Inferential Statistics for b and r
This section starts with assumptions on the errors that are necessary for statistical inference. Then, it gives an example of a significance test for the slope. Finally, it talks about constructing confidence intervals for the slope and closes with a significance test for the correlation.
Question 1 out of 4.
Which of the following are assumptions made in the calculation of regression inferential statistics?
The errors of prediction are normally distributed.
X is normally distributed.
Y is normally distributed.
The variance around the regression line is the same for all values of X.
The relationship between X and Y is linear.
Question 2 out of 4.
The slope of a regression line is 0.8, and the standard error of the slope is 0.3. The sample used to compute this regression line consisted of 12 participants. Compute the 95% confidence interval for the slope. Type the upper limit of the confidence interval in the box below.
Question 3 out of 4.
In a sample of 20, the correlation between two variables is .5. Determine if this correlation is significant at the .05 level by calculating the t value.
Question 4 out of 4.
Calculate the lower limit of the 95% confidence interval for the correlation of .75 (N = 25).