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2. 2 * Introduction & Thoughts Behind The Experiment - We wanted to chose an experiment that was easy to complete, organized, and some what entertaining. - Our original hypothesis, was that people who ate more Candy on a Regular Basis and had a stronger preference for Sweets rather than Chocolate would have more success and be able to correctly identify more skittles in one minute than those who do not.

3. 3 The Task * 40 Subjects * Objective: * How many Skittles can the Subject identify in one minute based solely on their Taste Buds * Categorical Factors: * Gender * Male or Female * Candy Consumption * Frequent, Sometimes, Never * Candy Preference * Chocolate or Sweet * Hair Color

4. 4 * Overall Quantitative Data The Data is right skewed and unimodal. The center is at the median of 2 skittles with an IQR of 2 skittles as well. The range was (0, 6) skittles. All data points are within the Upper & Lower Fence (UF=6) (LF=-2), thus there are no outliers. BOXPLOT

5. 5 SUMMARY STATS: Mean: 2.07962 Standard Dev.: 1.45791 Min: 0 Q1: 1 Median: 2 Q3: 3 Max: 6 NORMAL PROBABILITY PLOT Description of plot, conclusion on the normality of the data OUTLIER TEST:

6. 1 sample T Interval on the true average # of skittles Conditions Statement Formula (df!) Interval (a, b) Conclusion 6

7. 7 * Quantitative Data by Gender Female: Mean- 2.10526 Standard Dev.- 1.6632 Min- 0 Q1- 1 Median- 2 Q3- 3 Max- 6 Male: Mean- 2.07692 Standard Dev.- 1.45791 Min- 0 Q1- 1 Median- 2 Q3- 3 Max- 4

8. * OUTLIER TEST ON EACH GENDER 8 The plots of our data broken down by gender shows that the both females and males had the same median at 2 skittles. The range for females was larger, which was (0,6) skittles, compared to the males which was (0,4) skittles. However they both had an IQR of 2 skittles. Finally, the males’ data appears to be more symmetrical, while the females’ data is clearly right skewed. Both are unimodal when we look at histograms of the data.

9. 2 sample t test on male vs. female average skittles Conditions Statement Hypotheses:Ho: µF = µMHa: µF ≠ µM Test statistic P-value (df!) Conclusion If reject, complete a confidence interval 9

10. 10 * Quantitative Data by Categorical Variable (with only 2 values) Summary stats for Value 1 Summary stats for value 2 Parallel Boxplots

11. * OUTLIER TEST ON EACH VALUE 11 DESCRIPTION/COMPARISON OF EACH VALUE

12. 2 sample t test on value 1vs. value2 average skittles Conditions Statement Hypotheses:Ho: µ1 = µ2Ha: µ1 ≠ µ2 Test statistic P-value (df!) Conclusion If reject, complete a confidence interval 12

13. 13 * Quantitative Data by Candy Consumption Sometimes, Never, Frequently neversometimesfrequently 152010 neversometimesfrequently 33.3% 44.4%22.2%

14. 14 General conclusion about distribution of the variable

15. X 2 GOF test on type of Candy Consumption Conditions Statement Hypotheses Test Statistic P-Value (df) Conclusion 15 neversometimesfrequently observed152010 expected(uniform)

16. 16 * Distribution for Gender Male: 52.5 % Female: 47.5%

17. 17 * Simple Two-Way Table of Categorical Data neversometimesfrequentlytotal male812525 female78520 total15201045

18. * SEGMENTED BAR GRAPH 18 List the % in each category: Of the males… F = ___% S = ____% N = ____% Of the females… F = ___% S = ____% N = ____%

19. * X2 Test for Association * Observed Table:Expected Table * Conditions * Statement * Hypotheses * Test Statistic * P-value (df) * Conclusion 19 (made in Excel & copied in) neversometimesfrequently male8125 female785

20. * Candy preference (chocolate or sweet) 20 ChocolateSweet 2030 ChocolateSweet 40%60%

21. * 1 prop Z interval (for the true percent of one value of your categorical variable) p-hat = percent of people who like chocolate = 20/50 = 40% * Conditions * Statement * Formula (df) * Interval (a, b) * Conclusion 21

22. Percents of each value: Of the males: C = _____% S = _____% Of the females: C = ____% S = ____% 22 ChocolateSweet male1214 female816

23. * X2 Test for Association * Observed Table:Expected Table * Conditions * Statement * Hypotheses * Test Statistic * P-value * Conclusion 23 (made in Excel & copied in) ChocolateSweet male1214 female816

24. 24 * Sources of Error and Bias

25. 25 * Conclusion * Make a conclusion about each of the tests/intervals you did * Make a conclusion about each graph you made

26. * 26 EYEWEAR Glasses/ContactsNonetotal GENDERM121830 F182341 total304171