1. Binomial Distribution
Binomial distribution is the probability distribution for a binomial experiment
Helps find probabilities when there are a large number of trials

2. Characteristics
Each trial has two outcomes or can be reduced to two outcomes.
Ex: when rolling a die, getting odd or even, or rolling a two or not a two
There is a fixed number of trials
Outcomes of each trial must be mutually exclusive
P(s) – probability of success must remain same for each trial (independent events)

3. Examples of Binomial Experiments
Any experiment with only two possible outcomes
Tossing a coin
Type of child (boy or girl)
Rolling a die (3 or not 3)
Red or Black card

4. Binomial Distribution
A coin is tossed 3 times. Find the probability of getting exactly 2 heads.
Sample Space H T
Binomial Distribution
X = # of heads 2
Not 2
P(x)
3/8
5/8

5. Mean and Standard Deviation of a Binomial Distribution
Formula for mean:
Formula for standard deviation:
Reminder: n is the # of trials (or sample size)
p is the probability of success
q is 1 - p

6. Example 1: mean and standard deviation
A card is selected from a standard deck of cards and then replaced. Find the mean and standard deviation of the # of aces selected if you pick 20 cards.
n = 20
p = 4/52
q = 48/52

7. Example 2:
The probability that a divorcee will remarry within 3 years is 40%. In a sample of 200 divorcees, find the mean and standard deviation of the number of people that will remarry within 3 years.
n = 200
p = .40
q = .60

8. Finding the Probability of a Binomial Distribution – Example 1
A coin is tossed 3 times. Find the probability of getting exactly 2 heads.
Sample Space H T
Binomial Distribution
X = # of heads 2
Not 2
P(x)
3/8
5/8
Consider: What if we tossed the coin 20 times?
220 = sample space = 1,048,576 possibilities

9. Formula Formula: x = number of successes (what you are looking for)
n = number of trials,
p = probability of success on a single trial
q = probability of failure on a single trial (q = 1 – p)

10. Using the formula: Example 1
A coin is tossed 3 times. Find the probability of getting exactly two heads.
x = 2 heads
n = 3
p = ½
q = ½

11. Example 2
A coin is tossed 20 times. Find the probability of getting exactly two heads.
x = 2 heads
n = 20
p = ½
q = ½

12. Example 3:
In a survey, 75% students said the courts show too much concern for criminals. Find the probability that 3 out of 7 randomly selected students will agree with the statement.
n = 7
x = 3
p = .75
q = .25

13. Modification to Example 3
Find the probability that at most 2 out of 7 will agree.
x = 0, 1, 2

14. Example 4:
A coin is tossed 8 times. Find the probability of getting at least 2 heads.
x = 2, 3, 4, 5,
6, 7, 8
n = 8
p = 1/2
q = 1/2
Easier to use the complement rule: Find probability of 0 or 1 head and then subtract from 1. x = 0, 1

15. Example 4: Answer

16. Example 5:
If the probability is .40 that a divorcee will remarry within 3 years, find the probabilities that of 10 divorcees:
(a) at least 8 will remarry within 3 years
(b) at least 2 will remarry within 3 years
P(at least 8) = .0131
P(at least 2) = .954

17. Normal Approximation to the Binomial Distribution
A coin is tossed 50 times. Find the probability of getting at least 20 heads.
x = 20 or more heads
n = 50
p = ½
q = ½

18. We can use the normal distribution to find probabilities like this as long as the following conditions apply:
It is a binomial distribution (properties)
Probability of a success must be close to .5
If both np and nq are greater than or equal to 5

19. From Coin Toss Example
A coin is tossed 50 times. Find the probability of getting at least 20 heads.
x = 20 or more heads
n = 50
p = ½
q = ½
np = 50(.5) = 25
nq = 50(.5) = both greater than .5

20. Find continuity correction factor ( .5)
Calculate  and 
Find continuity correction factor ( .5)
summary on page 313 in text

21. Find z-score(s) – Use regular z-score formula
Determine area to be shaded and find it!

22. Example 2
Of the members of a bowling league, 10% are widowed. If 200 bowling league members are selected, find the probability that more than 10 will be widowed.

23. Example 3:
If a baseball player’s batting average is .320 find the probability that the player will get
a) at most 26 hits in 100 times at bat.
b) exactly 26 hits in 100 times at bat.