Econ 210 Exam 2
The probability that Pete will catch fish on a particular day when he goes fishing is 0.8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. The variance of the number of days Pete will catch fish is .16 .48 .8 2.4
.48
A sample of 2,500 people was asked how many cups of coffee they drink in the morning. You are given the following sample information. Cups of Coffee Frequency 0 700 1 900 2 600 3 300 2,500 Refer to Exhibit 5-7. The variance of the number of cups of coffee is .96 .9798 1 2.4
.96
In a standard normal distribution, the range of values of z is from minus infinity to infinity -1 to 1 0 to 1 -3.09 to 3.09
0 to 1
If A and B are mutually exclusive events with P(A) = 0.3 and P(B) = 0.5, then P(A ∩ B) = 0.30 0.15 0.00 0.20
0.00
In a binomial experiment the probability of success is 0.06. What is the probability of two successes in seven trials? 0.0036 0.06 0.0554 0.28
0.0554
A population of size 1,000 has a proportion of 0.5. Therefore, the proportion and the standard deviation of the sample proportion for samples of size 100 are 500 and 0.047 500 and 0.050 0.5 and 0.047 0.5 and 0.050
0.5 and 0.047
The assembly time for a product is uniformly distributed between 6 to 10 minutes. The probability of assembling the product between 7 to 9 minutes is zero 0.50 0.20 1
0.50
If P(A)=0.38, P(B)=0.83 and P(A intersect B)=0.57; then P(A u B)= 1.21 0.64 0.78 1.78
0.64
The probability that Pete will catch fish on a particular day when he goes fishing is 0.8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. The expected number of days Pete will catch fish is .6 .8 2.4 3
2.4
The starting salaries of individuals with an MBA degree are normally distributed with a mean of $40,000 and a standard deviation of $5,000. Refer to Exhibit 6-4. What percentage of MBA's will have starting salaries of $34,000 to $46,000? 38.49% 38.59% 50% 76.98%
76.98%
The assembly time for a product is uniformly distributed between 6 to 10 minutes. The expected assembly time (in minutes) is 16 2 8 4
8
Which of the following sampling methods does not lead to probability samples? stratified sampling cluster sampling systematic sampling convenience sampling
convenience sampling
For a uniform probability density function, the height of the function can not be larger than one is the same for each value of x is different for various values of x decreases as x increases
is the same for each value of x
All of the following are true about the standard error of the mean except it is larger than the standard deviation of the population it decreases as the sample size increases its value is influenced by the standard deviation of the population it measures the variability in sample mean
it is larger than the standard deviation of the population
Which of the following is an example of a nonprobability sampling technique? simple random sampling stratified random sampling cluster sampling judgment sampling
judgment sampling
A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces. Refer to Exhibit 7-4. In this problem the 0.22 is a parameter a statistic the standard error of the mean the average content of colognes in the long run
a parameter
Cluster sampling is a nonprobability sampling method the same as convenience sampling a probability sampling method None of the alternative answers is correct.
a probability sampling method
A graphical method of representing the sample points of a multiple-step experiment is a frequency polygon a histogram an ogive a tree diagram
a tree diagram
If P(A) = 0.5 and P(B) = 0.5, then P(A ∩ B) is 0.00 0.25 1.00 cannot be determined from the information given
cannot be determined from the information given
f P(A) = 0.5 and P(B) = 0.5, then P(A ∩ B) is 0.00 0.25 1.00 cannot be determined from the information given
cannot be determined from the information given
In an experiment, events A and B are mutually exclusive. If P(A) = 0.6, then the probability of B cannot be larger than 0.4 can be any value greater than 0.6 can be any value between 0 to 1 cannot be determined with the information given
cannot be larger than 0.4
A theorem that allows us to use the normal probability distribution to approximate the sampling distribution of sample means and sample proportions whenever the sample size is large is known as the approximation theorem normal probability theorem central limit theorem central normality theorem
central limit theorem
A method of assigning probabilities that assumes the experimental outcomes are equally likely is referred to as the objective method classical method subjective method experimental method
classical method
A finite population correction factor is needed in computing the standard deviation of the sampling distribution of sample means whenever the population is infinite whenever the sample size is more than 5% of the population size whenever the sample size is less than 5% of the population size The correction factor is not necessary if the population has a normal distribution
whenever the sample size is more than 5% of the population size
If two events are mutually exclusive, then the probability of their intersection will be equal to zero can have any value larger than zero must be larger than zero, but less than one will be one
will be equal to zero
On a December day, the probability of snow is .30. The probability of a "cold" day is .50. The probability of snow and a "cold" day is .15. Are snow and "cold" weather independent events? only if given that it snowed no yes only when they are also mutually exclusive
yes
The probability distribution for the daily sales at Michael's Co. is given below. Daily Sales ($1,000s) Probability 40 0.1 50 0.4 60 0.3 70 0.2 Refer to Exhibit 5-2. The expected daily sales are $55,000 $56,000 $50,000 $70,000
$56,000
Z is a standard normal random variable. What is the value of z if the area to the right of z is 0.9803? -2.06 0.4803 0.0997 3.06
-2.06
The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in ten minutes is 5.3. Refer to Exhibit 5-11. The probability that there are 8 occurrences in ten minutes is .0241 .0771 .1126 .9107
.0771
Exhibit 5-10 The probability that Pete will catch fish on a particular day when he goes fishing is 0.8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. The probability that Pete will catch fish on exactly one day is .008 .096 .104 .8
.096
The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in ten minutes is 5.3. Refer to Exhibit 5-11. The probability that there are less than 3 occurrences is .0659 .0948 .1016 .1239
.1016
The probability that Pete will catch fish on a particular day when he goes fishing is 0.8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. The probability that Pete will catch fish on one day or less is .008 .096 .104 .8
.104
A population consists of 500 elements. We want to draw a simple random sample of 50 elements from this population. On the first selection, the probability of an element being selected is 0.100 0.010 0.001 0.002
0.002
X is a normally distributed random variable with a mean of 5 and a variance of 4. The probability that x is greater than 10.52 is 0.0029 0.0838 0.4971 0.9971
0.0029
A production process produces 2% defective parts. A sample of five parts from the production process is selected. What is the probability that the sample contains exactly two defective parts? 0.0004 0.0038 0.10 0.02
0.0038
X is a normally distributed random variable with a mean of 22 and a standard deviation of 5. The probability that x is less than 9.7 is 0.000 0.4931 0.0069 0.9931
0.0069
Four percent of the customers of a mortgage company default on their payments. A sample of five customers is selected. What is the probability that exactly two customers in the sample will default on their payments? 0.2592 0.0142 0.9588 0.7408
0.0142
A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces. Refer to Exhibit 7-4. The standard error of the mean equals 0.3636 0.0331 0.0200 4.000
0.0200
Random samples of size 525 are taken from a process (an infinite population) whose population proportion is 0.3. The standard deviation of the sample proportions (i.e., the standard error of the proportion) is 0.0004 0.2100 0.3000 0.0200
0.0200
A random sample of 150 people was taken from a very large population. Ninety of the people in the sample were females. The standard error of the proportion of females is 0.0016 0.2400 0.1600 0.0400
0.0400
The student body of a large university consists of 60% female students. A random sample of 8 students is selected. Refer to Exhibit 5-8. What is the probability that among the students in the sample exactly two are female? 0.0896 0.2936 0.0413 0.0007
0.0413
The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 6-5. What is the probability that a randomly selected item will weigh between 11 and 12 ounces? 0.4772 0.4332 0.9104 0.0440
0.0440
The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. Refer to Exhibit 6-3. The probability of a player weighing more than 241.25 pounds is 0.4505 0.0495 0.9505 0.9010
0.0495
If A and B are independent events with P(A)=0.05 and P(B)=0.65 then P(A|B)= 0.05 0.0325 0.65 0.8
0.05
A sample of 400 observations will be taken from a process (an infinite population). The population proportion equals 0.8. The probability that the sample proportion will be greater than 0.83 is 0.4332 0.9332 0.0668 0.5668
0.0668
The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. Refer to Exhibit 6-6. What is the probability that a randomly selected tire will have a life of at least 47,500 miles? 0.4332 0.9332 0.0668 None of the alternative answers is correct.
0.0668
The starting salaries of individuals with an MBA degree are normally distributed with a mean of $40,000 and a standard deviation of $5,000. Refer to Exhibit 6-4. What is the probability that a randomly selected individual with an MBA degree will get a starting salary of at least $47,500? 0.4332 0.9332 0.0668 0.5000
0.0668
Forty percent of all registered voters in a national election are female. A random sample of 5 voters is selected. Refer to Exhibit 5-9. The probability that there are no females in the sample is 0.0778 0.7780 0.5000 0.3456
0.0778
Z is a standard normal random variable. The P(1.20 £ z £ 1.85) equals 0.4678 0.3849 0.8527 0.0829
0.0829
An experiment consists of four outcomes with P(E1) = 0.2, P(E2) = 0.3, and P(E3) = 0.4. The probability of outcome E4 is 0.500 0.024 0.100 0.900
0.100
Consider the continuous random variable x, which has a uniform distribution over the interval from 20 to 28. Refer to Exhibit 6-1. The probability density function has what value in the interval between 20 and 28? 0 0.050 0.125 1.000
0.125
If a coin is tossed three times, the likelihood of obtaining three heads in a row is zero 0.500 0.875 0.125
0.125
The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 6-5. What is the probability that a randomly selected item will weigh more than 10 ounces? 0.3413 0.8413 0.1587 0.5000
0.1587
Random samples of size 100 are taken from a process (an infinite population) whose population proportion is 0.2. The mean and standard deviation of the distribution of sample proportions are 0.2 and .04 0.2 and 0.2 20 and .04 None of the alternative answers is correct.
0.2 and .04
If P(A) = 0.62, P(B) = 0.47, and P(A u B)= 0.88; Then P(A intersect B) = 0.2914 1.9700 0.6700 0.2100
0.2100
Four hundred registered voters were randomly selected asked whether gun laws should be changed. Three hundred said "yes," and one hundred said "no." Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond "no" is 75 0.25 0.75 0.50
0.25
Of the last 100 customers entering a computer shop, 25 have purchased a computer. If the classical method for computing probability is used, the probability that the next customer will purchase a computer is 0.25 0.50 1.00 0.75
0.25
The assembly time for a product is uniformly distributed between 6 to 10 minutes. The probability density function has what value in the interval between 6 and 10? 0.25 4.00 5.00 zero
0.25
The probability density function for a uniform distribution ranging between 2 and 6 is 4 undefined any positive value 0.25
0.25
Consider the continuous random variable x, which has a uniform distribution over the interval from 20 to 28. Refer to Exhibit 6-1. The probability that x will take on a value of at least 26 is 0.000 0.125 0.250 1.000
0.250
Forty percent of all registered voters in a national election are female. A random sample of 5 voters is selected. Refer to Exhibit 5-9. The probability that the sample contains 2 female voters is 0.0778 0.7780 0.5000 0.3456
0.3456
The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 6-5. What percentage of items will weigh between 6.4 and 8.9 ounces? 0.1145 0.2881 0.1736 0.4617
0.4617
For a standard normal distribution, the probability of z ≤ 0 is zero -0.5 0.5 one
0.5
If a penny is tossed four times and comes up heads all four times, the probability of heads on the fifth trial is zero 1/32 0.5 larger than the probability of tails
0.5
Consider the continuous random variable x, which has a uniform distribution over the interval from 20 to 28. Refer to Exhibit 6-1. The probability that x will take on a value between 21 and 25 is 0.125 0.250 0.500 1.000
0.500
If P(A) = 0.85, P(A U B) = 0.72, and P(A ∩ B) = 0.66, then P(B) = 0.15 0.53 0.28 0.15
0.53
If P(A)= 0.85, P(A u B)= 0.72, and (A intersect B)=0.66; Then P(B) = 0.15 0.53 0.28 0.15
0.53
The probability distribution for the number of goals the Lions soccer team makes per game is given below. Number of Goals Probability 0 0.05 1 0.15 2 0.35 3 0.30 4 0.15 Refer to Exhibit 5-3. What is the probability that in a given game the Lions will score less than 3 goals? 0.85 0.55 0.45 0.80
0.55
The travel time for a college student traveling between her home and her college is uniformly distributed between 40 and 90 minutes. Refer to Exhibit 6-2. The probability that her trip will take longer than 60 minutes is 1.00 0.40 0.02 0.600
0.600
The following represents the probability distribution for the daily demand of microcomputers at a local store. Demand Probability 0 0.1 1 0.2 2 0.3 3 0.2 4 0.2 Refer to Exhibit 5-1. The probability of having a demand for at least two microcomputers is 0.7 0.3 0.4 1.0
0.7
Four hundred registered voters were randomly selected asked whether gun laws should be changed. Three hundred said "yes," and one hundred said "no." Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond "yes" is 300 approximately 300 0.75 0.25
0.75
The probability of at least one head in two flips of a coin is 0.33 0.50 0.75 1.00
0.75
The travel time for a college student traveling between her home and her college is uniformly distributed between 40 and 90 minutes. Refer to Exhibit 6-2. The probability that she will finish her trip in 80 minutes or less is 0.02 0.8 0.2 1.00
0.8
The probability distribution for the daily sales at Michael's Co. is given below. Daily Sales ($1,000s) Probability 40 0.1 50 0.4 60 0.3 70 0.2 Refer to Exhibit 5-2. The probability of having sales of at least $50,000 is 0.5 0.10 0.30 0.90
0.90
The probability distribution for the number of goals the Lions soccer team makes per game is given below. Number of Goals Probability 0 0.05 1 0.15 2 0.35 3 0.30 4 0.15 Refer to Exhibit 5-3. What is the probability that in a given game the Lions will score at least 1 goal? 0.20 0.55 1.0 0.95
0.95
The starting salaries of individuals with an MBA degree are normally distributed with a mean of $40,000 and a standard deviation of $5,000. Refer to Exhibit 6-4. What is the probability that a randomly selected individual with an MBA degree will get a starting salary of at least $30,000? 0.4772 0.9772 0.0228 0.5000
0.9772
The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. Refer to Exhibit 6-3. The probability of a player weighing less than 250 pounds is 0.4772 0.9772 0.0528 0.5000
0.9772
A lottery is conducted using three urns. Each urn contains chips numbered from 0 to 9. One chip is selected at random from each urn. The total number of sample points in the sample space is 30 100 729 1,000
1,000
Z is a standard normal random variable. What is the value of z if the area between -z and z is 0.754? 0.377 0.123 2.16 1.16
1.16
A sample of 2,500 people was asked how many cups of coffee they drink in the morning. You are given the following sample information. Cups of Coffee Frequency 0 700 1 900 2 600 3 300 2,500 Refer to Exhibit 5-7. The expected number of cups of coffee is 1 1.2 1.5 1.7
1.2
The following information was collected from a simple random sample of a population. 16 19 18 17 20 18 Refer to Exhibit 7-3. The point estimate of the population standard deviation is 2.000 1.291 1.414 1.667
1.414
AMR is a computer-consulting firm. The number of new clients that they have obtained each month has ranged from 0 to 6. The number of new clients has the probability distribution that is shown below. Number of New Clients Probability 0 0.05 1 0.10 2 0.15 3 0.35 4 0.20 5 0.10 6 0.05 Refer to Exhibit 5-5. The standard deviation is 1.431 2.047 3.05 21
1.431
From a population of 500 elements, a sample of 225 elements is selected. It is known that the variance of the population is 900. The standard error of the mean is approximately 1.1022 2 30 1.4847
1.4847
Given that z is a standard normal random variable, what is the value of z if the area to the left of z is 0.9382? 1.8 1.54 2.1 1.77
1.54
The following data was collected from a simple random sample from a process (an infinite population). 13 15 14 16 12 Refer to Exhibit 7-1. The point estimate of the population standard deviation is 2.500 1.581 2.000 1.414
1.581
Refer to Exhibit 5-4. The expected number of machine breakdowns per month is 2 1.70 one None of the alternative answers is correct.
1.70
Of five letters (A, B, C, D, and E), two letters are to be selected at random. How many possible selections are there? 20 7 5 10
10 (Combination)
Assume that you have a binomial experiment with p = 0.4 and a sample size of 50. The variance of this distribution is 20 12 3.46 Not enough information is given to answer this question.
12
How many different samples of size 3 (without replacement) can be taken from a finite population of size 10? 30 1,000 720 120
120
A simple random sample of 64 observations was taken from a large population. The population standard deviation is 120. The sample mean was determined to be 320. The standard error of the mean is 1.875 40 5 15
15
There are 6 children in a family. The number of children defines a population. The number of simple random samples of size 2 (without replacement) which are possible equals 12 15 3 16
15
The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. Refer to Exhibit 6-3. What is the minimum weight of the middle 95% of the players? 196 151 249 None of the alternative answers is correct.
151
An experiment consists of tossing 4 coins successively. The number of sample points in this experiment is 16 8 4 2
16
A simple random sample of 5 observations from a population containing 400 elements was taken, and the following values were obtained. 12 18 19 20 21 A point estimate of the population mean is 5 18 19 20
18
The following information was collected from a simple random sample of a population. 16 19 18 17 20 18 Refer to Exhibit 7-3. The point estimate of the mean of the population is 18.0 19.6 108 sixteen, since 16 is the smallest value in the sample
18.0
Random samples of size 49 are taken from a population that has 200 elements, a mean of 180, and a variance of 196. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are 180 and 24.39 180 and 28 180 and 1.74 180 and 2
180 and 1.74
AMR is a computer-consulting firm. The number of new clients that they have obtained each month has ranged from 0 to 6. The number of new clients has the probability distribution that is shown below. Number of New Clients Probability 0 0.05 1 0.10 2 0.15 3 0.35 4 0.20 5 0.10 6 0.05 Refer to Exhibit 5-5. The variance is 1.431 2.0475 3.05 21
2.0475
The following represents the probability distribution for the daily demand of microcomputers at a local store. Demand Probability 0 0.1 1 0.2 2 0.3 3 0.2 4 0.2 Refer to Exhibit 5-1. The expected daily demand is 1.0 2.2 2 4
2.2
The probability distribution for the number of goals the Lions soccer team makes per game is given below. Number of Goals Probability 0 0.05 1 0.15 2 0.35 3 0.30 4 0.15 Refer to Exhibit 5-3. The expected number of goals per game is 0 1 2 2.35
2.35
Random samples of size 36 are taken from a process (an infinite population) whose mean and standard deviation are 20 and 15, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample mean are 36 and 15 20 and 15 20 and 0.417 20 and 2.5
20 and 2.5
Random samples of size 81 are taken from a process (an infinite population) whose mean and standard deviation are 200 and 18, respectively. The distribution of the population is unknown. The mean and the standard error of the distribution of sample means are 200 and 18 81 and 18 9 and 2 200 and 2
200 and 2
Consider the continuous random variable x, which has a uniform distribution over the interval from 20 to 28. Refer to Exhibit 6-1. The mean of x is 0.000 0.125 23 24
24
Probability Distribution x f(x) 10 .2 20 .3 30 .4 40 .1 Refer to Exhibit 5-6. The expected value of x equals 24 25 30 100
24
AMR is a computer-consulting firm. The number of new clients that they have obtained each month has ranged from 0 to 6. The number of new clients has the probability distribution that is shown below. Number of New Clients Probability 0 0.05 1 0.10 2 0.15 3 0.35 4 0.20 5 0.10 6 0.05 Refer to Exhibit 5-5. The expected number of new clients per month is 6 0 3.05 21
3.05
The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 6-5. What percentage of items will weigh at least 11.7 ounces? 46.78% 96.78% 3.22% 53.22%
3.22%
Random samples of size 17 are taken from a population that has 200 elements, a mean of 36, and a standard deviation of 8. Refer to Exhibit 7-5. The mean and the standard deviation of the sampling distribution of the sample means are 8.7 and 1.94 36 and 1.94 36 and 1.86 36 and 8
36 and 1.86
A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces. Refer to Exhibit 7-4. The point estimate of the mean content of all bottles is 0.22 4 121 0.02
4
Twenty percent of the students in a class of 100 are planning to go to graduate school. The standard deviation of this binomial distribution is 20 16 4 2
4
The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in ten minutes is 5.3. Refer to Exhibit 5-11. The expected value of the random variable x is 2 5.3 10 2.30
5.3
Consider the continuous random variable x, which has a uniform distribution over the interval from 20 to 28. Refer to Exhibit 6-1. The variance of x is approximately 2.309 5.333 32 0.667
5.333
Assume that you have a binomial experiment with p = 0.5 and a sample size of 100. The expected value of this distribution is 0.50 0.30 50 Not enough information is given to answer this question.
50
The "Top Three" at a racetrack consists of picking the correct order of the first three horses in a race. If there are 10 horses in a particular race, how many "Top Three" outcomes are there? 302,400 720 1,814,400 10
720
The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. Refer to Exhibit 6-6. What percentage of tires will have a life of 34,000 to 46,000 miles? 38.49% 76.98% 50% None of the alternative answers is correct.
76.98%
Three applications for admission to a local university are checked to determine whether each applicant is male or female. The number of sample points in this experiment is 2 4 6 8
8
Probability Distribution x f(x) 10 .2 20 .3 30 .4 40 .1 Refer to Exhibit 5-6. The variance of x equals 9.165 84 85 93.33
84
For the Excel worksheet above, which of the following formulas would correctly calculate the posterior probability for cell E3? =SUM(B3:D3) =D3/$D$5 =D5/$D$3 B3/C3+D3
=D3/$D$5
If P(A intersection B) = 0, P(A) + P(B) = 1 either P(A) = 0 or P(B) = 0 A and B are mutually exclusive events A and B are independent events
A and B are mutually exclusive events
A local bottling company has determined the number of machine breakdowns per month and their respective probabilities as shown below. Number of Breakdowns Probability 0 0.12 1 0.38 2 0.25 3 0.18 4 0.07 Refer to Exhibit 5-4. The probability of at least 3 breakdowns in a month is 0.5 0.10 0.30 None of the alternative answers is correct.
None of the alternative answers is correct.
A local bottling company has determined the number of machine breakdowns per month and their respective probabilities as shown below. Number of Breakdowns Probability 0 0.12 1 0.38 2 0.25 3 0.18 4 0.07 Refer to Exhibit 5-4. The probability of no breakdowns in a month is 0.88 0.00 0.50 None of the alternative answers is correct.
None of the alternative answers is correct.
If the mean of a normal distribution is negative, the standard deviation must also be negative the variance must also be negative a mistake has been made in the computations, because the mean of a normal distribution can not be negative None of the alternative answers is correct.
None of the alternative answers is correct.
Random samples of size 17 are taken from a population that has 200 elements, a mean of 36, and a standard deviation of 8. Refer to Exhibit 7-5. Which of the following best describes the form of the sampling distribution of the sample mean for this situation? Approximately normal because the sample size is small relative to the population size. Approximately normal because of the central limit theorem. exactly normal None of the alternative answers is correct.
None of the alternative answers is correct.
The assembly time for a product is uniformly distributed between 6 to 10 minutes. The standard deviation of assembly time (in minutes) is approximately 0.3333 0.1334 16 None of the alternative answers is correct.
None of the alternative answers is correct.
The mean of a standard normal probability distribution is always equal to 1 can be any value as long as it is positive can be any value None of the alternative answers is correct.
None of the alternative answers is correct.
The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. Refer to Exhibit 6-3. What percent of players weigh between 180 and 220 pounds? 34.13% 68.26% 0.3413% None of the alternative answers is correct.
None of the alternative answers is correct.
The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 6-5. What is the probability that a randomly selected item weighs exactly 8 ounces? 0.5 1.0 0.3413 None of the alternative answers is correct.
None of the alternative answers is correct.
Z is a standard normal random variable. The P(1.41 < z < 2.85) equals 0.4772 0.3413 0.8285 None of the alternative answers is correct.
None of the alternative answers is correct.
The expected value of a random variable is the value of the random variable that should be observed on the next repeat of the experiment value of the random variable that occurs most frequently square root of the variance None of the answers is correct.
None of the answers is correct.
Which of the following is(are) required condition(s) for a discrete probability function? ∑f(x) = 0 f(x) = 1 for all values of x f(x) < 0 None of the answers is correct.
None of the answers is correct.
A graphical device used for enumerating sample points in a multiple-step experiment is a bar chart pie chart histogram None of the other answers is correct.
None of the other answers is correct
A method of assigning probabilities based upon judgment is referred to as the relative method probability method classical method None of the other answers is correct.
None of the other answers is correct.
Events A and B are mutually exclusive with P(A) = 0.3 and P(B) = 0.2. The probability of the complement of Event B equals 0.00 0.06 0.7 None of the other answers is correct.
None of the other answers is correct.
If two events are independent, then they must be mutually exclusive the sum of their probabilities must be equal to one the probability of their intersection must be zero None of the other answers is correct.
None of the other answers is correct.
Assume your favorite football team has 2 games left to finish the season. The outcome of each game can be win, lose or tie. The number of possible outcomes is 2 4 6 None of the other answers is correct.
None of the other answers is correct. (9)
The probability of the union of two events with nonzero probabilities cannot be less than one cannot be one cannot be less than one and cannot be one None of the other answers is correct.
None of the others answers is correct
Events A and B are mutually exclusive. Which of the following statements is also true? A and B are also independent P(A u B)=P(A)P(B) P(A u B)=P(A) + P(B) P(A intersect B)=P(A) + P(B)
P(A intersect B)=P(A) + P(B)
If A and B are mutually exclusive, then P(A) + P(B) = 0 P(A) + P(B) = 1 P(A union B) = 0 P(A intersect B) = 1
P(A union B) = 0
The complement of P(A | B) is P(AC | B) P(A | BC) P(B | A) P(A intersect B)
P(AC | B)
The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the probability of an occurrence is the same in any two time periods of an equal length. It is known that the mean number of occurrences in ten minutes is 5.3. Refer to Exhibit 5-11. The random variable x satisfies which of the following probability distributions? normal Poisson binomial Not enough information is given to answer this question.
Poisson
A(n) __________ is a graphical representation in which the sample space is represented by a rectangle and events are represented as circles. frequency polygon histogram Venn diagram tree diagram
Venn diagram
Two events, A and B, are mutually exclusive and each has a nonzero probability. If event A is known to occur, the probability of the occurrence of event B is one any positive value zero any value between 0 to 1
Zero
The uniform probability distribution is used with a continuous random variable a discrete random variable a normally distributed random variable any random variable
a continuous random variable
In statistical experiments, each time the experiment is repeated the same outcome must occur the same outcome can not occur again a different outcome may occur None of the other answers is correct.
a different outcome may occur
The binomial probability distribution is used with a continuous random variable a discrete random variable any distribution, as long as it is not normal All of these answers are correct.
a discrete random variable
The weight of an object, measured to the nearest gram, is an example of a continuous random variable a discrete random variable either a continuous or a discrete random variable, depending on the weight of the object either a continuous or a discrete random variable depending on the units of measurement
a discrete random variable
A standard normal distribution is a normal distribution with a mean of 1 and a standard deviation of 0 a mean of 0 and a standard deviation of 1 any mean and a standard deviation of 1 any mean and any standard deviation
a mean of 0 and a standard deviation of 1
Any process that generates well-defined outcomes is an event an experiment a sample point None of the other answers is correct.
an experiment
If arrivals follow a Poisson probability distribution, the time between successive arrivals must follow a Poisson probability distribution a normal probability distribution a uniform probability distribution an exponential probability distribution
an exponential probability distribution
For a population with an unknown distribution, the form of the sampling distribution of the sample mean is approximately normal for all sample sizes exactly normal for large sample sizes exactly normal for all sample sizes approximately normal for large sample sizes
approximately normal for large sample sizes
A sample of 25 observations is taken from a process (an infinite population). The sampling distribution of mc067-1.jpg is not normal since n < 30 approximately normal because mc067-2.jpg is always normally distributed approximately normal if np ≥ 5 and n(1-p) ≥ 5 approximately normal if np > 30 and n(1-p) > 30
approximately normal if np ≥ 5 and n(1-p) ≥ 5
A probability distribution showing the probability of x successes in n trials, where the probability of success does not change from trial to trial, is termed a uniform probability distribution binomial probability distribution hypergeometric probability distribution normal probability distribution
binomial probability distribution
If you are conducting an experiment where the probability of a success is .02 and you are interested in the probability of 4 successes in 15 trials, the correct probability function to use is the standard normal probability density function normal probability density function Poisson probability function binomial probability function
binomial probability function
The following data was collected from a simple random sample from a process (an infinite population). 13 15 14 16 12 Refer to Exhibit 7-1. The mean of the population is 14 is 15 is 15.1581 could be any value
could be any value
A simple random sample from a process (an infinite population) is a sample selected such that each element selected comes from the same population each element is selected independently each element selected comes from the same population and each element is selected independently the probability of being selected changes
each element selected comes from the same population and each element is selected independently
A measure of the average value of a random variable is called a(n) variance standard deviation expected value None of the answers is correct.
expected value
The probability distribution that can be described by just one parameter is the uniform normal exponential binomial
exponential
The expected value of mc001-1.jpgequals the mean of the population from which the sample is drawn only if the sample size is 30 or greater only if the sample size is 50 or greater only if the sample size is 100 or greater for any sample size
for any sample size
To compute the probability that in a random sample of n elements, selected without replacement, we will obtain x successes, we would use the binomial probability distribution Poisson probability distribution hypergeometric probability distribution exponential probability distribution
hypergeometric probability distribution
If P(A)=0.50, P(B)=0.60, and P(A intersect B)=0.30; then events A and B are mutually exclusive events not independent events independent events Not enough information is given to answer this question.
independent events
It is impossible to construct a frame for a finite population infinite population target population sampled population
infinite population
The following data was collected from a simple random sample from a process (an infinite population). 13 15 14 16 12 Refer to Exhibit 7-1. The point estimate of the population mean is 5 is 14 is 4 cannot be determined because the population is infinite
is 14
From a population of 200 elements, the standard deviation is known to be 14. A sample of 49 elements is selected. It is determined that the sample mean is 56. The standard error of the mean is 3 2 greater than 2 less than 2
less than 2
The expected value of the random variable mc037-1.jpg is s the standard error the sample size m
m
In a Poisson probability problem, the rate of defects is one every two hours. To find the probability of three defects in four hours, m = 1, x = 4 m = 2, x = 3 m = 3, x = 4 m = 4, x = 3
m = 1, x = 4
The probability of the occurrence of event A in an experiment is 1/3. If the experiment is performed 2 times and event A did not occur, then on the third trial event A must occur may occur could not occur has a 2/3 probability of occurring
may occur
The probability of an intersection of two events is computed using the addition law subtraction law multiplication law division law
multiplication law
The probability of the intersection of two mutually exclusive events can be any value between 0 to 1 must always be equal to 1 must always be equal to 0 can be any positive value
must always be equal to 0
Given that event E has a probability of 0.25, the probability of the complement of event E cannot be determined with the above information can have any value between zero and one must be 0.75 is 0.25
must be 0.75
Events that have no sample points in common are independent events posterior events mutually exclusive events complements
mutually exclusive events
A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size N has the same probability of being selected n has a probability of 0.5 of being selected n has a probability of 0.1 of being selected n has the same probability of being selected
n has the same probability of being selected
A binomial probability distribution with p = .3 is negatively skewed symmetrical positively skewed bimodal
negatively skewed
A sample of 92 observations is taken from a process (an infinite population). The sampling distribution of mc056-1.jpg is approximately normal because mc056-2.jpg is always approximately normally distributed the sample size is small in comparison to the population size of the central limit theorem None of the alternative answers is correct.
of the central limit theorem
The binomial probability distribution is most symmetric when n is 30 or greater n equals p p approaches 1 p equals 0.5
p equals 0.5
A simple random sample of 28 observations was taken from a large population. The sample mean equaled 50. Fifty is a population parameter point estimator sample parameter point estimate
point estimate
A sample statistic, such as mc024-1.jpg, that estimates the value of the corresponding population parameter is known as a point estimator parameter population parameter Both a parameter and a population parameter are correct.
point estimator
The purpose of statistical inference is to provide information about the sample based upon information contained in the population population based upon information contained in the sample population based upon information contained in the population mean of the sample based upon the mean of the population
population based upon information contained in the sample
Revised probabilities of events based on additional information are joint probabilities posterior probabilities marginal probabilities complementary probabilities
posterior probabilities
A numerical description of the outcome of an experiment is called a descriptive statistic probability function variance random variable
random variable
Doubling the size of the sample will reduce the standard error of the mean to one-half its current value reduce the standard error of the mean to approximately 70% of its current value have no effect on the standard error of the mean double the standard error of the mean
reduce the standard error of the mean to approximately 70% of its current value
When the results of experimentation or historical data are used to assign probability values, the method used to assign probabilities is referred to as the relative frequency method subjective method classical method posterior method
relative frequency method
The probability distribution of all possible values of the sample proportion p-bar is the probability density function of p-bar sampling distribution of x-bar same as p-bar , since it considers all possible values of the sample proportion sampling distribution of p-bar
sampling distribution of p-bar
The standard deviation of mc004-1.jpg is referred to as the standard x standard error of the mean sample standard mean sample mean deviation
standard error of the mean
The basis for using a normal probability distribution to approximate the sampling distribution of mc002-1.jpg is Chebyshev's theorem the empirical rule the central limit theorem Bayes' theorem
the central limit theorem
A weighted average of the value of a random variable, where the probability function provides weights is known as a probability function a random variable the expected value None of the answers is correct
the expected value
For a continuous random variable x, the probability density function f(x) represents the probability at a given value of x the area under the curve at x Both the probability at a given value of x and the area under the curve at x are correct answers. the height of the function at x
the height of the function at x
The probability that Pete will catch fish on a particular day when he goes fishing is 0.8. Pete is going fishing 3 days next week. Refer to Exhibit 5-10. What is the random variable in this experiment? the 0.8 probability of catching fish the 3 days the number of days out of 3 that Pete catches fish the number of fish in the body of water
the number of days out of 3 that Pete catches fish
The student body of a large university consists of 60% female students. A random sample of 8 students is selected. Refer to Exhibit 5-8. What is the random variable in this experiment? the 60% of female students the random sample of 8 students the number of female students out of 8 the student body size
the number of female students out of 8
Bayes' theorem is used to compute the prior probabilities the union of events both the prior probabilities and the union of events the posterior probabilities
the posterior probabilities
The starting salaries of individuals with an MBA degree are normally distributed with a mean of $40,000 and a standard deviation of $5,000. Refer to Exhibit 6-4. What is the random variable in this experiment? the starting salaries the normal distribution $40,000 $5,000
the starting salaries
The probability of an event is the sum of the probabilities of the sample points in the event the product of the probabilities of the sample points in the event the minimum of the probabilities of the sample points in the event the maximum of the probabilities of the sample points in the event
the sum of the probabilities of the sample points in the event
The travel time for a college student traveling between her home and her college is uniformly distributed between 40 and 90 minutes. Refer to Exhibit 6-2. What is the random variable in this experiment? the uniform distribution 40 minutes 90 minutes the travel time
the travel time
The addition law is potentially helpful when we are interested in computing the probability of independent events the intersection of two events the union of two events conditional events
the union of two events
The weight of football players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. Refer to Exhibit 6-3. What is the random variable in this experiment? the weight of football players 200 pounds 25 pounds the normal distribution
the weight of football players
The weight of items produced by a machine is normally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. Refer to Exhibit 6-5. What is the random variable in this experiment? the weight of items produced by a machine 8 ounces 2 ounces the normal distribution
the weight of items produced by a machine
Two events are mutually exclusive if the probability of their intersection is 1 they have no sample points in common the probability of their intersection is 0.5 the probability of their intersection is 1 and they have no sample points in common
they have no sample points in common
The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. Refer to Exhibit 6-6. What is the probability that a randomly selected tire will have a life of exactly 47,500 miles? 0.4332 0.9332 0.0668 zero
zero
The travel time for a college student traveling between her home and her college is uniformly distributed between 40 and 90 minutes. Refer to Exhibit 6-2. The probability that her trip will take exactly 50 minutes is zero 0.02 0.06 0.20
zero
The range of probability is any value larger than zero any value between minus infinity to plus infinity zero to one any value between -1 to 1
zero to one
