In speaking with a friend, Lauren, you learn that she is performing community service by analyzing the attitude data collected on behalf of a not-for-profit organization. Lauren tells you, “I’m just going to run the analyses and find the most statistically significant results and base my recommendations off of that. After all, the more statistically significant the result, the bigger the difference in attitudes.”

What do you think of Lauren’s data analysis strategy? Should she ignore all non–statistically significant results? Why or why not? Is her assumption regarding the degree of statistical significance and the size of the attitude difference correct? What factors influence the ease with which statistical differences are found in a sample?