The exercise on this page gives a normal linear regression model and asks for the distribution of the response at a fixed value of the explanatory variable.
Any estimator's standard error gives information about its accuracy. The exercise on this page gives the standard error of a least squares line's slope and asks for a roughly calculated interval that is likely to include the underlying model's slope. (T values are not required in this exercise.)
In the two exercises on this page, confidence intervals for a regression model's slope should be calculated from the least squares slope and its standard error. The second exercise is a little harder -- it asks for various confidence levels.
This exercise asks for the characteristics of a data set that will result in more accurate estimation of the linear model's slope.
This exercise gives the least squares slope and its standard error. The p-value for testing whether the regression slope is zero should be calculated and interpreted.