Mann-whitney U test? math n00b?

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In summary, the person is trying to use the Mann-Whitney U test to determine the significance of data on motor performance in rats exposed to different substances. However, there is concern about the test not taking into account the individual variations within each group, particularly with one outlier rat. There may also be issues with using a large number of trials for the outlier rat, as it may not be independent and could potentially bias the results. It is recommended to use the mean result of each rat instead of individual trials, but this may result in a small sample size. It is important to decide on statistical tests before conducting experiments to avoid bias in the analysis.
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mann-whitney U test? please help math n00b?

I am trying to test the difference in motor performance (measured by the amount of time each rat is able to keep running on a moving beam) between two groups of rats (those with early exposure to a common antidepressant and those with early exposure to Saline as control) in SPSS. There are three rats in each group and over a hundred entries for each of the six rats. I feel that the Mann-Whitney U test is most appropriate to determine the significance of my data. The problem is that I do not think that this takes into account the measures for each particular rat. One of these rats is an ENORMOUS outlier, big enough that it may make the entire group look significantly different if the program does not differentiate between rats within a group and only looks at all the times for each group as a whole. I understand that non-parametric tests are suited to deal with huge variation within a group but my concern is whether or not the mann-whitney U test is suited to deal with consistently large variation coming from one or two samples with hundreds of entries.
 
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I could interpret your remarks to mean that you are considering using the result of each of the hundreds of trials as your sample, so the statistic would be computed on the basis of ranking them all. That doesn't sound right, since the trials aren't independent if you believe that the ones that come from the outlier rat tend to be different that the trials from the other rats. It's more convincing to use the mean result of each rat, but that only gives you 6 things to rank, which might not be enough of a sample to impress anybody.

If each rat did the test hundreds of times, did they get better with practice?

In scientific investigations, the statistics that are to be used should be decided upon before the experiments are conducted. Otherwise, the investigator is liable to "cherry pick" the statistical tests that are used in order to make the analysis swing one way or the other.
 
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FAQ: Mann-whitney U test? math n00b?

What is a Mann-Whitney U test?

A Mann-Whitney U test is a nonparametric statistical test used to compare two independent groups of data. It is often used to determine if there is a difference between the medians of the two groups.

When should a Mann-Whitney U test be used?

A Mann-Whitney U test should be used when the data does not meet the assumptions of a parametric test, such as the t-test. This includes when the data is not normally distributed or when the sample sizes are small.

How is a Mann-Whitney U test calculated?

A Mann-Whitney U test is calculated by assigning ranks to the data in each group, combining the ranks from both groups, and then comparing the sum of ranks between the two groups. The test statistic is then compared to a critical value to determine significance.

What is the difference between a Mann-Whitney U test and a Wilcoxon rank-sum test?

A Mann-Whitney U test and a Wilcoxon rank-sum test are essentially the same test, but have different names due to historical reasons. The main difference is that the Mann-Whitney U test is used when the sample sizes for each group are unequal, while the Wilcoxon rank-sum test is used when the sample sizes are equal.

Can a Mann-Whitney U test be used for dependent samples?

No, a Mann-Whitney U test is only appropriate for independent samples. If the data is paired or related in some way, a different test, such as the Wilcoxon signed-rank test, should be used.

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