Test of Significance and Measures of Association

This set of flashcards covers the key concepts, hypotheses, and types of errors related to testing significance and measures of association in inferential statistics.

What is the primary purpose of testing hypotheses using inferential statistics?

To determine if a hypothesized relationship between an independent variable (IV) and a dependent variable (DV) exists.

What is the null hypothesis (H0) in the context of gender and voting behavior?

There is no relationship between gender and Democratic Party thermometer ratings.

What indicates statistical significance?

Statistical significance indicates whether the relationship between an IV and a DV truly exists or could have occurred by chance.

What is a Type I Error?

It occurs when one rejects the null hypothesis when it is actually true.

What is a Type II Error?

It occurs when one fails to reject the null hypothesis when it is actually false.

What threshold is typically set for rejecting the null hypothesis?

A minimum significance level of .05.

What does it mean if the likelihood of a random sampling error exceeds 5%?

We cannot reject the null hypothesis and cannot accept the alternative hypothesis.

What are confidence intervals in hypothesis testing?

Plausible limits of the means of populations, typically at a confidence level of 95%.

What does overlapping confidence intervals suggest?

It suggests that we cannot reject the null hypothesis.

What does a very small p-value indicate?

It indicates strong evidence against the null hypothesis, leading us to reject it.