1. The Binomial Probability Distribution and Related Topics
Chapter 6
The Binomial Probability Distribution and Related Topics
Understanding Basic Statistics
Fifth Edition
By Brase and Brase
Prepared by Jon Booze

2. Statistical Experiments and Random Variables
Statistical Experiments – any process by which measurements are obtained.
A quantitative variable, x, is a random variable if its value is determined by the outcome of a random experiment.
Random variables can be discrete or continuous.

3. Random Variables and Their Probability Distributions
Discrete random variables – can take on only a countable or finite number of values.
Continuous random variables – can take on countless values in an interval on the real line
Probability distributions of random variables – An assignment of probabilities to the specific values or a range of values for a random variable.

4. Random Variables and Their Probability Distributions
Which measurement involves a discrete random variable?
a). Determine the mass of a randomly-selected penny
b). Assess customer satisfaction rated from 1 (completely satisfied) to 5 (completely dissatisfied).
c). Find the rate of occurrence of a genetic disorder in a given sample of persons.
d). Measure the percentage of light bulbs with lifetimes less than 400 hours.

5. Random Variables and Their Probability Distributions
Which measurement involves a discrete random variable?
a). Determine the mass of a randomly-selected penny
b). Assess customer satisfaction rated from 1 (completely satisfied) to 5 (completely dissatisfied).
c). Find the rate of occurrence of a genetic disorder in a given sample of persons.
d). Measure the percentage of light bulbs with lifetimes less than 400 hours.

6. Discrete Probability Distributions
Each value of the random variable has an assigned probability.
The sum of all the assigned probabilities must equal 1.

7. Probability Distribution Features
Since a probability distribution can be thought of as a relative-frequency distribution for a very large n, we can find the mean and the standard deviation.
When viewing the distribution in terms of the population, use µ for the mean and σ for the standard deviation.

8. Means and Standard Deviations for Discrete Probability Distributions

9. Binomial Experiments S = success F = failure
There are a fixed number of trials. This is denoted by n.
The n trials are independent and repeated under identical conditions.
Each trial has two outcomes:
S = success F = failure

10. Binomial Experiments
Which of the following does not involve binomial trials?
a). A recyclable item is placed into a bin meant for paper, plastic, or glass.
b). A randomly-selected student passes a statistics course.
c). A electronic power supply is rejected if it delivers less than 300 milliamps of current.
d). A given concept is classified as “traditional” or “modern”.

11. Binomial Experiments
Which of the following does not involve binomial trials?
a). A recyclable item is placed into a bin meant for paper, plastic, or glass.
b). A randomly-selected student passes a statistics course.
c). A electronic power supply is rejected if it delivers less than 300 milliamps of current.
d). A given concept is classified as “traditional” or “modern”.

12. Binomial Experiments
For each trial, the probability of success, p, remains the same. Thus, the probability of failure is 1 – p = q.
The central problem is to determine the probability of r successes out of n trials.

13. Determining Binomial Probabilities
Use the Binomial Probability Formula.
Use Table 2 of the appendix.
Use technology.

14. Binomial Probability Formula

15. Binomial Probability Formula
Find the probability of observing 6 successes in 10 trials if the probability of success is p = 0.4.
a) b) c) d)

16. Binomial Probability Formula
Find the probability of observing 6 successes in 10 trials if the probability of success is p = 0.4.
a) b) c) d)

17. Using the Binomial Table
Locate the number of trials, n.
Locate the number of successes, r.
Follow that row to the right to the corresponding p column.

18. Use Table 2 in the Appendix to find the probability of observing 3 successes in 5 trials if p = 0.7.
a) b) c) d)

19. Use Table 2 in the appendix to find the probability of observing 3 successes in 5 trials if p = 0.7.
a) b) c) d)

20. Binomial Probabilities
At times, we will need to calculate other probabilities:
P(r < k)
P(r ≤ k)
P(r > k)
P(r ≥ k)
where k is a specified value less than or equal to the number of trials, n.

21. Graphing a Binomial Distribution

22. Mean and Standard Deviation of a Binomial Distribution

23. Mean and Standard Deviation of a Binomial Distribution
Calculate the standard deviation of a binomial population with n = 100 and p = 0.3.
a). 21 b).9 c) d). 4.41

24. Mean and Standard Deviation of a Binomial Distribution
Calculate the standard deviation of a binomial population with n = 100 and p = 0.3.
a). 21 b).9 c) d). 4.41

25. Critical Thinking
Unusual values – For a binomial distribution, it is unusual for the number of successes r to be more than 2.5 standard deviations from the mean.
– This can be used as an indicator to determine whether a specified number of r out of n trials in a binomial experiment is unusual.

26. Critical Thinking
Unusual values – For a binomial distribution, it is unusual for the number of successes r to be more than 2.5 standard deviations from the mean.
A particular binomial experiment has a mean of 14 and a standard deviation of 2. Which of the following is not an unusual number of successes?
a) b).17
c) d). None of these are unusual.

27. Critical Thinking
Unusual values – For a binomial distribution, it is unusual for the number of successes r to be more than 2.5 standard deviations from the mean.
A particular binomial experiment has a mean of 14 and a standard deviation of 2. Which of the following is not an unusual number of successes?
a) b).17
c) d). None of these are unusual.