Which option should you use if your data is skewed or has outliers?
Median and IQR
If your data is skewed or has outliers, you should use non-parametric tests or robust statistical methods. Non-parametric tests do not assume that the data comes from a specific distribution and can handle skewed or non-normal data. Some common non-parametric tests include the Wilcoxon rank-sum test, Kruskal-Wallis test, and the Mann-Whitney U test.
Robust statistical methods, on the other hand, are designed to be less sensitive to outliers and skewed data. These methods include trimmed means, Winsorization, and robust regression techniques. For instance, instead of using the mean to calculate a summary statistic, you might use the median, which is less sensitive to outliers.
Overall, the approach you use will depend on the specific nature of your data and your research question, and it’s always best to consult a statistical expert or consult your supervisor before making any decisions.
More Answers:
Understanding the implications of small standard deviation in data analysisMastering Standard Deviation: Understanding and Applying Statistical Measures for Data Analysis
Understanding the Mean in Statistics: A Guide to Calculating Central Tendency