Q&A Hero

Q: For a standard normal distribution, a negative value of zindicates a. a mistake has been made in computations, because zis always positive b. the area corresponding to the zis negative c. the zis to the left of the mean d. the zis to the right of the mean

Q: In a standard normal distribution, the range of values of zis from a. minus infinity to infinity b. -1 to 1 c. 0 to 1 d. -3.09 to 3.09

Q: A standard normal distribution is a normal distribution with a. a mean of 1 and a standard deviation of 0 b. a mean of 0 and a standard deviation of 1 c. any mean and a standard deviation of 1 d. any mean and any standard deviation

Q: Larger values of the standard deviation result in a normal curve that is a. shifted to the right b. shifted to the left c. narrower and more peaked d. wider and flatter

Q: If the mean of a normal distribution is negative, a. the standard deviation must also be negative b. the variance must also be negative c. a mistake has been made in the computations, because the mean of a normal distribution can not be negative d. None of the alternative answers is correct.

Q: The highest point of a normal curve occurs at a. one standard deviation to the right of the mean b. two standard deviations to the right of the mean c. approximately three standard deviations to the right of the mean d. the mean

Q: Which of the following is nota characteristic of the normal probability distribution? a. The graph of the curve is the shape of a rectangle b. The total area under the curve is always equal to 1. c. 99.72% of the time the random variable assumes a value within plus or minus three standard deviations of its mean d. The mean is equal to the median, which is also equal to the mode.

Q: Which of the following is nota characteristic of the normal probability distribution? a. The mean, median, and the mode are equal b. The mean of the distribution can be negative, zero, or positive c. The distribution is symmetrical d. The standard deviation must be 1

Q: A normal probability distribution a. is a continuous probability distribution b. is a discrete probability distribution c. can be either continuous or discrete d. always has a standard deviation of 1

Q: Refer to Exhibit 6-2. The probability that her trip will take exactly 50 minutes is a. zero b. 0.02 c. 0.06 d. 0.20

Q: Refer to Exhibit 6-2. The probability that her trip will take longer than 60 minutes is a. 1.00 b. 0.40 c. 0.02 d. 0.600

Q: Refer to Exhibit 6-2. The probability that she will finish her trip in 80 minutes or less is a. 0.02 b. 0.8 c. 0.2 d. 1.00

Q: Exhibit 6-2The travel time for a college student traveling between her home and her college is uniformly distributed between 40 and 90 minutes.Refer to Exhibit 6-1. What is the random variable in this experiment?a. the uniform distributionb. 40 minutesc. 90 minutesd. the travel time

Q: Refer to Exhibit 6-1. The variance of xis approximatelya. 2.309b. 5.333c. 32d. 0.667

Q: Refer to Exhibit 6-1. The mean of xis a. 0.000 b. 0.125 c. 23 d. 24

Q: Refer to Exhibit 6-1. The probability that xwill take on a value of at least 26 is a. 0.000 b. 0.125 c. 0.250 d. 1.000

Q: Refer to Exhibit 6-1. The probability that xwill take on a value between 21 and 25 is a. 0.125 b. 0.250 c. 0.500 d. 1.000

Q: Exhibit 6-1Consider the continuous random variable x, which has a uniform distribution over the interval from 20 to 28.Refer to Exhibit 6-3. The probability density function has what value in the interval between 20 and 28?a. 0b. 0.050c. 0.125d. 1.000

Q: The assembly time for a product is uniformly distributed between 6 to 10 minutes. The standard deviation of assembly time (in minutes) is approximatelya. 0.3333b. 0.1334c. 16d. None of the alternative answers is correct.

Q: The assembly time for a product is uniformly distributed between 6 to 10 minutes. The expected assembly time (in minutes) is a. 16 b. 2 c. 8 d. 4

Q: The assembly time for a product is uniformly distributed between 6 to 10 minutes. The probability of assembling the product in 7 minutes or more is a. 0.25 b. 0.75 c. zero d. 1

Q: The assembly time for a product is uniformly distributed between 6 to 10 minutes. The probability of assembling the product in less than 6 minutes is a. zero b. 0.50 c. 0.15 d. 1

Q: 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 a. zero b. 0.50 c. 0.20 d. 1

Q: 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? a. 0.25 b. 4.00 c. 5.00 d. zero

Q: The random variable xis known to be uniformly distributed between 70 and 90. The probability of xhaving a value between 80 and 95 is a. 0.75 b. 0.5 c. 0.05 d. 1

Q: The probability density function for a uniform distribution ranging between 2 and 6 is a. 4 b. undefined c. any positive value d. 0.25

Q: A continuous random variable is uniformly distributed between aand b. The probability density function between aand bis a. zero b. (a- b) c. (b- a) d. 1/(b- a)

Q: For a uniform probability density function, the height of the function a. can not be larger than one b. is the same for each value of x c. is different for various values of x d. decreases as xincreases

Q: A uniform probability distribution is a continuous probability distribution where the probability that the random variable assumes a value in any interval of equal length is a. different for each interval b. the same for each interval c. Either a or b could be correct depending on the magnitude of the standard deviation. d. None of the alternative answers is correct.

Q: The uniform probability distribution is used with a. a continuous random variable b. a discrete random variable c. a normally distributed random variable d. any random variable

Q: For any continuous random variable, the probability that the random variable takes on exactly a specific value is a. 1.00 b. 0.50 c. any value between 0 to 1 d. zero

Q: The function that defines the probability distribution of any continuous random variable is a a. normal function b. uniform function c. Both the normal function and the uniform function are correct. d. probability density function

Q: For a continuous random variable x, the probability density function f(x) represents a. the probability at a given value of x b. the area under the curve at x c. Both the probability at a given value of xand the area under the curve at xare correct answers. d. the height of the function at x

Q: A continuous random variable may assume a. all values in an interval or collection of intervals b. only integer values in an interval or collection of intervals c. only fractional values in an interval or collection of intervals d. all the positive integer values in an interval

Q: The probability distribution that can be described by just one parameter is the a. uniform b. normal c. exponential d. binomial

Q: The mean, median, and mode have the same value for which of the following probability distributions? a. uniform b. normal c. exponential d. Poisson

Q: The form of the continuous uniform probability distribution is a. triangular b. rectangular c. bell-shaped d. a series of vertical lines

Q: There is a lower limit but no upper limit for a random variable that follows the a. uniform probability distribution b. normal probability distribution c. exponential probability distribution d. binomial probability distribution

Q: Whenever the probability is proportional to the length of the interval in which the random variable can assume a value, the random variable is a. uniformly distributed b. normally distributed c. exponentially distributed d. Poisson distributed

Q: If arrivals follow a Poisson probability distribution, the time between successive arrivals must followa. a Poisson probability distributionb. a normal probability distributionc. a uniform probability distributiond. an exponential probability distribution

Q: Assume that you have a binomial experiment with p= 0.5 and a sample size of 100. The expected value of this distribution is a. 0.50 b. 0.30 c. 50 d. Not enough information is given to answer this question.

Q: The standard deviation of a binomial distribution isa. E(x) = pn(1 -n)b. E(x) = np(1 -p)c. E(x) = npd. None of the alternative answers is correct.

Q: The variance for the binomial probability distribution isa. Var(x) = p(1 -p)b. Var(x) = npc. Var(x) = n(1 -p)d. Var(x) = np(1 -p)

Q: The expected value for a binomial probability distribution isa. E(x) = pn(1 -n)b. E(x) = p(1 -p)c. E(x) = npd. E(x) = np(1 -p)

Q: When using Excel's BINOMDIST function, one should choose TRUE for the fourth input if a. a probability is desired b. a cumulative probability is desired c. the expected value is desired d. the correct answer is desired

Q: Excel's BINOMDIST function has how many inputs? a. 2 b. 3 c. 4 d. 5

Q: Excel's BINOMDIST function can be used to compute a. bin width for histograms b. binomial probabilities c. cumulative binomial probabilities d. Both binomial probabilities and cumulative binomial probabilities are correct.

Q: 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? a. 0.0004 b. 0.0038 c. 0.10 d. 0.02

Q: 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? a. 0.2592 b. 0.0142 c. 0.9588 d. 0.7408

Q: In a binomial experiment the probability of success is 0.06. What is the probability of two successes in seven trials? a. 0.0036 b. 0.06 c. 0.0554 d. 0.28

Q: 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 a. standard normal probability density function b. normal probability density function c. Poisson probability function d. binomial probability function

Q: The binomial probability distribution is used witha. a continuous random variableb. a discrete random variablec. any distribution, as long as it is not normald. All of these answers are correct.

Q: A probability distribution showing the probability of xsuccesses in ntrials, where the probability of success does not change from trial to trial, is termed a a. uniform probability distribution b. binomial probability distribution c. hypergeometric probability distribution d. normal probability distribution

Q: Which of the following is nota property of a binomial experiment? a. the experiment consists of a sequence of nidentical trials b. each outcome can be referred to as a success or a failure c. the probabilities of the two outcomes can change from one trial to the next d. the trials are independent

Q: Which of the following is nota characteristic of an experiment where the binomial probability distribution is applicable? a. the experiment has a sequence of nidentical trials b. exactly two outcomes are possible on each trial c. the trials are dependent d. the probabilities of the outcomes do not change from one trial to another

Q: In a binomial experiment, the a. probability of success does not change from trial to trial b. probability of success does change from trial to trial c. probability of success could change from trial to trial, depending on the situation under consideration d. All of these answers are correct.

Q: Which of the following is a characteristic of a binomial experiment? a. at least 2 outcomes are possible b. the probability of success changes from trial to trial c. the trials are independent d. All of these answers are correct.

Q: Refer to Exhibit 5-7. The variance of the number of cups of coffee is a. .96 b. .9798 c. 1 d. 2.4

Q: Exhibit 5-7A 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 CoffeeFrequency07001900260033002,500Refer to Exhibit 5-7. The expected number of cups of coffee isa. 1b. 1.2c. 1.5d. 1.7

Q: Refer to Exhibit 5-6. The variance of xequalsa. 9.165b. 84c. 85d. 93.33

Q: Exhibit 5-6Probability Distributionxf(x)10.220.330.440.1Refer to Exhibit 5-6. The expected value of xequalsa. 24b. 25c. 30d. 100

Q: The number of electrical outages in a city varies from day to day. Assume that the number of electrical outages (x) in the city has the following probability distribution.xf(x)00.8010.1520.0430.01The mean and the standard deviation for the number of electrical outages (respectively) area. 2.6 and 5.77b. 0.26 and 0.577c. 3 and 0.01d. 0 and 0.8

Q: Refer to Exhibit 5-5. The standard deviation is a. 1.431 b. 2.047 c. 3.05 d. 21

Q: Refer to Exhibit 5-5. The variance is a. 1.431 b. 2.0475 c. 3.05 d. 21

Q: Exhibit 5-5AMR 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 ClientsProbability00.0510.1020.1530.3540.2050.1060.05Refer to Exhibit 5-5. The expected number of new clients per month isa. 6b. 0c. 3.05d. 21

Q: Refer to Exhibit 5-4. The probability of no breakdowns in a month isa. 0.88b. 0.00c. 0.50d. None of the alternative answers is correct.

Q: Refer to Exhibit 5-4. The probability of at least 3 breakdowns in a month is a. 0.5 b. 0.10 c. 0.30 d. None of the alternative answers is correct.

Q: Exhibit 5-4A local bottling company has determined the number of machine breakdowns per month and their respective probabilities as shown below.Number of BreakdownsProbability00.1210.3820.2530.1840.07Refer to Exhibit 5-4. The expected number of machine breakdowns per month isa. 2b. 1.70c. oned. None of the alternative answers is correct.

Q: Refer to Exhibit 5-3. What is the probability that in a given game the Lions will score no goals?a. 0.95b. 0.85c. 0.75d. None of the answers is correct.

Q: Refer to Exhibit 5-3. What is the probability that in a given game the Lions will score less than 3 goals? a. 0.85 b. 0.55 c. 0.45 d. 0.80

Q: Refer to Exhibit 5-3. What is the probability that in a given game the Lions will score at least 1 goal? a. 0.20 b. 0.55 c. 1.0 d. 0.95

Q: Exhibit 5-3The probability distribution for the number of goals the Lions soccer team makes per game is given below.Number of GoalsProbability00.0510.1520.3530.3040.15Refer to Exhibit 5-3. The expected number of goals per game isa. 0b. 1c. 2d. 2.35

Q: Refer to Exhibit 5-2. The probability of having sales of at least $50,000 isa. 0.5b. 0.10c. 0.30d. 0.90

Q: Exhibit 5-2The probability distribution for the daily sales at Michael's Co. is given below.Daily Sales ($1,000s)Probability400.1500.4600.3700.2Refer to Exhibit 5-2. The expected daily sales area. $55,000b. $56,000c. $50,000d. $70,000

Q: Refer to Exhibit 5-1. The probability of having a demand for at least two microcomputers isa. 0.7b. 0.3c. 0.4d. 1.0

Q: Exhibit 5-1The following represents the probability distribution for the daily demand of microcomputers at a local store.DemandProbability00.110.220.330.240.2Refer to Exhibit 5-1. The expected daily demand isa. 1.0b. 2.2c. 2d. 4

Q: xis a random variable with the probability function: f(x) = x/6 for x= 1,2 or 3.The expected value of xisa. 0.333b. 0.500c. 2.000d. 2.333

Q: The standard deviation is the a. variance squared b. square root of the sum of the deviations from the mean c. same as the expected value d. positive square root of the variance

Q: Excel's __________ function can be used to compute the variance of a discrete random variable. a. SUMPRODUCT b. AVERAGE c. MEDIAN d. VAR

Q: The variance is a weighted average of the a. square root of the deviations from the mean b. square root of the deviations from the median c. squared deviations from the median d. squared deviations from the mean