Contents
Can you use t-test with outliers?
For the t-test on independent samples, the data in each sample must be normal or at least reasonably symmetric and that the presence of outliers does not distort either of these results.
How do t tests deal with outliers?
If the outlier in question is: A measurement error or data entry error, correct the error if possible. If you can’t fix it, remove that observation because you know it’s incorrect. Not a part of the population you are studying (i.e., unusual properties or conditions), you can legitimately remove the outlier.
Is t-test sensitive to outliers?
Outliers are anomalous values in the data. The one-sample t statistic is based on the sample mean and the sample variance of the sample values, both of which are sensitive to outliers. (In other words, neither the sample mean nor the sample variance is resistant to outliers, and thus, neither is the t statistic.)
Can you do a two sample t-test with non normal?
For a t-test to be valid on a sample of smaller size, the population distribution would have to be approximately normal. The t-test is invalid for small samples from non-normal distributions, but it is valid for large samples from non-normal distributions.
Do outliers affect P value?
2, with three outlier samples or less, power increases as effect size increases in the distribution-based p-value, the outlier robust t-statistic, and the outlier sum approaches, but not in the other two approaches for both normal and t-distributions. The distribution-based p-value approach performs best in most cases.
Can I use t-test for skewed data?
For studies with a large sample size, t-tests and their corresponding confidence intervals can and should be used even for heavily skewed data.
How to detect outliers in an independent t-test?
Fortunately, when using SPSS Statistics to run an independent t-test on your data, you can easily detect possible outliers. In our enhanced independent t-test guide, we: (a) show you how to detect outliers using SPSS Statistics; and (b) discuss some of the options you have in order to deal with outliers.
How is an independent t test used in statistics?
The independent-samples t-test (or independent t-test, for short) compares the means between two unrelated groups on the same continuous, dependent variable.
When to use paired samples instead of independent t test?
This is more of a study design issue than something you can test for, but it is an important assumption of the independent t-test. If your study fails this assumption, you will need to use another statistical test instead of the independent t-test (e.g., a paired-samples t-test).
When do you not need a t test?
If you think your data has, or could have, very large outliers, a t-test will not be appropriate no matter how many samples you take. Let’s look at an example: