Business Stats Exam 3
The power of a test is
(1-B)
When the sample size is equal to or more than 30, the distribution of the samples; mean will be _______ even though the population distribution may be extremely skewed.
approximately normal
The Central Limit Theorem states that regardless of the shape of the population distribution, the distribution of the samples' mean will be _______, provided that the samples we take are ________.
approximately normal; sufficiently large
In a one-tailed test of hypothesis, the critical point is a point that
divides the area under the sampling distribution of a sample statistic into one rejection and one non rejection region
The probability distribution of a sample statistic is called
the sampling distribution of that statistic
Suppose we know that the mean age of all students at a university is 24 years. The mean age of a random sample of 100 students selected from this university is found to e 23.6 years. The difference 23.6 - 24= -0.4 is called:
the sampling error
A sampling distribution is the probability distribution of
A sample statistic
The sampling distribution is the probability distribution of
A sample statistic
In a two-tailed test of hypothesis, the two critical points:
divide the area under the sampling distribution of a sample statistic into two rejection and one non region
The formula for the standard error of the proportion used in hypothesis testing is the same as that used in interval estimation.
False
The sample mean is an inconsistent estimator of the population mean
False
Given the sample size, the standard error of the mean will be larger,
The larger the standard deviation of the population from which the samples are taken.
The mean of the sampling distribution of the sample mean is....
The mean of the means of all possible samples of the same size taken from the population
The relationship between a parameter and its corresponding statistic can be describes as:
The statistic deals only with the sample, wile the parameter deals with population. The statistic is often a good estimator of the parameter. If the estimator is consistent, as the sample size becomes large, the value of the statistic approaches the value of the parameter.
An estimator is said to be unbiased if the expected value of the statistic is equal to the value of the corresponding parameter.
True
The critical value enables us to identify the rejection region in hypothesis testing
True
The wiser the confidence interval is, the less precise is our estimate of the parameter
True
The error of rejection a true null hypothesis is called _________
Type I error
The error of not rejecting a false null hypothesis is called _______
Type II error
The null hypothesis is a claim:
about a population parameter that is assumed to be true until it is declared false.
the alternative hypothesis is a claim:
about a population parameter that will be true if the null hypothesis is false.
The mean of of the sampling distribution of the sample mean
always equal to the population mean
The sample mean is:
an estimator of the population mean, an unbiased estimator of M, a consistent estimator of p.
The sample proportion is:
an estimator of the population proportion, an unbiased estimator of p, a consistent estimator of p.
The Central Limit Theorem states that when the sample size is sufficiently large, the sampling distribution of the proportion will be ____ with its mean centered at ____ and its standard deviation equal to ____.
approx. normal; p; squareroot: (pq/n)
As the confidence coefficient (CC) increases, the confidence interval...
becomes wider
the sampling distribution of p hat is normal if
boh np > 5 and np > 5
The sampling distribution of the proportion is approximately normal when...
both np > 5 and nq > 5
The significance level, denoted by alpha, is the probability of
committing a Type I error
If an estimator tends to approach the value of the population parameter as the sample size increases, the estimator is said to be
consistent
As sample size increases, the probability that the mean of a sample will be vary far away from the mean of the population will:
decrease
When n increases, the standard error of the mean _______
decreases
With a fixed sample size, as Type I error increases, Type II error
decreases
In determining the sample size needed to estimate a parameter, a researcher need to
know the confidence coefficient, know the maximum error of estimation desired, have an idea about the standard deviation
The sample size needed to estimate a parameter is
larger the larger confidence coefficient is, larger the larger the variance is, larger the more precisely you want to be able to estimate the parameter.
Non sampling errors are the errors
made while collecting, recording, and tabulating data
The standard error of the mean...
measures the amount of variation in the sampling distribution
As n increases, the sample mean will become _____ around the population mean.
more clustered
The further away the mean of our sample is from the hypothesis population mean, the _______ we are to reject the null hypothesis.
more likely
The standard deviation of the sampling distribution of the sample mean decreases when
n increases
The mean of the sampling distribution of p hat is always equal to
p
The value of Beta gives the
probability of committing a Type II error
The standard error of the mean is _____ the standard deviation of the population from which the samples are taken.
smaller than
A sampling error is
the difference between the value of a sample statistic based on a random sample and the value of the corresponding population parameter.
The probability of rejecting a correct null hypothesis is ____ which is represented by the symbol _______
the level of significance of a test; a
The mean of the sampling distribution of x bar is always equal to...
the mean
Suppose we know that the mean weekly earning of all employees of a company are $822. The mean weekly earning of a random sample if 25 employees selected form theis company is found to be $837. The difference 837 - 822 = 15 is called:
the non-sampling error
A two-tailed test is a test with
two rejection regions
By rejecting the null hypothesis, are you stating that the alternative hypothesis is true?
yes (proof by contradiction)
