Q&A Hero

Q: Consider a population of five families with the following data representing the number of pets in each family.FamilyNumber of PetsA2B6C4D3E1a. There are ten possible samples of size 2 (sampling without replacement). List the 10 possible samples of size 2, and determine the mean of each sample.b. Determine the mean and the variance of the population.c. Using the ten sample mean values, compute the mean and the standard error of the mean.

Q: Consider a population of five weights identical in appearance but weighing 1, 3, 5, 7, and 9 ounces.a. Determine the mean and the variance of the population.b. Sampling without replacement from the above population with a sample size of 2 produces ten possible samples. Using the ten sample mean values, determine the mean of the population and the variance of .c. Compute the standard error of the mean.

Q: A sample of 10 members of a video club provides the following data on number of videos they own. Use Excel to answer the questions that follow the data.MemberNumber Owned1200226315847555263527178276948810129a. What is the point estimate for the mean number of videos owned by all video club members?b. Determine the point estimate for the standard deviation of the population.

Q: A sample of 8 new models of automobiles provides the following data on highway miles per gallon. Use Excel to answer the questions that follow the data.ModelHighway Miles Per Gallon133.6226.8320.2438.7535.1628.0726.2827.6a. What is the point estimate for the average highway miles per gallon for all new models of autos?b. Determine the point estimate for the standard deviation of the population.

Q: Starting salaries of a sample of five management majors along with their genders are shown below.EmployeeSalary ($1000s)Gender130F228M322F426F519Ma. What is the point estimate for the starting salaries of all management majors?b. Determine the point estimate for the variance of the population.c. Determine the point estimate for the proportion of male employees.

Q: A simple random sample of 8 employees of a corporation provided the following information.Employee12345678Age2532264050542223GenderMMMMFMMFa. Determine the point estimate for the average age of all employees.b. What is the point estimate for the standard deviation of the population?c. Determine a point estimate for the proportion of all employees who are female.

Q: The population we want to make inferences about is thea. sampled populationb. framec. target populationd. finite population

Q: Which of the following sampling methods does notlead to probability samples? a. stratified sampling b. cluster sampling c. systematic sampling d. convenience sampling

Q: Which of the following is an example of a nonprobability sampling technique? a. simple random sampling b. stratified random sampling c. cluster sampling d. judgment sampling

Q: Convenience sampling is an example of a. probabilistic sampling b. stratified sampling c. a nonprobability sampling technique d. cluster sampling

Q: Cluster sampling is a. a nonprobability sampling method b. the same as convenience sampling c. a probability sampling method d. None of the alternative answers is correct.

Q: Stratified random sampling is a method of selecting a sample in which a. the sample is first divided into groups, and then random samples are taken from each group b. various strata are selected from the sample c. the population is first divided into groups, and then random samples are drawn from each group d. None of the alternative answers is correct.

Q: A sample of 51 observations will be taken from a process (an infinite population). The population proportion equals 0.85. The probability that the sample proportion will be between 0.9115 and 0.946 is a. 0.8633 b. 0.6900 c. 0.0819 d. 0.0345

Q: A sample of 66 observations will be taken from a process (an infinite population). The population proportion equals 0.12. The probability that the sample proportion will be less than 0.1768 is a. 0.0568 b. 0.0778 c. 0.4222 d. 0.9222

Q: 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 a. 0.4332 b. 0.9332 c. 0.0668 d. 0.5668

Q: A sample of 25 observations is taken from a process (an infinite population). The sampling distribution of is

Q: As a general rule, the sampling distribution of the sample proportions can be approximated by a normal probability distribution whenever

Q: 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 a. 0.2 and .04 b. 0.2 and 0.2 c. 20 and .04 d. None of the alternative answers is correct.

Q: A light bulb manufacturer claims its light bulbs will last 500 hours on the average. The lifetime of a light bulb is assumed to follow an exponential distribution.a. What is the probability that the light bulb will have to be replaced within 500 hours?b. What is the probability that the light bulb will last more than 1000 hours?c. What is the probability that the light bulb will last between 200 and 800 hours.

Q: The township of Middleton sets the speed limit on its roads by conducting a traffic study and determining the speed (to the nearest 5 miles per hour) at which 80% of the drivers travel at or below. A study was done on Brown's Dock Road that indicated driver's speeds follow a normal distribution with a mean of 36.25 miles per hour and a variance of 6.25.a. What should the speed limit be?b. What percent of the drivers travel below that speed?

Q: The time at which the mailman delivers the mail to Ace Bike Shop follows a normal distribution with mean 2:00 PM and standard deviation of 15 minutes.a. What is the probability the mail will arrive after 2:30 PM?b. What is the probability the mail will arrive before 1:36 PM?c. What is the probability the mail will arrive between 1:48 PM and 2:09 PM?

Q: Delicious Candy markets a two-pound box of assorted chocolates. Because of imperfections in the candy making equipment, the actual weight of the chocolate has a uniform distribution ranging from 31.8 to 32.6 ounces.a. Define a probability density function for the weight of the box of chocolate.b. What is the probability that a box weighs (1) exactly 32 ounces; (2) more than 32.3 ounces; (3) less than 31.8 ounces?c. The government requires that at least 60% of all products sold weigh at least as much as the stated weight. Is Delicious violating government regulations?

Q: The Harbour Island Ferry leaves on the hour and at 15-minute intervals. The time, x, it takes John to drive from his house to the ferry has a uniform distribution with xbetween 10 and 20 minutes. One morning John leaves his house at precisely 8:00a.m.a. What is the probability John will wait less than 5 minutes for the ferry?b. What is the probability John will wait less than 10 minutes for the ferry?c. What is the probability John will wait less than 15 minutes for the ferry?d. What is the probability John will not have to wait for the ferry?e. Suppose John leaves at 8:05a.m. What is the probability John will wait (1) less than 5 minutes for the ferry; (2) less than 10 minutes for the ferry?f. Suppose John leaves at 8:10a.m. What is the probability John will wait (1) less than 5 minutes for the ferry; (2) less than 10 minutes for the ferry?g. What appears to be the best time for John to leave home if he wishes to maximize the probability of waiting less than 10 minutes for the ferry?

Q: When using Excel's EXPONDIST function, one should choose TRUE for the third input ifa. a probability is desiredb. a cumulative probability is desiredc. the expected value is desiredd. the correct answer is desired

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

Q: Excel's EXPONDIST function can be used to compute a. exponents b. exponential probabilities c. cumulative exponential probabilities d. Both exponential probabilities and cumulative exponential probabilities are correct.

Q: Refer to Exhibit 6-7. The probability that xis between 3 and 6 is a. 0.4512 b. 0.1920 c. 0.2592 d. 0.6065

Q: Refer to Exhibit 6-7. The probability that xis less than 5 is a. 0.6065 b. 0.0606 c. 0.3935 d. 0.9393

Q: Exhibit 6-7f(x) =(1/10) e"‘x/10 x0Refer to Exhibit 6-7. The mean of xisa. 0.10b. 10c. 100d. 1,000

Q: An exponential probability distributiona. is a continuous distributionb. is a discrete distributionc. can be either continuous or discreted. must be normally distributed

Q: The exponential probability distribution is used with a. a discrete random variable b. a continuous random variable c. any probability distribution with an exponential term d. an approximation of the binomial probability distribution

Q: A continuous probability distribution that is useful in describing the time, or space, between occurrences of an event is a(n) a. normal probability distribution b. uniform probability distribution c. exponential probability distribution d. Poisson probability distribution

Q: Excel's NORMINV function can be used to compute a. cumulative probabilities for a standard normal zvalue b. the standard normal zvalue given a cumulative probability c. cumulative probabilities for a normally distributed xvalue d. the normally distributed xvalue given a cumulative probability

Q: Excel's NORMDIST function can be used to compute a. cumulative probabilities for a standard normal zvalue b. the standard normal zvalue given a cumulative probability c. cumulative probabilities for a normally distributed xvalue d. the normally distributed xvalue given a cumulative probability

Q: Excel's NORMSINV function can be used to compute a. cumulative probabilities for a standard normal zvalue b. the standard normal zvalue given a cumulative probability c. cumulative probabilities for a normally distributed xvalue d. the normally distributed xvalue given a cumulative probability

Q: Excel's NORMSDIST function can be used to compute a. cumulative probabilities for a standard normal zvalue b. the standard normal zvalue given a cumulative probability c. cumulative probabilities for a normally distributed xvalue d. the normally distributed xvalue given a cumulative probability

Q: Refer to Exhibit 6-6. What is the probability that a randomly selected tire will have a life of exactly 47,500 miles? a. 0.4332 b. 0.9332 c. 0.0668 d. zero

Q: Refer to Exhibit 6-6. What percentage of tires will have a life of 34,000 to 46,000 miles? a. 38.49% b. 76.98% c. 50% d. None of the alternative answers is correct.

Q: Refer to Exhibit 6-6. What is the probability that a randomly selected tire will have a life of at least 47,500 miles? a. 0.4332 b. 0.9332 c. 0.0668 d. None of the alternative answers is correct.

Q: Refer to Exhibit 6-6. What is the probability that a randomly selected tire will have a life of at least 30,000 miles? a. 0.4772 b. 0.9772 c. 0.0228 d. None of the alternative answers is correct.

Q: Exhibit 6-6The 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 random variable in this experiment?a. the life expectancy of this brand of tireb. the normal distributionc. 40,000 milesd. None of the alternative answers is correct.

Q: Refer to Exhibit 6-5. What is the probability that a randomly selected item weighs exactly 8 ounces?a. 0.5b. 1.0c. 0.3413d. None of the alternative answers is correct.

Q: Refer to Exhibit 6-5. What percentage of items will weigh between 6.4 and 8.9 ounces? a. 0.1145 b. 0.2881 c. 0.1736 d. 0.4617

Q: Refer to Exhibit 6-5. What percentage of items will weigh at least 11.7 ounces?a. 46.78%b. 96.78%c. 3.22%d. 53.22%

Q: Refer to Exhibit 6-5. What is the probability that a randomly selected item will weigh between 11 and 12 ounces? a. 0.4772 b. 0.4332 c. 0.9104 d. 0.0440

Q: Refer to Exhibit 6-5. What is the probability that a randomly selected item will weigh more than 10 ounces? a. 0.3413 b. 0.8413 c. 0.1587 d. 0.5000

Q: Exhibit 6-5The 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?a. the weight of items produced by a machineb. 8 ouncesc. 2 ouncesd. the normal distribution

Q: Refer to Exhibit 6-4. What percentage of MBA's will have starting salaries of $34,000 to $46,000?a. 38.49%b. 38.59%c. 50%d. 76.98%

Q: 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? a. 0.4332 b. 0.9332 c. 0.0668 d. 0.5000

Q: 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? a. 0.4772 b. 0.9772 c. 0.0228 d. 0.5000

Q: Exhibit 6-4The 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?a. the starting salariesb. the normal distributionc. $40,000d. $5,000

Q: Refer to Exhibit 6-3. What is the minimum weight of the middle 95% of the players?a. 196b. 151c. 249d. None of the alternative answers is correct.

Q: Refer to Exhibit 6-3. What percent of players weigh between 180 and 220 pounds? a. 34.13% b. 68.26% c. 0.3413% d. None of the alternative answers is correct.

Q: Refer to Exhibit 6-3. The probability of a player weighing less than 250 pounds is a. 0.4772 b. 0.9772 c. 0.0528 d. 0.5000

Q: Refer to Exhibit 6-3. The probability of a player weighing more than 241.25 pounds is a. 0.4505 b. 0.0495 c. 0.9505 d. 0.9010

Q: Exhibit 6-3The 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?a. the weight of football playersb. 200 poundsc. 25 poundsd. the normal distribution

Q: The ages of students at a university are normally distributed with a mean of 21. What percentage of the student body is at least 21 years old?a. It could be any value, depending on the magnitude of the standard deviationb. 50%c. 21%d. 1.96%

Q: Xis a normally distributed random variable with a mean of 22 and a standard deviation of 5. The probability that Xis less than 9.7 is a. 0.000 b. 0.4931 c. 0.0069 d. 0.9931

Q: Xis a normally distributed random variable with a mean of 12 and a standard deviation of 3. The probability that Xequals 19.62 is a. 0.000 b. 0.0055 c. 0.4945 d. 0.9945

Q: Xis a normally distributed random variable with a mean of 5 and a variance of 4. The probability that Xis greater than 10.52 is a. 0.0029 b. 0.0838 c. 0.4971 d. 0.9971

Q: Xis a normally distributed random variable with a mean of 8 and a standard deviation of 4. The probability that Xis between 1.48 and 15.56 is a. 0.0222 b. 0.4190 c. 0.5222 d. 0.9190

Q: For a standard normal distribution, the probability of obtaining a zvalue between -1.9 to 1.7 is a. 0.9267 b. 0.4267 c. 1.4267 d. 0.5000

Q: For a standard normal distribution, the probability of obtaining a zvalue of less than 1.6 is a. 0.1600 b. 0.0160 c. 0.0016 d. 0.9452

Q: For a standard normal distribution, the probability of obtaining a zvalue between -2.4 to -2.0 is a. 0.4000 b. 0.0146 c. 0.0400 d. 0.5000

Q: Zis a standard normal random variable. What is the value of zif the area to the right of zis 0.9803? a. -2.06 b. 0.4803 c. 0.0997 d. 3.06

Q: Zis a standard normal random variable. What is the value of zif the area between -zand zis 0.754? a. 0.377 b. 0.123 c. 2.16 d. 1.16

Q: Given that zis a standard normal random variable, what is the value of zif the area to the left of zis 0.9382? a. 1.8 b. 1.54 c. 2.1 d. 1.77

Q: Given that zis a standard normal random variable, what is the value of zif the area to the right of zis 0.1401? a. 1.08 b. 0.1401 c. 2.16 d. -1.08

Q: Given that zis a standard normal random variable, what is the value of zif the area to the right of zis 0.1112? a. 0.3888 b. 1.22 c. 2.22 d. 3.22

Q: Zis a standard normal random variable. The P(z>2.11) equals a. 0.4821 b. 0.9821 c. 0.5 d. 0.0174

Q: Zis a standard normal random variable. The P("‘1.5 <z<1.09) equals a. 0.4322 b. 0.3621 c. 0.7953 d. 0.0711

Q: Zis a standard normal random variable. The P (-1.20 ï‚£zï‚£1.50) equals a. 0.0483 b. 0.3849 c. 0.4332 d. 0.8181

Q: Zis a standard normal random variable. The P(-1.96 ï‚£zï‚£-1.4) equals a. 0.8942 b. 0.0558 c. 0.475 d. 0.4192

Q: Zis a standard normal random variable. The P(1.41 < z< 2.85) equals a. 0.4772 b. 0.3413 c. 0.8285 d. None of the alternative answers is correct.

Q: Zis a standard normal random variable. The P(1.05 <z<2.13) equals a. 0.8365 b. 0.1303 c. 0.4834 d. None of the alternative answers is correct.

Q: Zis a standard normal random variable. The P(1.20 ï‚£zï‚£1.85) equals a. 0.4678 b. 0.3849 c. 0.8527 d. 0.0829

Q: For a standard normal distribution, the probability of zï‚£0 is a. zero b. -0.5 c. 0.5 d. one

Q: The standard deviation of a standard normal distribution a. is always equal to zero b. is always equal to one c. can be any positive value d. can be any value

Q: The mean of a standard normal probability distribution a. is always equal to 1 b. can be any value as long as it is positive c. can be any value d. None of the alternative answers is correct.

Q: For the standard normal probability distribution, the area to the left of the mean is a. -0.5 b. 0.5 c. any value between 0 to 1 d. 1