Are the Parameter Estimates Statistically Significant?
Measuring an entire population is often impossible. Quite often, we must measure a sample of the population and generalize our findings to the population. When we take an average or standard deviation of a data set that is a subset of the population, our values are estimates of the actual parameters for the population’s true average and standard deviation. These are subject to sampling error. Likewise, when we perform regression analysis on a sample of the population, our coefficients (a and b) are also subject to sampling error. Whenever we estimate population parameters (the population’s true α and β), we are frequently concerned that they might actually have values of zero. Even though we have derived values a=$9636.36 and b=$479.02, we want to perform a statistical significance test to make sure their distance from zero is meaningful and not due to sampling error. Recall from the May 25 blog post, Using Statistics to Evaluate a Promotion, that in order to do significance testing, w
