Term
1.A numerical description of the outcome of an experiment is called a
a.
descriptive statistic
b.
probability function
c.
variance
d.
random variable |
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2. 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
a.
uniform probability distribution
b.
binomial probability distribution
c.
Hyper-geometric probability distribution
d.
normal probability distribution |
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3. A continuous random variable may assume
a.
any value 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.
only the positive integer values in an interval |
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Term
4. An experiment consists of making 80 telephone calls in order to sell a particular insurance policy. The random variable in this experiment is a
a.
discrete random variable
b.
continuous random variable
c.
complex random variable
d.
simplex random variable |
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Term
5. Which of the following statements about a discrete random variable and its probability distribution are true?
a.
Values of the random variable can never be negative.
b.
Some negative values of f(x) are allowed as long as f(x) = 1.
c.
Values of f(x) must be greater than or equal to zero.
d.
The values of f(x) increase to a maximum point and then decrease. |
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6. The expected value of a random variable is
a.
the value of the random variable that should be observed on the next repeat of the experiment
b.
the value of the random variable that occurs most frequently
c.
the square root of the variance
d.
None of these alternatives is correct. |
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7. The expected value for a binomial probability distribution is
a.
E(x) = Pn(1 - n)
b.
E(x) = P(1 - P)
c.
E(x) = nP
d.
E(x) = nP(1 - P) |
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Definition
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Term
8. The center of a normal curve is
a.
always equal to zero
b.
is the mean of the distribution
c.
cannot be negative
d.
is the standard deviation |
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9. 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.
the area under the curve to the right of x
d.
the height of the function at x |
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Term
10.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.
almost zero |
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Term
12. A continuous random variable is uniformly distributed between a and b. The probability density function between a and b is
a.
zero
b.
(a - b)
c.
(b - a)
d.
1/(b - a) |
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Definition
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Term
18. If we consider the simple random sampling process as an experiment, the sample mean is
a.
always zero
b.
always smaller than the population mean
c.
a random variable
d.
exactly equal to the population mean |
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19. Whenever the population has a normal probability distribution, the sampling distribution of is a normal probability distribution for
a.
only large sample sizes
b.
only small sample sizes
c.
any sample size
d.
only samples of size thirty or greate |
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Term
22. For a population with any distribution, the form of the sampling distribution of the sample mean is
a.
sometimes normal for all sample sizes
b.
sometimes normal for large sample sizes
c.
always normal for all sample sizes
d.
always normal for large sample sizes |
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Definition
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Term
23. The absolute value of the difference between the point estimate and the population parameter it estimates is
a.
the standard error
b.
the sampling error
c.
precision
d.
the error of confidence |
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Term
26. A sample of 200 elements from a population with a known standard deviation is selected. For an interval estimation of , the proper distribution to use is the
a.
normal distribution
b.
t distribution with 200 degrees of freedom
c.
t distribution with 201 degrees of freedom
d.
t distribution with 202 degrees of freedom |
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Definition
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Term
15. Parameters are
a.
numerical characteristics of a sample
b.
numerical characteristics of a population
c.
the averages taken from a sample
d.
numerical characteristics of either a sample or a population |
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Definition
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Term
16. Sampling distribution of is the
a.
probability distribution of the sample mean
b.
probability distribution of the sample proportion
c.
mean of the sample
d.
mean of the population |
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Definition
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17. Since the sample size is always smaller than the size of the population, the sample mean
a.
must always be smaller than the population mean
b.
must be larger than the population mean
c.
must be equal to the population mean
d.
can be smaller, larger, or equal to the population mean |
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Definition
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Term
16. Sampling distribution of is the
a.
probability distribution of the sample mean
b.
probability distribution of the sample proportion
c.
mean of the sample
d.
mean of the population |
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Definition
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Term
17. Since the sample size is always smaller than the size of the population, the sample mean
a.
must always be smaller than the population mean
b.
must be larger than the population mean
c.
must be equal to the population mean
d.
can be smaller, larger, or equal to the population mean |
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Definition
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Term
24. When s is used to estimate , the margin of error is computed by using
a.
normal distribution
b.
t distribution
c.
the mean of the sample
d.
the mean of the population |
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27.A 95% confidence interval for a population mean is determined to be 100 to 120. If the confidence coefficient is reduced to 0.90, the interval for
a.
becomes narrower
b.
becomes wider
c.
does not change
d.
becomes 0.1 |
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Definition
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Term
28. When the level of confidence decreases, the margin of error
a.
stays the same
b.
becomes smaller
c.
becomes larger
d.
becomes smaller or larger, depending on the sample size |
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Definition
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Term
29. The sample size needed to provide a margin of error of 2 or less with a .95 probability when the population standard deviation equals 11 is
a.
10
b.
11
c.
116
d.
117 |
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Definition
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Term
30. When constructing a confidence interval for the population mean and the standard deviation of the sample is used, the degrees of freedom for the t distribution equals
a.
n-1
b.
n
c.
29
d.
30 |
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Definition
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