This work is done by Adrian Liaw
In a Stroop task, participants are presented with a list of words, with each word displayed in a color of ink. The participant’s task is to say out loud the color of the ink in which the word is printed. The task has two conditions: a congruent words condition, and an incongruent words condition. In the congruent words condition, the words being displayed are color words whose names match the colors in which they are printed: for example RED, BLUE. In the incongruent words condition, the words displayed are color words whose names do not match the colors in which they are printed: for example PURPLE, ORANGE. In each case, we measure the time it takes to name the ink colors in equally-sized lists. Each participant will go through and record a time from each condition.
Independent variable: condition of the task
Dependent variable: time to complete the task
In this case, we want to see if it takes longer to complete the task in the incongruent words condition.
Null hypothesis: It takes the same time to complete the task in both conditions.
Alternative hypothesis: It takes longer to complete the task in the incongruent words condition.
(Where $\mu_{cong.}$ stands for the population mean of the results in congruent words condition, $\mu_{incong.}$ for incongruent words condition)
We don't know the population parameters, so I choose to use a t-test to infer the population.
This data set is a within-subject design, which two samples are paired (two conditions), so I'll perform a paired samples t-test.
$M$ | $SD$ | |
---|---|---|
congruent words | 14.05 | 3.56 |
incongruent words | 22.02 | 4.80 |
diff. (incong. - cong.) | 7.96 | 4.86 |
We can see the distribution of the incongruent one is more to the right than the congruent one.
The result says, it takes significantly longer time to complete the task in the incongruent condition than in the congruent condition, and that's what we're expecting.
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