram is a specific form of a bar chart where the bars are proportional in area to the frequency and proportional in width to the interval represented by the bar.

#### Guided Practice

1. Let R\begin{align*}R\end{align*} be a discrete random variable representing the number of red marbles pulled over three trials of pulling and replacing one marble out of a bag containing 4 red, 4 yellow, and 4 green marbles. Create a probability distribution table for R\begin{align*}R\end{align*}.
2. Let S\begin{align*}S\end{align*} be a discrete random variable representing the number of 2’s you spin over 5 spins on a spinner with 4 equally-spaced points. Create a histogram showing the probability distribution of S\begin{align*}S\end{align*}.
3. Create a probability distribution table for the outcomes of the sum of two 5-sided dice.

Solutions:

1. The possible values of \begin{align*}R\end{align*} are 1, 2, and 3. There is a \begin{align*}\frac{1}{3}\end{align*} chance or red on each pull. The probability distribution for \begin{align*}R\end{align*} would thus be:

 \begin{align*}P(1)\end{align*} \begin{align*}0.333\end{align*} \begin{align*}P(2)\end{align*} \begin{align*}(.333)^2=.111\end{align*} \begin{align*}P(3)\end{align*} \begin{align*}(.333)^2=.037\end{align*}

2. The possible values of \begin{align*}S\end{align*} are 1, 2, 3, 4, and 5. There is a \begin{align*}\frac{1}{4}\end{align*} chance of a 2 on each spin:

3. Let’s start by creating a grid to show all of the possible combinations:

 1 2 3 4 5 1 2 3 4 5 6 2 3 4 5 6 7 3 4 5 6 7 8 4 5 6 7 8 9 5 6 7 8 9 10

Now we can create a distribution based on the probability of each possible outcome 2-10, let \begin{align*}R\end{align*} be a discrete random variable representing the sum of the dice:

 \begin{align*}R\end{align*} 2 3 4 5 6 7 8 9 10 \begin{align*}P(R)\end{align*} \begin{align*}\frac{1}{25} = .04\end{align*} \begin{align*}\frac{2}{25} =.08\end{align*} \begin{align*}\frac{3}{25} =.12\end{align*} \begin{align*}\frac{4}{25} =.16\end{align*} \begin{align*}\frac{5}{25} =.02\end{align*} \begin{align*}\frac{4}{25} =.16\end{align*} \begin{align*}\frac{3}{25} =.12\end{align*} \begin{align*}\frac{2}{25} =.08\end{align*} \begin{align*}\frac{1}{25} =.04\end{align*}

#### Practice Problems

1. Create a probability distribution table for a single roll of two 7-sided dice.
2. Create a histogram to visualize the data from problem 1.
3. Create a pie chart showing the same data.
4. There are 12 green, 9 blue, and 4 red candies in an opaque bag. Let \begin{align*}R\end{align*} be a discrete random variable representing the number of red candies you get in a row by pulling and replacing one candy four times. Create a probability distribution table illustrating the possible outcomes of \begin{align*}R\end{align*}.
5. Create a histogram illustrating the information from problem 4.
6. Create a pie chart showing the same data.
7. Let discrete random variable \begin{align*}S\end{align*} represent the number of 7’s you get when rolling two 5-sided dice three times. Create a probability distribution table for \begin{align*}S\end{align*}.
8. Create a histogram illustrating the information from problem 7.
9. Create a pie chart with the same information.
10. Let \begin{align*}T\end{align*} be the number of tails you get when you flip a fair coin 4 times, create a probability distribution table for \begin{align*}T\end{align*}.
11. Create a histogram or bar chart for \begin{align*}T\end{align*}, from problem 10.
12. Create a pie chart for \begin{align*}T\end{align*} from problem 10.

### Vocabulary Language: English

Histogram

Histogram

A histogram is a display that indicates the frequency of specified ranges of continuous data values on a graph in the form of immediately adjacent bars.
probability distribution

probability distribution

In a probability distribution, you may have a table, a graph, or a chart that shows you all the possible values of X (your variable), and the probability associated with each of these values P(X).