Reference no: EM131018376

1. The mean of the distribution of sample means will have the same value as the mean of the distribution of individual scores upon which it is based.

True

False

Question 2. What statistic measures data variability in both groups in an independent t-test?

The critical value of t.

The M1

- M2 difference.

The calculated value of t.

The SEd

Question 3. What question 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?

Question 4. The desired sample size depends only the size of the population to be tested.

True

False
Question 5. 5. How do statistical tests like the one sample t adjust for the absence of parameter values?

The values are estimated from sample data.

The values are assumed to have a constant value.

The test is reconstructed so that the values aren't needed.

The test is reformulated so that data are always normal.

Question 6. 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

Question 7. 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 explained by normal circumstances.

Question 8. Each different t-distribution is defined by which of the following?

The degree of normality in the data.

The degrees of freedom for the problem.

The amount of variability in the data.

The amount of difference between M and μM.

Question 9. What is the relationship between the power of a statistical test and decision errors?

Powerful tests minimize the risk of decision errors.

Powerful tests are more inclined to type II than type I errors.

Powerful tests compensate for decision errors with stronger effect sizes.

Powerful tests minimize type II errors.

Question 10. 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.