1. Probability Distributions

2. Essential Question: What is a probability distribution and how is it displayed?

3. Random Variable Variable whose value is determined by the outcome of a probability experiment. Example: roll a die, the variable is the number you roll, possibilities include: numbers 1-6.

4. Probability Distribution Data distribution that gives the probabilities of the values of a random variable. Represented by a histogram – Possible outcomes on horizontal axis – Probabilities on the vertical axis

5. Result of rolling a cube Values of random variable are consecutive whole numbers. Bars have width of 1 Centered on the value of the variable Area for each bar equals the probability of the corresponding outcome. Combined areas is the sum of the probabilities (1)

6. Cumulative Probability Probability that a random variable is less than or equal to a given value. Can be found by adding all the areas of the bars for all outcomes less than or equal to the given value.

7. Reflect 1a. In an experiment in which a coin is tossed twice, the random variable X is the number of times that the coins lands heads up. What are the possible values of the random variable?

8. Reflect 1b. A spinner has 8 equal sections, each labeled 1, 2, 3, or 4. The histogram shows the probability distribution for spinning the spinner. How many sections of the spinner are labeled with each number? How do you know?

9. Displaying a Probability Distribution You roll two number cubes at the same time. Let X be a random variable that represents the sum of the numbers you rolled. Make a histogram to show the probability distribution for X.

10. Complete the frequency table to show the number of ways you can get each sum in one roll of the number cubes. Sum23456789101112 Frequency1

11. Find the total number of outcomes Add the frequencies you found in part A to find the total number of possible outcomes. The total number of possible outcomes is: ___

12. Divide each frequency by the total number of outcomes Sum23456789101112 Probability

13. Histogram

14. Reflect 2a.

15. Theoretical vs. Experimental Theoretical Probability – finding the probability of events that come from a sample space of known equally likely outcomes. Experimental Probability – probability of an even occurring when an experiment is conducted.

16. Using a Simulation You flip a coin 7 times in a row. Use a simulation to determine the probability distribution for the number of times the coin lands heads up.simulation

17. Groups: Try it, and Record Data Trial1234 Number of heads Flip1234567 Result

18. Class Results Number of Heads 01234567 Frequency Relative Frequency **To find relative frequency, divide the frequency of the outcome by the total number of trials in the class. # of Trials: ________

19. Histogram

20. Reflect 3a. Describe the shape of the probability distribution.

21. Reflect 3b.

22. Reflect 3c. If you flipped a coin 7 times and got 7 heads, would this cause you to question whether the coin is fair? Why or why not?

23. Analyzing a Probability Distribution The histogram shows the theoretical probability distribution for the previous situation.

24. Analyzing a Probability Distribution

25. What is the probability of getting at least 1 head?

26. Reflect 4a. Why are the probabilities in the histogram you made different from the probabilities given in the histogram to the right?

27. Reflect 4b. What do you think would happen to the histogram you made in our trials if you included data from 1000 additional trials?

28. Reflect 4c. Why does it make sense that the histogram that shows the theoretical probabilities is symmetric?