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At the end of the lesson, students can: Recognize and describe the 4 attributes of a binomial distribution. Use binompdf and binomcdf commands Determine.

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Presentation on theme: "At the end of the lesson, students can: Recognize and describe the 4 attributes of a binomial distribution. Use binompdf and binomcdf commands Determine."— Presentation transcript:

1 At the end of the lesson, students can: Recognize and describe the 4 attributes of a binomial distribution. Use binompdf and binomcdf commands Determine a binomial coefficient Determine the mean and standard deviation of a binomial distribution

2 The Binomial Setting – a situation where the following 4 conditions are satisfied … (remember BINS) 1. 2. 3. 4. B inary? The possible outcomes of each trial can be classified as “success” or “failure”. I ndependent? Does knowing the result of one trial must not have any effect on the result of any other trial. N umber? The number of trials n of the chance process must be fixed in advance. S uccess? On each trial, the probability p of success must be the same.

3 * If data are produced in a binomial setting, then the random variable X = number of successes is called a binomial random variable. * The distribution of X in the binomial setting is the binomial distribution with parameters n and p. NOTATION: X is _______________ n = ________________________ p = ________________________ possible values of X are the whole #s 0 to n. # of successes # of trials in the chance process probability of success on any one trial

4 One of the lowest scoring AP Free Response Test questions are on binomial distribution because often students do not recognize that using the binomial distribution is appropriate. So let’s practice identifying binomial distributions. Remember, when you are having trouble answering a probability question, check to see if it is a binomial setting! (BINS)

5 Examples: Is it reasonable to use a binomial distribution as a model for the following situations? A basketball player makes 68% of his free throws.. During a particular game, he shoots 10 free throws. X = # of shots made. B inary? Yes success = make a shot I ndependent? Yes, it is reasonable to assume that making one shot does not change the probability of making another. N umber? Yes, there are 10 free throws S uccess? Yes, he has a 68% chance each time. This is a binomial setting. X is a binomial random variable with parameters n = 10 and p = 0.68

6 B inary? Yes success = blood type O I ndependent? Yes, children inherit genes determining blood type independently from their parents. N umber? Yes, there are 5 children S uccess? Yes, the probability of a “success” is 0.25. Examples: Is it reasonable to use a binomial distribution as a model for the following situations? The probability of having the blood type O from a particular set of parents is 0.25. The couple has 5 children. X = number of children with blood type O. This is a binomial setting. X is a binomial random variable with parameters n = 5 and p = 0.25

7 B inary? Yes success = # of red cards I ndependent? No, since you are not replacing the cards, each card’s probability is affected by the card dealt before it. This is a NOT binomial setting. Examples: Is it reasonable to use a binomial distribution as a model for the following situations? Deal 10 cards from a shuffled deck of 52 cards. X = # of red cards.

8 B inary? No, there are more than two possible colors. Also, C is not even a random variable since the outcomes aren’t numerical. Examples: Is it reasonable to use a binomial distribution as a model for the following situations? Observe the next 100 cars that go by and let C = color. This is not a binomial setting.

9 B inary? Yes success = the number of sixes I ndependent? Yes, the die is fair and one roll does not affect the probability of the next roll. N umber? Yes, rolling the die 10 times S uccess? Yes, the probability of a “success” is 1/6 or 0.167. Examples: Is it reasonable to use a binomial distribution as a model for the following situations? Roll a fair die 10 times and let X = the number of sixes. This is a binomial setting. X is a binomial random variable with parameters n = 10 and p = 0.167.

10 More practice examples on p. 384 in book and Check Your Understanding (answers in back of book on p. 385)

11 54321 = 120 1

12 Flip a coin 5 times. Consider getting a “heads” a success. Determine the number of different arrangements of 3 successes (3 heads) among 5 observations (5 coin tosses). Or you can put in your calculator Under the Math menu  PRB  option 3: nCr 5 nCr 3 = 10

13 *Binomial probability – If X has the binomial distribution with n observations and probability p of success on each observation, the possible values of X are 0, 1, 2, …, n. If k is any one of these values, then: This is the binompdf function in the calc – this formula is on the formula sheet, so you just need to know when and how to use it!

14 Each child born to a particular set of parents has probability 0.25 of having blood type O. If these parents have 5 children, what is the probability that exactly 2 of them have type O blood? There is a 26.37% chance that exactly 2 children have O type blood.

15 Suppose you purchase a bundle of 10 bare-root broccoli plants. The sales clerk tells you that on average you can expect 5% of the plants to die before producing any broccoli. Assume that the bundle is a random sample of plants. Use the binomial formula to find the probability that you will lose at most one of the broccoli plants. Note that you can check your answer in your calculator using the binomcdf(10,.05, 1)

16 The probability of having the blood type O from a particular set of parents is 0.25. The couple has 5 children. X = number of children with blood type O. Use the binomial probability formula to find the probability that at least one of the children in this example has blood type O. B(5, 0.25) There is a 76.27% that at least one of the children will have blood type O.

17 Finding Binomial Probabilities – you’ve calculated these probabilities by hand, and now, we’ll use our calculators! TI-84: binompdf (n, p, X)  found under 2 nd DISTR / 0:binompdf “pdf” stands for probability distribution function. If X is a discrete random variable, the pdf assigns a probability to each value of X. Please note that on the AP Free Response Exam, you will not receive much credit for just showing the calculator technique. At the very least, you must indicate what each of those calculator inputs represent. How to show complete work will be in the future slides.

18 Corinne is a basketball player who makes 75% of her free throws over the course of a season. In a particular game, Corinne shoots 12 free throws. What is the probability that she makes exactly 8 of the 12 shots? (Check BINS!) P(X = 8) = Binompdf(12,0.75,8) = 0.1936 Corinne has a 19.36% probability of making 8 of the 12 free throws.

19 A quality engineer selects an SRS of 10 switches from a large shipment for detailed inspection. Unknown to the engineer, 10% of the switches in the shipment fail to meet the specifications. What is the probability that no more than 1 of the 10 switches in the sample fail inspection? P(X ≤ 1) = P(X = 0) + P(X = 1) = Binompdf(10,0.10,0) + Binompdf(10,0.10,1) = 0.7361 There is a 73.61% chance of no more than 1 of the 10 switches in the sample to fail inspection.

20 Corinne is a basketball player who makes 75% of her free throws over the course of a season. In a particular game, Corinne shoots 12 free throws. What is the probability that she makes at most 8 of the 12 shots? P(X ≤ 8) = P(X=0)+ P(X=1) +... +P(X=8) = Binompdf(12,0.75,0) + Binompdf(12,0.75,1) + Binompdf(12,0.75,2) + Binompdf(12,0.75,3) + Binompdf(12,0.75,4) + Binompdf(12,0.75,5) + Binompdf(12,0.75,6) + Binompdf(12,0.75,7) + Binompdf(12,0.75,8) = 0.3512

21 *Oftentimes, we want to find the probability that a random variable takes a range of values (problem #2 and 3) as opposed to a specific value (#1). The cumulative binomial probability is useful in these cases. Cumulative distribution function (cdf) of random variable X calculates the sum of the probabilities for 0, 1, 2, …, up to the value X. In other words, it calculates the probability of obtaining at most X success in n trials. TI-83: binomcdf (n, p, X)  found under 2 nd DISTR / A:binomcdf

22 Corinne is a basketball player who makes 75% of her free throws over the course of a season. In a particular game, Corinne shoots 12 free throws. What is the probability that she makes at most 8 of the 12 shots? Use the cumulative distribution function. P(X≤8) = Binomcdf(12,0.75,8) = 0.35122 There is a 35.12% probability that Corinne will make at most 8 of the 12 shots.

23 A quality engineer selects an SRS of 10 switches from a large shipment for detailed inspection. Unknown to the engineer, 10% of the switches in the shipment fail to meet the specifications. X = # of defective switches, B(10, 0.1) probability that there is at most 3 defective switches probability that there are more than 3 defective switches probability that there are more than 4 defective switches P(X≤3)=Binomcdf(10, 0.1, 3) = 0.9872 P(X>3)= 1 - Binomcdf(10, 0.1, 3) = 0.0128 P(X>4)= 1 - Binomcdf(10, 0.1, 4) =.0016

24 Binomial Mean and Standard Deviation – these formulas only work for binomial distributions!! Check BINS! If a count X has the binomial distribution with number of observations n and probability of success p, then the mean and standard deviation of X are: Mean: Standard Deviation: These are also in your formula packet!!! μ x = np σ x = √np(1 – p)

25 A factory employs several thousand workers, of whom 30% are women. If the 15 members of the union executive committee were chosen from the workers at random, the number of women on the committee would have the binomial distribution with n = ________ and p = ________. Find the mean number of women on a randomly chosen committee of 15 workers. What is the standard deviation of the count X of women members on the committee? 15.30 15(.30) = 4.5 This means of a randomly selected committee of 15 members, we would expect there to be between 4 and 5 women members √15(.30)(1-.30)=1.77 This means of the randomly selected 15 members, the number of women members would differ from 4.5 by an average of 1.77.

26 Read Textbook pages p. 382 – 393 Do exercises p. 403 – 404 #71 – 73, 75 – 78, 80, 82, 84 Check answers to odd problems

27 At the end of the lesson, students can: Recognize and describe the 4 attributes of a binomial distribution. Use binompdf and binomcdf commands Determine a binomial coefficient Determine the mean and standard deviation of a binomial distribution


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