Gambling in public high schools. With the rapid growth in legalized gambling in the United States, there is concern that the involvement of youth in gambling activities is also increasing. University of Minnesota Professor Randy Stinchfield compared the rates of gambling among Minnesota public school students between 1992 and 1998 (Journal of Gambling Studies, Winter 2001). Based on survey data, the table (next column) shows the percentages of ninth-grade boys who gambled weekly or daily on any game (e.g., cards, sports betting, lotteries) for the 2 years.
a. Are the percentages of ninth-grade boys who gambled weekly or daily on any game in 1992 and 1998 significantly different? (Use α = .01.)
b. Professor Stinchfield states that “because of the large sample sizes, even small differences may achieve statistical significance, so interpretations of the differences should include a judgment regarding the magnitude of the difference and its public health significance.” Do you agree with this statement? If not, why not? If so, obtain a measure of the magnitude of the difference between 1992 and 1998 and attach a measure of reliability to the difference.
a. Suppose you want to make an inference about the difference between the mean salaries of male and female accounting/finance/banking professionals at a 95% level of confidence. Why is this impossible to do using the information in the table?
b. Give values of the missing standard deviations that would lead you to conclude that the mean salary for males is significantly higher than the mean salary for females at a 95% level of confidence.
c. In your opinion, are the sample standard deviations, part b, reasonable values for the salary data? Explain.
d. How does the data-collection method impact any inferences derived from the data?
Data Analysis and Politics “For today’s August 31, 2016 First Class graduate, one word: STATISTICS”-NYT A New Paradigm Today we learned about the importance of the course (cause obviously it wouldn’t be required if it weren’t important)! Some key points: 1. Using data analysis has become HUGE in he world today because there is more “big data” available from the government, non-proﬁts, and citizens via social media. “Big data” meaning professions, hobbies, ages, genders, political preferences, social commonalities.