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Inferential Statistics, please help

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For my Psychology IA, I conducted a study in which I told participants to read out loud a list of words, the words were color names printed in black (this is condition one) and wrote down the time they took to complete the task. Then, I gave them another list of words, but printed in colors different than what their names pronounced (for example: red, green, blue), this was condition two.

There are no control groups or experimental groups since every participant went through both conditions. However, I'm having trouble in the inferential statistics criteria for my paper. I don't know what test to use. Please help.

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Your teacher should explain to you that this is a within subjects design, also called a repeated measures design. Your data are interval/ratio since they are times and have an absolute 0 (meaning 0 actually means no time taken). You can use a related t-test for your data to get the p-value.

If you have a small sample size you can use the Wilcoxon t-test, even though it is a non-parametric test (for ordinal data like rating the attractiveness of a person out of 10), it can be more robust for small sample sizes with interval/ratio data.

You can justify the use of either test, there are online calculators that will return the right values.

Remember to report the mean and standard deviation when making your tables and graphs and the p value from the inferential test.


Good luck!

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There is not much to explain, the repeated measures t-test examines the variance between the means between the first trial and the second trial and looks up the value it returns in a table to calculate the probability the results occurred from chance. If the p value is small enough you conclude the results did not occur from chance and instead from the treatment manipulation you used in your experiment.

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Tails refer to the direction of the hypothesis. When you have clear theoretical reasons to predict one condition will be greater than another then you use a one-tailed test. When you have no theoretical grounds and just assume there will be a difference then you use a two-tailed test.

http://www.ats.ucla.edu/stat/mult_pkg/faq/general/tail_tests.htm

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It has been a while since I did it manually but that sounds right, if t is higher than critical value then the null hypothesis is rejected (for some statistical tests the critical value needs to be less than).

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