Deck 7: Random Variables and Discrete Probability Distributions
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Deck 7: Random Variables and Discrete Probability Distributions
1
The Poisson probability distribution is a continuous probability distribution.
False
2
In a(n) ____________________ experiment, the probability of a success in an interval is the same for all equal-sized intervals.
Poisson
3
In a Poisson distribution, the mean and standard deviation are equal.
False
4
The Sutton police department must write, on average, 6 tickets a day to keep department revenues at budgeted levels. Suppose the number of tickets written per day follows a Poisson distribution with a mean of 6.5 tickets per day. Interpret the value of the mean.
A)The mean has no interpretation.
B)The expected number of tickets written would be 6.5 per day.
C)Half of the days have less than 6.5 tickets written and half of the days have more than 6.5 tickets written.
D)The number of tickets that is written most often is 6.5 tickets per day.
A)The mean has no interpretation.
B)The expected number of tickets written would be 6.5 per day.
C)Half of the days have less than 6.5 tickets written and half of the days have more than 6.5 tickets written.
D)The number of tickets that is written most often is 6.5 tickets per day.
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5
The number of accidents that occur at a busy intersection in one month is an example of a Poisson random variable.
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6
The Poisson distribution is applied to events for which the probability of occurrence over a given span of time, space, or distance is very small.
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7
The largest value that a Poisson random variable X can have is n.
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8
The mean of a Poisson distribution, where is the average number of successes occurring in a specified interval, is .
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9
On the average, 1.6 customers per minute arrive at any one of the checkout counters of Sunshine food market. What type of probability distribution can be used to find out the probability that there will be no customers arriving at a checkout counter in 10 minutes?
A)Poisson distribution
B)Normal distribution
C)Binomial distribution
D)None of these choices.
A)Poisson distribution
B)Normal distribution
C)Binomial distribution
D)None of these choices.
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10
The Poisson random variable is a:
A)discrete random variable with infinitely many possible values.
B)discrete random variable with finite number of possible values.
C)continuous random variable with infinitely many possible values.
D)continuous random variable with finite number of possible values.
A)discrete random variable with infinitely many possible values.
B)discrete random variable with finite number of possible values.
C)continuous random variable with infinitely many possible values.
D)continuous random variable with finite number of possible values.
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11
The Poisson random variable is a discrete random variable with infinitely many possible values.
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12
In a Poisson distribution, the variance and standard deviation are equal.
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13
In a Poisson experiment, the number of successes that occur in any interval of time is ____________________ of the number of success that occur in any other interval.
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14
In a Poisson distribution, the:
A)mean equals the standard deviation.
B)median equals the standard deviation.
C)mean equals the variance.
D)None of these choices.
A)mean equals the standard deviation.
B)median equals the standard deviation.
C)mean equals the variance.
D)None of these choices.
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15
Which of the following cannot have a Poisson distribution?
A)The length of a movie.
B)The number of telephone calls received by a switchboard in a specified time period.
C)The number of customers arriving at a gas station in Christmas day.
D)The number of bacteria found in a cubic yard of soil.
A)The length of a movie.
B)The number of telephone calls received by a switchboard in a specified time period.
C)The number of customers arriving at a gas station in Christmas day.
D)The number of bacteria found in a cubic yard of soil.
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16
Given a Poisson random variable X, where the average number of successes occurring in a specified interval is 1.8, then P(X = 0) is:
A)1.8
B)1.3416
C)0.1653
D)6.05
A)1.8
B)1.3416
C)0.1653
D)6.05
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17
In a Poisson distribution, the mean and variance are equal.
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18
A community college has 150 word processors. The probability that any one of them will require repair on a given day is 0.025. To find the probability that exactly 25 of the word processors will require repair, one will use what type of probability distribution?
A)Normal distribution
B)Poisson distribution
C)Binomial distribution
D)None of these choices.
A)Normal distribution
B)Poisson distribution
C)Binomial distribution
D)None of these choices.
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19
The number of customers arriving at a department store in a 5-minute period has a Poisson distribution.
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20
The number of customers making a purchase out of 30 randomly selected customers has a Poisson distribution.
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21
In a Poisson experiment, the probability of a success in an interval is ____________________ to the size of the interval.
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22
NARRBEGIN: 911 Phone Calls
911 Phone Calls
911 phone calls arrive at the rate of 30 per hour at the local call center.NARREND
-{911 Phone Calls Narrative} If no calls are currently being processed, what is the probability that the desk employee can take four minutes break without being interrupted?
911 Phone Calls
911 phone calls arrive at the rate of 30 per hour at the local call center.NARREND
-{911 Phone Calls Narrative} If no calls are currently being processed, what is the probability that the desk employee can take four minutes break without being interrupted?
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23
Compute the following Poisson probabilities (to 4 decimal places) using the Poisson formula:
a.P(X = 3), if = 2.5
b.P(X 1), if = 2.0
c.P(X 2), if = 3.0
a.P(X = 3), if = 2.5
b.P(X 1), if = 2.0
c.P(X 2), if = 3.0
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24
In the Poisson distribution, the mean is equal to the ____________________.
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25
A Poisson random variable is a(n) ____________________ random variable.
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26
NARRBEGIN: Post office
Post office
The number of arrivals at a local post office between 3:00 and 5:00 P.M. has a Poisson distribution with a mean of 12.NARREND
-{{Post Office Narrative} Find the probability that the number of arrivals between 4:00 and 5:00 P.M. is exactly two.
Post office
The number of arrivals at a local post office between 3:00 and 5:00 P.M. has a Poisson distribution with a mean of 12.NARREND
-{{Post Office Narrative} Find the probability that the number of arrivals between 4:00 and 5:00 P.M. is exactly two.
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27
Let X be a Poisson random variable with = 6. Use the table of Poisson probabilities to calculate:
a.P(X 8)
b.P(X = 8)
c.P(X 5)
d.P(6 X 10)
a.P(X 8)
b.P(X = 8)
c.P(X 5)
d.P(6 X 10)
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28
NARRBEGIN: Post office
Post office
The number of arrivals at a local post office between 3:00 and 5:00 P.M. has a Poisson distribution with a mean of 12.NARREND
-{Post Office Narrative} Find the probability that the number of arrivals between 3:00 and 5:00 P.M. is at least 10.
Post office
The number of arrivals at a local post office between 3:00 and 5:00 P.M. has a Poisson distribution with a mean of 12.NARREND
-{Post Office Narrative} Find the probability that the number of arrivals between 3:00 and 5:00 P.M. is at least 10.
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29
The possible values of a Poisson random variable start at ____________________.
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30
A Poisson random variable is the number of successes that occur in a period of ____________________ or an interval of ____________________ in a Poisson experiment.
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31
NARRBEGIN: 911 Phone Calls
911 Phone Calls
911 phone calls arrive at the rate of 30 per hour at the local call center.NARREND
-{911 Phone Calls Narrative} Find the probability of receiving two calls in a five-minute interval of time.
911 Phone Calls
911 phone calls arrive at the rate of 30 per hour at the local call center.NARREND
-{911 Phone Calls Narrative} Find the probability of receiving two calls in a five-minute interval of time.
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32
NARRBEGIN: Classified Department Pho
Classified Department Phone Calls
A classified department receives an average of 10 telephone calls each afternoon between 2 and 4 P.M. The calls occur randomly and independently of one another.NARREND
-{Classified Department Phone Calls Narrative} Find the probability that the department will receive at least five calls between 2 and 4 P.M. on a particular afternoon.
Classified Department Phone Calls
A classified department receives an average of 10 telephone calls each afternoon between 2 and 4 P.M. The calls occur randomly and independently of one another.NARREND
-{Classified Department Phone Calls Narrative} Find the probability that the department will receive at least five calls between 2 and 4 P.M. on a particular afternoon.
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33
The ____________________ of a Poisson distribution is the rate at which successes occur for a given period of time or interval of space.
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34
NARRBEGIN: Post office
Post office
The number of arrivals at a local post office between 3:00 and 5:00 P.M. has a Poisson distribution with a mean of 12.NARREND
-{Post Office Narrative} Find the probability that the number of arrivals between 3:30 and 4:00 P.M. is at least 10.
Post office
The number of arrivals at a local post office between 3:00 and 5:00 P.M. has a Poisson distribution with a mean of 12.NARREND
-{Post Office Narrative} Find the probability that the number of arrivals between 3:30 and 4:00 P.M. is at least 10.
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35
In Poisson experiment, the probability of more than one success in an interval approaches ____________________ as the interval becomes smaller.
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36
NARRBEGIN: Classified Department Pho
Classified Department Phone Calls
A classified department receives an average of 10 telephone calls each afternoon between 2 and 4 P.M. The calls occur randomly and independently of one another.NARREND
-{Classified Department Phone Calls Narrative} Find the probability that the department will receive 13 calls between 2 and 4 P.M. on a particular afternoon.
Classified Department Phone Calls
A classified department receives an average of 10 telephone calls each afternoon between 2 and 4 P.M. The calls occur randomly and independently of one another.NARREND
-{Classified Department Phone Calls Narrative} Find the probability that the department will receive 13 calls between 2 and 4 P.M. on a particular afternoon.
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37
Let X be a Poisson random variable with = 8. Use the table of Poisson probabilities to calculate:
a.P(X 6)
b.P(X = 4)
c.P(X 3)
d.P(9 X 14)
a.P(X 6)
b.P(X = 4)
c.P(X 3)
d.P(9 X 14)
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38
NARRBEGIN: Classified Department Pho
Classified Department Phone Calls
A classified department receives an average of 10 telephone calls each afternoon between 2 and 4 P.M. The calls occur randomly and independently of one another.NARREND
-{Classified Department Phone Calls Narrative} Find the probability that the department will receive seven calls between 2 and 3 P.M. on a particular afternoon.
Classified Department Phone Calls
A classified department receives an average of 10 telephone calls each afternoon between 2 and 4 P.M. The calls occur randomly and independently of one another.NARREND
-{Classified Department Phone Calls Narrative} Find the probability that the department will receive seven calls between 2 and 3 P.M. on a particular afternoon.
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39
In the Poisson distribution, the ____________________ is equal to the variance.
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40
NARRBEGIN: 911 Phone Calls
911 Phone Calls
911 phone calls arrive at the rate of 30 per hour at the local call center.NARREND
-{911 Phone Calls Narrative} Find the probability of receiving exactly eight calls in 15 minutes.
911 Phone Calls
911 phone calls arrive at the rate of 30 per hour at the local call center.NARREND
-{911 Phone Calls Narrative} Find the probability of receiving exactly eight calls in 15 minutes.
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41
The expected number of heads in 100 tosses of an unbiased coin is
A)25
B)50
C)75
D)100
A)25
B)50
C)75
D)100
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42
The binomial distribution deals with consecutive trials, each of which has two possible outcomes.
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43
NARRBEGIN: Post office
Post office
The number of arrivals at a local post office between 3:00 and 5:00 P.M. has a Poisson distribution with a mean of 12.NARREND
Suppose that the number of buses arriving at a Depot per minute is a Poisson process. If the average number of buses arriving per minute is 3, what is the probability that exactly 6 buses arrive in the next minute?
Post office
The number of arrivals at a local post office between 3:00 and 5:00 P.M. has a Poisson distribution with a mean of 12.NARREND
Suppose that the number of buses arriving at a Depot per minute is a Poisson process. If the average number of buses arriving per minute is 3, what is the probability that exactly 6 buses arrive in the next minute?
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44
The standard deviation of a binomial random variable X is given by the formula 2= np(1 - p), where n is the number of trials, and p is the probability of success.
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45
NARRBEGIN: Unsafe Levels of Radioact
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the standard deviation of the number of incidents is in one year.
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the standard deviation of the number of incidents is in one year.
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46
NARRBEGIN: Unsafe Levels of Radioact
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the probability that there will be exactly 3 incidents in a year.
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the probability that there will be exactly 3 incidents in a year.
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47
If the probability of success p remains constant in a binomial distribution, an increase in n will increase the variance.
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48
NARRBEGIN: Unsafe Levels of Radioact
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the variance of the number of incidents in one year.
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the variance of the number of incidents in one year.
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49
If X is a binomial random variable with n = 25, and p = 0.25, then P(X = 25) = 1.0.
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50
NARRBEGIN: Unsafe Levels of Radioact
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactiviy Narrative} Find the probability that there will be at least 1 incident in a year.
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactiviy Narrative} Find the probability that there will be at least 1 incident in a year.
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51
The variance of a binomial distribution for which n = 50 and p = 0.20 is 8.0.
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52
The number of female customers out of a random sample of 100 customers arriving at a department store has a binomial distribution.
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53
The expected number of heads in 250 tosses of an unbiased coin is 125.
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54
The binomial random variable is the number of successes that occur in a fixed period of time.
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55
NARRBEGIN: Unsafe Levels of Radioact
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the probability that there will be at least 3 incidents in a year.
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the probability that there will be at least 3 incidents in a year.
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56
The number of customers arriving at a department store in a 5-minute period has a binomial distribution.
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57
Which of the following about the binomial distribution is not a true statement?
A)The probability of success must be constant from trial to trial.
B)The random variable of interest is continuous.
C)Each outcome may be classified as either "success" or "failure".
D)Each outcome is independent of the other.
A)The probability of success must be constant from trial to trial.
B)The random variable of interest is continuous.
C)Each outcome may be classified as either "success" or "failure".
D)Each outcome is independent of the other.
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58
NARRBEGIN: Unsafe Levels of Radioact
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the probability that there will be no more than 1 incident in a year.
Unsafe Levels of Radioactivity
The number of incidents at a nuclear power plant has a Poisson distribution with a mean of 6 incidents per year.NARREND
{Unsafe Levels of Radioactivity Narrative} Find the probability that there will be no more than 1 incident in a year.
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59
The binomial probability distribution is a discrete probability distribution.
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60
If the probability of success p remains constant in a binomial distribution, an increase in n will not change the mean.
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61
The variance of a binomial distribution is equal to ____________________.
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62
Which of the following is not a characteristic of a binomial experiment?
A)Each trial results in two or more outcomes.
B)There is a sequence of identical trials.
C)The trials are independent of each other.
D)The probability of success p is the same from one trial to another.
A)Each trial results in two or more outcomes.
B)There is a sequence of identical trials.
C)The trials are independent of each other.
D)The probability of success p is the same from one trial to another.
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63
Evaluate the following binomial coefficients.
a.
b.
c.
d.
a.
b.
c.
d.
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64
If n = 10 and p = 0.60, then the mean of the binomial distribution is
A)0.06
B)2.65
C)6.00
D)5.76
A)0.06
B)2.65
C)6.00
D)5.76
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65
The variance of a binomial distribution for which n = 100 and p = 0.20 is:
A)100
B)80
C)20
D)16
A)100
B)80
C)20
D)16
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66
NARRBEGIN: Stress
Stress
Consider a binomial random variable X with n = 5 and p = 0. 40, where X represents the number of times in the final exam week a student with 18 credit hours may feel stressed.NARREND
{Stress Narrative} Find the expected number of times a student may feel stressed during the final exam week.
Stress
Consider a binomial random variable X with n = 5 and p = 0. 40, where X represents the number of times in the final exam week a student with 18 credit hours may feel stressed.NARREND
{Stress Narrative} Find the expected number of times a student may feel stressed during the final exam week.
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67
A binomial experiment consists of a(n) ____________________ number of trials, n.
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68
If n= 20 and p = 0.70, then the standard deviation of the binomial distribution is
A)0.14
B)2.05
C)14.0
D)14.7
A)0.14
B)2.05
C)14.0
D)14.7
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69
To find the probability that X is at most 10, you should find the probability that X is 10 or ____________________.
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70
NARRBEGIN: Stress
Stress
Consider a binomial random variable X with n = 5 and p = 0. 40, where X represents the number of times in the final exam week a student with 18 credit hours may feel stressed.NARREND
{Stress Narrative} Find the probability distribution of X.
Stress
Consider a binomial random variable X with n = 5 and p = 0. 40, where X represents the number of times in the final exam week a student with 18 credit hours may feel stressed.NARREND
{Stress Narrative} Find the probability distribution of X.
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71
The probability P(X x) is called a(n) ____________________ probability. The binomial table reports these probabilities.
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72
The mean of a binomial distribution is equal to ____________________.
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73
NARRBEGIN: Stress
Stress
Consider a binomial random variable X with n = 5 and p = 0. 40, where X represents the number of times in the final exam week a student with 18 credit hours may feel stressed.NARREND
{Stress Narrative} Find P(X < 3).
Stress
Consider a binomial random variable X with n = 5 and p = 0. 40, where X represents the number of times in the final exam week a student with 18 credit hours may feel stressed.NARREND
{Stress Narrative} Find P(X < 3).
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74
NARRBEGIN: Stress
Stress
Consider a binomial random variable X with n = 5 and p = 0. 40, where X represents the number of times in the final exam week a student with 18 credit hours may feel stressed.NARREND
-{Stress Narrative} Find P(2 X 4).
Stress
Consider a binomial random variable X with n = 5 and p = 0. 40, where X represents the number of times in the final exam week a student with 18 credit hours may feel stressed.NARREND
-{Stress Narrative} Find P(2 X 4).
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75
The trials in a binomial experiment are ____________________, meaning the outcome of one trial does not affect the outcomes of any other trials.
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76
To find the probability that X is at least 10, you should find the probability that X is 10 or ____________________.
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77
The probability of a success in a binomial experiment is denoted by ____________________.
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78
The probability of a failure in a binomial experiment is denoted by ____________________.
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79
In each trial of a binomial experiment, there are ____________________ possible outcomes.
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80
The expected value, E(X), of a binomial probability distribution with n trials and probability p of success is:
A)n + p
B)np(1 - p)
C)np
D)n + p - 1
A)n + p
B)np(1 - p)
C)np
D)n + p - 1
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