PHC 4069-A distribution of sample means is a collection of sample

Question 1
1 pts

A distribution of sample means is a collection of sample
means from
samples of different sizes from different populations.
samples of size N from different populations.
samples of size N from the same population.
samples of different sizes from the same population

Question 2
1 pts

A friend of mine studies the effects of praise on happiness.
She believes that children who receive praise are happier
overall than children who do not receive praise. She
measures happiness by counting the number of times a child
smiles in a one hour period. She knows that in the population
of children who do not receive praise smiles average 4 times
per hour with a standard deviation of .5, and that these data
are normally distributed. She selects a sample of 100
children whom she knows receive praise and finds that they
smile an average of 3.5 times per hour. The characteristics of
the appropriate comparison (sampling) distribution are
a mean of zero and a standard deviation of 1.
a mean of 4 and a standard deviation of .5.
a mean of 4 and a standard deviation of .05.
a mean of 3.5 and a standard deviation of .5.

Question 3
1 pts

The normal approximation to the binomial distribution is
most useful for finding which of the following?
The probability P(X = 5) when X is a binomial
random variable with large n
The probability P(X 5) when X is a binomial
random variable with large n.
The probability P(X = 5) when X is a normal random
variable with small n
The probability P(X 5) when X is a normal random
variable with small n

Question 4
1 pts

The central limit theorem tells us that the sampling
distribution of the sample mean is approximately normal.
Which of the following conditions are necessary for the
theorem to be valid:
a) The sample size has to be large.
b) We have to be sampling from a normal
population.
c) The population has to be symmetric.
d) Both a) and c).

Question 5
1 pts

The Central Limit Theorem is important in statistics because

a) for a large sample size n, it says the population is
approximately normal
b) for any population, it says the sampling distribution
of the sample mean is approximately normal,
regardless of the sample size.
c) for a large sample size n, it says the sampling
distribution of the sample mean is approximately
normal, regardless of the shape of the population
d) both a) and c).above.

Question 6
1 pts

The standard error of the proportion p will become larger
as p approaches 0.
as p approaches .50.

as p approaches 1.00.
as n increases.

Question 7
1 pts

Since the sample size is always smaller than the size of the
population, the sample mean
must always be smaller than the population mean
must be larger than the population mean
must be equal to the population mean

can be smaller, larger, or equal to the population
mean

Question 8
1 pts

A simple random sample from an infinite population
is a sample selected such that
each element is selected independently and from
the same population
each element has a 0.5 probability of being
selected
each element has a probability of at least 0.5 of
being selected
the probability of being selected changes

Question 9
1 pts

If we consider the simple random sampling process as an
experiment, the sample mean is
always zero
always smaller than the population mean
a random variable
exactly equal to the population mean

Question 10
1 pts

As the sample size becomes larger, the sampling distribution
of sample mean approaches a

binomial distribution
either binomial distribution or normal
distribution
normal distribution
none of the above