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Colored Words Experiment/ Stroop Effect

By: Tyler Lipshutz & Sarah Hadyniak. Colored Words Experiment/ Stroop Effect. About Stroop Effect. Named after John Ridley Stroop The Stroop effect refers to the fact that naming the color of the first set of words is easier and quicker than the second.

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Colored Words Experiment/ Stroop Effect

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  1. By: Tyler Lipshutz & Sarah Hadyniak Colored Words Experiment/ Stroop Effect

  2. About Stroop Effect • Named after John Ridley Stroop • The Stroop effect refers to the fact that naming the color of the first set of words is easier and quicker than the second. • Stimuli 1:Purple Brown Red Blue Green • Stimuli 2:PurpleBrownGreenBlueGreen • Stimuli 3: ▀ ▀ ▀ ▀ ▀ ▀ ▀ ▀ ▀ ▀▀ ▀ ▀ ▀ ▀▀ ▀ ▀ ▀ ▀▀ ▀ ▀ ▀ ▀

  3. The Task • 39 Subjects • How many correct colors can the subject identify in 60 seconds or until a wrong color is spoken • Read from up to 3 sheets of colors generated randomly • Categorical Factors: • Gender • Male/Female • Vision • Contacts or Glasses/None • Art/Music Class 2+ MPs at South • Yes/No • Answered Wrong or Time Ran Out

  4. Why we choose this “challenge” • Art and Music are affiliated with right brain characteristics • This test can be an indication if some people are more right- or left-brained • Entertaining to watch people suffer through the task

  5. Overall Quantitative Data Data is slightly left skewed with two peaks around 30 and 45. There is a possible outlier at 91. The center is at 52.1538 with a standard deviation 16.2813. The range was 68.

  6. Data and the Normal Model Shown from the normal probability plot, the data shows that the association is linear; yet, it seems to have curves which would indicate that the data is not linear and a better model would fit our results.

  7. Quantitative Data by Gender The plots of our data broken down by gender shows that the mean result for females was 54.8261, higher than the mean result for males at 48.3125. The range for females was larger at 68 than the male’s 46. The female’s data appears to be more symmetrical, while the male’s data looks to be skewed left.

  8. Quantitative Data by Art/Music Class • Our categorical variable that worked best with the data was if the subject took two or more marking periods of an art or music at South. Eyewear, having either glasses, contacts or nothing, had little to no effect on the data and was not important to pursue. Saying the wrong color or time running out also showed little difference. We chose to compare classes taken at South to data results to see if there is an association between people who took two or more marking periods of an art or music at south with the number of colors they identified.

  9. Quantitative Data by Art/Music Class The comparison shows that the center for students who had taken art and music classes was 54.667, higher than the center for students who had not taken an art or music, which was 48.1333. The range for the art/music students was larger at 68 than for the non-art/music at 44. The standard deviation was larger for the art/music at 24 than the 15 for the non-art/music. The shape for the art/music was apparently symmetric while for the non-art/music, it appeared to be left skewed.

  10. Quantitative Data by Partner SH = Sarah Hadyniak TL = Tyler Lipshutz Tyler’s results were symmetric, while Sarah’s results were left skewed. Sarah had 25 subjects, while Tyler had 14. The centers were similar, with Tyler’s at 57.1429 and Sarah’s at 49.36. Tyler’s minimum was close to Sarah’s Q1. The spread of the two was 50 for Sarah and 58 for Tyler, so the spread of the data sets were similar.

  11. Simple two-way table of Categorical Data More females completed the experiment than did males, additionally, more females participated in art or music at South than males did.

  12. Marginal Distribution for Gender Females = 23/39 58.974% Males = 16/39 41.026%

  13. Marginal Distribution for Classes Yes (Taken two or more marking periods of Art/Music at South) 24/39 = 61.538% No (Less than one marking period of Art/Music at South) = 15/39 = 38.462%

  14. Condition Distribution Our two-way table between gender and classes shows that out of all females, 34.7826% have not taken two or more marking periods of art/music at South, while 65.217% of females have taken two or more marking periods of art/music at South.

  15. Conditional Distribution Our two-way table between gender and classes shows that out of all the females, 53.333% have not taken two or more marking periods of art/music, while out of all males, 46.6667% have not taken two or more marking periods of art/music.

  16. Test for Independence We preformed a Chi-Squared test for Independence between our variables of gender and classes taken at South. We got a p-value of 0.57, which proves that we fail to reject our null hypothesis at the 0.05 level and that the two values are independent. Therefore, gender and classes taken are independent variables.

  17. Sources of Error and Bias • Sources of error were how some individuals were confusing red, orange, pink and purple. • Another source of error would be the difference between people who messed up and people who ran out of time • Sources of bias include individuals who have seen or read color charts before and are familiar with how they work. • Also, if subjects overheard previous experiments, they may be more prepared than others.

  18. Conclusion • Our findings ultimately showed that women, on average, are able to correctly identify more colors than men, and students who have taken more art or music classes are also able to do better on a stroop test. • If we were to re-do the experiment, we would possibly block results between people who messed up and stopped reading and people who ran out of time for more accurate results.

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