Regression

I really liked working through some sample data sets with R on Tuesday. It helped me learned how varying some of the terms could change the coefficent of determination and the p-value. Here is the summary of what I learned:
Regression is used for two continuous variables (both independent and dependent). A regression assumes that there is a cause and effect relationship between x and y. Also, this technique asumes that the x variable is measured without error (can this be done?!?) As far as a linear relationship between two variables, the null hypothesis proposes that there is none and that the slope is 0. The alternative hypothesis depends on slope. Also, the slope, the coefficient of variation, and the sample size all affect the p-value. Remember the p-value is the probability that the slope of the line equals zero and that there is no relationship between variables (null hypothesis).