7. Explain why the statistical significance of a correlation is important. That is, what must be
assumed when the correlation is found to not be statistically significant?
The null hypothesis for a correlation states that the population correlation coefficient is
8. Describe the connection between a correlation and a bivariate regression analysis. In your
discussion, specifically note: (1) statistical significance, (2) sign, and (3) use or application.
A bivariate regression means there are only two variables involved. The correlation
coefficient is based on a straight line relationship, meaning a linear regression of two
variables. A statistically significant correlation indicates that there is a linear (bivariate
9. Relate how a bivariate regression analysis can be used to predict the dependent variable. In
your answer, identify the independent and dependent variables, intercept, and slope. Also,
give an example of how the prediction should be accomplished.
The dependent variable, y, is predicted by the equation y = a + bx where a is the intercept and
95% Confidence Interval for a
predicted y value using a
10. When a regression analysis is performed, what assures the researcher that the resulting