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Sneaky Sneakers By: Blake Smith Jesse Lee Jen Feder
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Study Description We did two different studies with shoes: The first was to test for association between gender and type of shoe. The second was testing the observed frequency distribution of sneaker style compared to the expected frequency distribution.
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Test for Association To gather data for these tests we compiled a list of various shoe types: Sneakers/Flip Flops/ Moccasins/ Boots/Clogs/Dress/Other …and recorded the number of people wearing each type of shoe.
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Test for Association We recorded 30 males and 30 females from each lunch to total 120 males and 120 females. To make it random we only surveyed every 5 th student, so it was systematic.
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Test For Association: Work SneakersFlip-FlopsMoccasinsBootsClogsDressOther Male6030410 15 Female2061649713 StateCheck 2 Ind. SRSSystematic All Exp. Counts ≥ 5 No, but we’ll still continue
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Test For Association: Work Ho: There is no association between gender and type of shoe. Ha: There is an association between gender and type of shoe. df = (rows – 1) x (columns – 1) = (2-1) x (7-1) = 6
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Test For Association: Work Conclusion: We reject our Ho because p-value < = 0.05. We have sufficient evidence that there is an association between gender and type of shoe.
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Shoe Preference - Percentages
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Male vs. Female Shoe Preference
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Goodness Of Fit: Test 1 To gather our data we used a systematic sample of every 5 th male exiting the cafeteria We tallied the number of males wearing each brand of sneaker: Nike / Adidas / New Balance / Asics Etnies / Vans / Other
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G.O.F. Test 1 Ho: The observed frequency distribution of sneaker brand preference of males fits the expected distribution Ha: The observed frequency distribution of sneaker brand preference of males does not fit the expected distribution The expected distribution was 17.143
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G.O.F. Test 1 Continued MALE SNEAKERS Nike35 Adidas24 New Balance9 Asics5 Etnies9 Vans16 Other22 StateCheck SRSSystematic All Expected Counts ≥ 5 17.143
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G.O.F. Test 1 Continued df: 6
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G.O.F. Test 1 Continued Conclusion: We reject our Ho because the p-value is < =.05. We have sufficient evidence that observed frequency distribution of sneaker brand preference of males does not fit the expected distribution.
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Goodness Of Fit: Test 2 To gather our data we used a systematic sample of every 5 th female exiting the cafeteria We tallied the number of females wearing each brand of sneaker: Nike / Adidas / New Balance / Asics Etnies / Vans / Other
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G.O.F. Test 2 Ho: The observed frequency distribution of sneaker brand preference of females fits the expected distribution Ha: The observed frequency distribution of sneaker brand preference of females does not fit the expected distribution The expected distribution was 17.143
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G.O.F. Test 2 Continued FEMALE SNEAKERS Nike19 Adidas22 New Balance19 Asics15 Etnies18 Vans10 Other17 StateCheck SRSSystematic All Expected Counts ≥ 5 17.143
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G.O.F. Test 2 Continued df: 6
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G.O.F. Test 2 Continued Conclusion: We fail to reject our Ho because our calculated p-value is > =.05. We have sufficient evidence that the observed frequency distribution of sneaker brand preference among females fits the expected distribution
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Male Sneaker Preference
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Female Sneaker Preference
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Male vs. Female Sneaker Preference
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Personal Conclusions: Association Our test showed that there was an association between gender and shoe type. We believe this is because certain shoe types are more socially acceptable for females to wear as opposed to males, and vice-versa.
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Personal Conclusions: Goodness of Fit Goodness of Fit females: The observed frequency distribution fits the expected Goodness of Fit males: The observed frequency distribution does not fit the expected
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Personal Conclusions: G.O.F. We feel that males prefer the major name brand sneaks (Nike, Adidas) due to the influence of pop culture Male athlete endorsements Football Baseball Soccer
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Personal Conclusions: G.O.F. Females tended to be more evenly distributed in their choice of sneaker, therefore fitting the expected distribution We accredit this to the lack of major female endorsement among sneaker brands
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Application We found that it was simple to collect the data because the students were so concentrated as they exited the cafeteria. It was difficult to sample every 5 th person, but not impossible. We were not surprised by our results.
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Sources of Error Seasons Involuntary Human Error Sample Method: Not technically random Not everyone goes to lunch People in more than one lunch D-Lunch-Early Release Gym Hallway Gym Classes
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