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problem 1. The standard error of the mean is actually the standard deviation of all of the means that make up the distribution of sample means.
True
False

problem 2. What is the advantage of a one-tailed test over a two-tailed test?
Less data variability in the groups involved.
Smaller critical values indicate significance.
Rejecting at HO
= .05 involves less chance of error.
There are fewer calculations to make.

problem 3. Type I errors may occur with ______ results and type II errors with ______ results.
statistically significant, statistically significant
statistically significant, statistically non-significant
statistically non-significant, statistically significant
statistically non-significant, statistically non-significant

problem 4. What is the alternate hypothesis in a problem where sales group two is predicted to be ". . . significantly less productive than sales group one?"
HA: μ1
≠ μ 2
HA: μ 1= μ 2
HA: μ 1> μ2
HA: μ 1< μ 2

problem 5. Which of the following defines statistical significance?
The outcome is unlikely to have occurred by chance.
The outcome is important.
The outcome is unusual.
The outcome is one that can be describeed by normal circumstances.

problem 6. Statistical significance for a tested mean difference means practical significance as well.
True
False

problem 7. The desired sample size depends only the size of the population to be tested.
True
False

problem 8. Which of the following is a provision of the central limit theorem?
A skewed distribution will remain skewed however it is plotted.
There are limits to the range of scores that can be fitted to a distribution.
A distribution based on sample means will be normal.
There will always be theoretical differences between distributions.

problem 9. What problem does the z test answer?
Is the individual characteristic of the group?
Has there been a type I error?
Does the sample represent the population?
Are the data normal?

problem 10. Large differences in the numerator of a statistical test for differences for means are the only critical factor in determining statistical significance.
True
False

Statistics and Probability, Statistics

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