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Q:
A sampling distribution for a sample mean shows the distribution of the possible values for the sample mean for a given sample size from a population.
Q:
A sampling distribution is the distribution of the individual values that are included in a sample from a population.
Q:
Sampling error can be eliminated if the sample size is large enough.
Q:
A major automobile manufacturer has developed a new model car that it claims will average 25 mpg on the highway. A random sample of fifty of these cars was tested and they averaged 24 mpg. This means that the claim made by the auto company is incorrect.
Q:
It is very unlikely that a nonstatistical sample will ever provide less sampling error than a statistical sample of the same size.
Q:
If it is desired that sampling error be reduced, one step that tends to work is to increase the sample size that is selected from the population.
Q:
Sampling error can be eliminated if the sampling is done properly.
Q:
Sampling error occurs when the population parameter and the sample statistic are different.
Q:
Suppose the mean balance of checking accounts at Regions Bank is known to be $4320. A random sample of 10 accounts yields a total of $41,490. This means the sampling error is -$171.
Q:
A simple random sample is selected in a manner such that each possible sample of a given size has an equal chance of being selected.
Q:
An increase in sample size will tend to result in less sampling error.
Q:
If a population mean is equal to 200, the sample mean for a random sample selected from the population is about as likely to be higher or lower than 200.
Q:
A local bank has 1,400 checking account customers. Of these, 1,020 also have savings accounts. A sample of 400 checking account customers was selected from the bank of which 302 also had savings accounts. The sampling error in this situation is .0264.
Q:
A larger sample size reduces the potential for large sampling error.
Q:
A smaller sample might provide less sampling error than a larger sample from a given population.
Q:
Suppose it is known that the mean purchase price for all homes sold last year in Blacksburg, Virginia was $203,455. Recently, two studies were done on home sales prices. In the first study, a random sample of 200 homes was selected from the population. In the second study, a random sample of 60 homes was selected. Based on this information, we know that the second study would contain more sampling errors than the first study due to the smaller sample size.
Q:
If a sample is selected using random sampling methods, the primary reason that the sample mean might be different from the corresponding population mean is that the sample might be biased.
Q:
If the mean age for all students that attend your university is 24.78 years, it would be reasonable to expect that the mean of a sample of students selected from that population would also equal 24.78 years as long at the sampling is done using sound statistical methods.
Q:
The reason that a population mean and the mean of a random sample selected from that population might be different is that the sample mean is found by dividing by n-1 while the population mean is found by dividing by n.
Q:
Sampling error is the difference between the sample statistic and the population parameter.
Q:
The actual mean fill volume for all bottles of a soft drink product that were filled on a Tuesday is 11.998 ounces. A sample of 64 bottles was randomly selected and the sample mean fill volume was 12.004 ounces. Based upon this information, the sampling error is .006 ounce.
Q:
Recently the State Fish and Game planted several thousand tagged fish in a local river. The mean length of these fish, which constitute a population, is 12.6 inches. Yesterday, fishermen caught 100 of these tagged fish. You could expect that the mean length for these fish would be 12.6 inches as well since they come from the population.
Q:
Taking a larger sample size will always result in less sampling error but costs more money and takes more time.
Q:
The size of the sampling error that comes from a random sample depends on both the variation in the population and the size of the sample being selected.
Q:
The sample mean is a parameter.
Q:
An assembly process takes between 20 and 40 minutes to complete with the distribution of time thought to be uniformly distributed. Based on this, the percentage of assemblies that require less than 25 minutes is 0.05.
Q:
The amount of drying time for the paint applied to a plastic component part is thought to be uniformly distributed between 30 and 60 minutes. Currently, the automated process selects the part from the drying bin after the part has been there for 50 minutes. The probability that none of three parts picked are still wet when they are selected is approximately 0.04.
Q:
The amount of drying time for the paint applied to a plastic component part is thought to be uniformly distributed between 30 and 60 minutes. Currently, the automated process selects the part from the drying bin after the part has been there for 50 minutes. Based on this, the probability that a part selected will not be dry is approximately 0.33.
Q:
It has been determined the weight of bricks made by the Dillenger Stone Company is uniformly distributed between 1 and 1.5 pounds. Based on this information, the probability that two randomly selected bricks will each weigh more than 1.3 pounds is 0.16.
Q:
If a uniform distribution and normal distribution both have the same mean and the same range, the normal distribution will have a larger standard deviation than the uniform distribution
Q:
If the time it takes for a customer to be served at a fast-food chain business is thought to be uniformly distributed between 3 and 8 minutes, then the probability that the time it takes for a randomly selected customer to be served will be less than 5 minutes is 0.40.
Q:
Suppose the time it takes for a customer to be served at a fast-food chain business is thought to be uniformly distributed between 3 and 8 minutes, then the probability that a customer is served in less than 3 minutes is 0.
Q:
One of the basic differences between a uniform probability distribution and a normal probability distribution is that the uniform is symmetrical but the normal is skewed depending on the value of the standard deviation.
Q:
Suppose the time it takes for a customer to be served at a fast-food chain business is thought to be uniformly distributed between 3 and 8 minutes, then the probability that it will take exactly 5 minutes is 0.20.
Q:
For a normal distribution, the probability of a value being between a positive z-value and its population mean is the same as that of a value being between a negative z-value and its population mean.
Q:
Any normal distribution can be converted to a standard normal distribution.
Q:
The vehicle speeds on a city street have been determined to be normally distributed with a mean of 33.2 mph and a variance of 16. Based on this information, the probability that if three randomly selected vehicles are monitored and that two of the three will exceed the 35 mph speed limit is slightly greater than 0.18.
Q:
A seafood shop sells salmon fillets where the weight of each fillet is normally distributed with a mean of 1.6 pounds and a standard deviation of 0.3 pounds. Based on this information we can conclude that 90 percent of the fillets weight more than 1.0 pound.
Q:
A seafood shop sells salmon fillets where the weight of each fillet is normally distributed with a mean of 1.6 pounds and a standard deviation of 0.3 pounds. They want to classify the largest fillets as extra large and charge a higher price for them. If they want the largest 15 percent of the fillets to be classified as extra large, the minimum weight for an extra large fillet should be 1.91 pounds.
Q:
The Varden Packaging Company has a contract to fill 50-gallon barrels with gasoline for use by the U.S. Army. The machine that Varden uses has an adjustable device that allows the average fill per barrel to be adjusted as desired. However, the actual distribution of fill volume from the machine is known to be normally distributed with a standard deviation equal to 0.5 gallons. The contract that Varden has with the military calls for no more than 2 percent of all barrels to contain less than 49.2 gallons of gasoline. Suppose Varden managers are unwilling to set the mean fill at any level higher than 50 gallons. Given that, in order to meet the requirements, they will need to increase the standard deviation of fill volume.
Q:
The Varden Packaging Company has a contract to fill 50-gallon barrels with gasoline for use by the U.S. Army. The machine that Varden uses has an adjustable device that allows the average fill per barrel to be adjusted as desired. However, the actual distribution of fill volume from the machine is known to be normally distributed with a standard deviation equal to 0.5 gallons. The contract that Varden has with the military calls for no more than 2 percent of all barrels to contain less than 49.2 gallons of gasoline. In order to meet this requirement, Varden should set the mean fill to approximately 50.225 gallons.
Q:
The Varden Packaging Company has a contract to fill 50 gallon barrels with gasoline for use by the U.S. Army. The machine that Varden uses has an adjustable device that allows the average fill per barrel to be adjusted as desired. However, the actual distribution of fill volume from the machine is known to be normally distributed with a standard deviation equal to 0.5 gallons. The contract that Varden has with the military calls for no more than 2 percent of all barrels to contain less than 49.2 gallons of gasoline. In order to meet this requirement, Varden should set the mean fill to approximately 49.92 gallons.
Q:
Watersports Rental at Flathead Lake rents jet skis and power boats for day use. Each piece of equipment has a clock that records the time that it was actually in use while rented. The company has observed over time that the distribution of time used is normally distributed with a mean of 3.6 hours and a standard deviation equal to 1.2 hours. Watersports management has decided to give a rebate to customers who use the equipment for only a short amount of time. They wish to grant a rebate to no more than 10 percent of all customers. Based on the information provided, the amount of time that should be set as the cut-off between getting the rebate and not getting the rebate is approximately 2.06 hours.
Q:
Watersports Rental at Flathead Lake rents jet skis and power boats for day use. Each piece of equipment has a clock that records the time that it was actually in use while rented. The company has observed over time that the distribution of time used is normally distributed with a mean of 3.6 hours and a standard deviation equal to 1.2 hours. Watersports management has decided to give a rebate to customers who use the equipment for less than 2.0 hours. Based on this information, the probability that a customer will get the rebate is 0.4082.
Q:
The State Department of Forests has determined that annual tree growth in a particular forest area is normally distributed with a mean equal to 17 inches and a standard deviation equal to 6 inches. If 2 trees are randomly chosen, the probability that both trees will have grown more than 20 inches during the year is approximately .037.
Q:
The State Department of Forests has determined that annual tree growth in a particular forest area is normally distributed with a mean equal to 17 inches and a standard deviation equal to 6 inches. Based on this information, it is possible for a randomly selected tree not to have grown any during a year.
Q:
The time it takes a parent to assemble a children's bicycle has been shown to be normally distributed with a mean equal to 295 minutes with a standard deviation equal to 45 minutes. Given this information, the probability that it will take a randomly selected parent more than 220 minutes is about 0.0475.
Q:
The standard normal distribution has a mean of 0 and a standard deviation of 1.0.
Q:
The standard normal distribution table provides probabilities for the area between the z-value and the population mean.
Q:
The actual weight of 2-pound sacks of salted peanuts is found to be normally distributed with a mean equal to 2.04 pounds and a standard deviation of 0.25 pounds. Given this information, the probability of a sack weighing more than 2.40 pounds is 0.4251.
Q:
The parameters of a normal distribution are the mean and the standard deviation.
Q:
All symmetric distributions can be assumed normally distributed.
Q:
When a single die is rolled, each of the six sides are equally likely. This is an example of a uniform distribution.
Q:
If the mean, median and mode are all equal for a continuous random variable, then the random variable is normally distributed.
Q:
A continuous random variable approaches normality as the level of skewness increases.
Q:
For a continuous distribution the total area under the curve is equal to 100.
Q:
When graphed, the probability distribution for a discrete random variable looks like a histogram.
Q:
The probability distribution for a continuous random variable is represented by a probability density function that defines a curve.
Q:
One example of a difference between discrete random variables and continuous random variables is that in a discrete distribution P(x > 2) = P(x 3) while in a continuous distribution P(x > 2) is treated the same as P(x 2).
Q:
The number of defects manufactured by workers in a small engine plant is an example of a discrete random variable.
Q:
Typically, a continuous random variable is one whose value is determined by measurement instead of counting.
Q:
The normal distribution is one of the most frequently used discrete probability distributions.
Q:
At the West-Side Drive-Inn, customers arrive at the rate of 10 every 30 minutes. The time between arrivals is exponentially distributed. Based on this information, what is the probability that the time between two customers arriving will exceed 6 minutes?
Q:
At the West-Side Drive-Inn, customers arrive at the rate of 10 every 30 minutes. The time between arrivals is exponentially distributed. Given this, what is the mean time between arrivals?
Q:
In comparing a uniform distribution with a normal distribution where both distributions have the same mean and the same range, explain which distribution will have the larger standard deviation.
Q:
The money spent by people at an amusement park, after paying to get in the gate, is thought to be uniformly distributed between $5.00 and $25.00. Based on this, what is the probability that someone will spend between $8.00 and $12.00?
Q:
The fares received by taxi drivers working for the City Taxi line are normally distributed with a mean of $12.50 and a standard deviation of $3.25. Suppose a driver has four consecutive fares that are less than $6.00. What is the probability of this happening?
Q:
The fares received by taxi drivers working for the City Taxi line are normally distributed with a mean of $12.50 and a standard deviation of $3.25. Based on this information, what is the probability that a specific fare will exceed $15.00?
Q:
A class takes an exam where the average time to complete the exam is normally distributed with a time of 40 minutes and standard deviation of 9 minutes. If the class lasts 1 hour, what percent of the students will have turned in the exam after 60 minutes?
Q:
The weight of sacks of potatoes is normally distributed with a mean of 20 pounds and a standard deviation of 2 pounds. The weight of sacks of onions is also normally distributed with a mean of 20 pounds and a standard deviation of 0.50 pounds. Based on this information, which product will yield the highest probability of getting a very heavy sack?
Q:
What is the difference between a normal distribution and the standard normal distribution?
Q:
A random variable is normally distributed with a mean of 25 and a standard deviation of 5. If an observation is randomly selected from the distribution, what value will 15% of the observations be below?
A) 19.8
B) 16.2
C) 18.7
D) 17.2
Q:
A random variable is normally distributed with a mean of 25 and a standard deviation of 5. If an observation is randomly selected from the distribution, determine two values of which the smallest has 25% of the values below it and the largest has 25% of the values above it.
A) 18.85 and 27.94
B) 19.31 and 21.12
C) 16.23 and 18.82
D) 21.65 and 28.35
Q:
A random variable is normally distributed with a mean of 25 and a standard deviation of 5. If an observation is randomly selected from the distribution, what value will be exceeded 85% of the time?
A) 16.2
B) 17.9
C) 19.8
D) 14.2
Q:
A random variable is normally distributed with a mean of 25 and a standard deviation of 5. If an observation is randomly selected from the distribution, what value will be exceeded 10% of the time?
A) 31.40
B) 28.60
C) 66.23
D) 14.56
Q:
A randomly selected value from a normal distribution is found to be 2.1 standard deviations above its mean. What is the probability that a randomly selected value from the distribution will be less than 2.1 standard deviations from the mean?
A) 0.9488
B) 0.9821
C) 0.9976
D) 0.9712
Q:
A randomly selected value from a normal distribution is found to be 2.1 standard deviations above its mean. What is the probability that a randomly selected value from the distribution will be greater than 2.1 standard deviations above the mean?
A) 0.0179
B) 0.0512
C) 0.0231
D) 0.0024
Q:
For the normal distribution with parameters = 0, = 3; calculate P(x > 1).A) 0.5812B) 0.1214C) 0.3707D) 0.4412
Q:
For the normal distribution with parameters = 4, = 3; calculate P(x > 1).A) 0.8413B) 0.4562C) 0.7812D) 0.4152
Q:
For the normal distribution with parameters = 3, = 2; calculate P(0 < x < 8).A) 0.3124B) 0.9270C) 0.8123D) 0.6723