Exam 19: Inferential Statistics

What type of error would you make if you rejected a true null hypothesis (i.e., a false positive)?

If you drew all possible samples from some population, calculated the mean for each of the samples, and constructed a line graph (showing the shape of the distribution) based on all of those means, what would you have?

Define inferential statistics.

Explain the difference between statistical and practical significance.

If you failed to reject a false null hypothesis (i.e., a false negative), you are making a:

A researcher will usually test his or her regression coefficients for statistical significance in order to ensure that the observed coefficient is not due simply to chance.

The calculation of effect size indicators is not very important because all that is really important is whether a finding is statistically significant.

Dr. Jones conducted a study and found that the 95% confidence interval for the data in his sample was 42-64. Based upon this information we know that the margin of error is:

In hypothesis testing, the statistical decision is made in the final step.

You can use the analysis of variance test for statistical significance when you have how many means to compare?

When using inferential statistics, researchers go beyond their data to make statements about the population from which the sample was chosen.

The alternative hypothesis refers to sample statistics.

The _____ is a statement that the population parameter is some value other than the value stated by the null hypothesis.

If we drew all possible samples from a population, calculated the correlation coefficient for each of the samples, and constructed a line graph (showing the shape of the distribution) based on all of those sample correlation coefficients, what would we have?

Walt's directional alternative hypothesis was that male students would score better on the GRE verbal test than female students. This hypothesis would be written as:

"Significance testing" is another way of saying:

The first step in hypothesis testing is:

A Chi-square test is used for contingency tables to determine if there is a relationship between the categorical variables.

A one-way analysis of variance on two independent groups generally requires follow-up (i.e., post hoc) tests.

In hypothesis testing, the step that involves the comparison of the probability value to the significance level is: