1. Energy Drinks!

2. By: Michael Williams, Erica Lee, Erica Kim, and Davis Song

3. Goal or Purpose Our goal is to see if there is a correlation between the sex of Castro Valley High School seniors and whether they like energy drinks or not.

4. Experimental Design -Experiment to provide evidence if there’s a difference in proportions between senior boys and girls who prefer energy drinks -Past experience- -Older students prefer energy drinks than younger students -Male students prefer energy drinks more than female students

5. Process - Created a poll and distributed it randomly to all seniors in the classes we visited - Polled only seniors at CVHS in 7 th period - Ensured that no student was polled twice

6. FORM Gender (circle one) Male Female Preferred Beverage (circle one) CoffeeJuice Energy DrinkSoda WaterTea

7. Process Continued… -To determine whether the subjects preferred energy drinks we listed “energy drinks” among other beverages rather than asking if they like energy drinks or not -7 th period classes- example: Government and Economics classes to ensure mostly seniors -If juniors were present, they did not receive a form

8. Process Continued… -Most students filled out forms correctly -Collected 117 forms -1 filled out incorrectly -1 filled out incorrectly -2 wrote their own drinks (“tea” and “milk”) because 1 st preferred not present -2 wrote their own drinks (“tea” and “milk”) because 1 st preferred not present

9. Errors in Process -We had to randomly select 55 forms out of our 117, because our population was too small and our sample size was too big. -To do so, we used the random numbers chart

10. Bias -Not a true SRS, not all seniors had an equal chance of being chosen *Not all seniors have a 7 th

11. Data MaleFemale Coffee14 Energy Drink 125 Water58 Juice46 Soda42 Tea01 Milk10 Total2728 Proportion of Seniors Who prefer Energy Drink: Male=.4444 Female=.1786

16. 2-Prop Z Test H 0 : p 1 = p 2 where p1 = proportion of male seniors at Castro Valley High who prefer energy drinks H A : p 1 > p 2 and p2 = proportion of female seniors at Castro Valley High who prefer energy drinks z test =-2.5036, p-value=.0123 Reject H 0 if p-value < α

17. Calculations for percentages

18. Conditions All are 5 or larger, we are safe using a 2-sample z-procedure

19. Conditions -The population is at least 10 times as large as the sample. Castro Valley’s senior population is 554, and our sample size is 55. (55)(10)=550 554 > 550 seniors at CVHS

20. Z-test statistic

21. Analysis We reject H 0 at the 5% level (p=.01646). We reject H 0 at the 5% level (p=.01646). If we do in fact reject H 0,then the proportion of male seniors at CVHS prefer energy drinks over the proportion of female seniors at CVHS. If we do in fact reject H 0,then the proportion of male seniors at CVHS prefer energy drinks over the proportion of female seniors at CVHS.

22. 2-prop Z Int.Conditions All are 5 or larger, therefore we are safe using a 2-proportion z interval.

23. 95% Confidence Interval Confidence interval: (.0308,.5009)

24. Analysis  We are 95% confident that the true mean proportion(Proportion of males who prefer energy drinks- Proportion of females who prefer energy drinks) is between.0308 and.5009.

25. Conclusion  Our experiment to decide whether or not male seniors at CVHS prefer energy drinks more than female seniors at CVHS seemed to confirm that a larger proportion or male seniors prefer energy drinks than female seniors

26. Conclusion Significance Test  Significant at 5% level  Rejected hypothesis that the two proportions are equal

27. Conclusion Confidence Interval -Male proportion likely to be larger because the left tail of the distribution not covered by the interval (2.5%) is still over zero meaning the male proportion would still be larger than the female proportion. The right tail would still mean a larger male proportion -This coincides with the significance results of.0165

28. Final Conclusion -We feel the survey we created, distributed, and analyzed shows a greater male proportion of seniors over female who prefer energy drinks. -Data could be used for marketing. *More male oriented energy drinks *More male oriented energy drinks