Colored Words Experiment

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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.
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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

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Overall Quantitative Data
Mean 2.07962 Standard Dev. 1.45791 Min 0 Q1
1 Median 2 Q3 3 Max 6
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 (UF6) (LF-2), thus there are no outliers.
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• 1 sample T Interval on the true average of
  skittles
• Conditions
• Statement
• Formula
• Interval (a, b)
• Conclusion

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Quantitative Data by Gender
Male Mean- 2.07692 Standard Dev.- 1.45791 Min-
0 Q1- 1 Median- 2 Q3- 3 Max- 4
Female Mean- 2.10526 Standard Dev.- 1.6632 Min-
0 Q1- 1 Median- 2 Q3- 3 Max- 6
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.
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• 2 sample t test on male vs. female average
  skittles
• Conditions
• Statement
• Hypotheses Ho µF µM Ha µF ? µM
• Test statistic
• P-value
• Conclusion
• If reject, complete a confidence interval

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Quantitative Data by Candy Consumption
SUMMARY STATS NEEDED FOR EACH VALUE OF THE
VARIABLE
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Quantitative Data by Candy Consumption
(frequently, sometimes, or never)
We chose to compare Candy Consumption to the data
results to see if there was an association
between people who ate Candy Frequently,
Sometimes, or Never with the number of Skittles
they correctly identified.

• Our categorical variable that worked best with
  the data was if the subject ate candy on a
  regular basis (Frequently). The Frequently
  variable was more consistent overall than the
  Sometimes and Never variables
• Frequently had a median at 3.5 skittles, which
  was the highest. Next was Sometimes with a
  median of 2 skittles, And never was the lowest
  with a median of ½ skittles.
• The Sometimes variable had the largest range from
  (0,6) making it the most inconsistent, where as,
  the Never variable had a range from (0,1) and the
  Frequently variable had a range of (2, 5). The
  IQR of Frequently was
• The shape of frequently was ..

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• X2 GOF test on type of Candy Consumption
• NEVER SOMETIMES FREQ
• OBS 10 28 30
• EXP (uniform)
• Conditions
• Statement
• Hypotheses
• Test Statistic
• P-Value
• Conclusion

• NOTE
• If your categorical variable only has 2 values,
  instead of doing a Chi-Square GOF test, complete
  a 1 prop Z test to see if the of one of the
  values is 50

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Simple Two-Way Table of Categorical Data
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Marginal Distribution for Gender
Male 52.5 Female 47.5
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Marginal Distribution for Candy Preference
Chocolate 50 Sweet 50
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  C S
F 57.89 42.11
M 42.86 57.14

• SEGMENTED BAR GRAPH

List the in each category Of the females C
57.89 S 42.11 Of the males C 42.86 S
57.14
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• X2 Test for Association
• Observed Table Expected Table
• Conditions
• Statement
• Hypotheses
• Test Statistic
• P-value
• Conclusion

(made in Excel copied in)
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Sources of Error and Bias
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Conclusion

• Make a conclusion about each of the
  tests/intervals you did
• Make a conclusion about each graph you made

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EYEWEAR
Glasses/Contacts None total
GENDER M 12 18 30
F 18 23 41
total 30 41 71