⬅️Skewed distribution➡️
🔹Occurs due to outliers
🔹Outlier - Observation or value that is very distant from other observations in the distribution.
🔺Left skewed or negatively skewed
🔹If the outlier is smaller than other observations, causes left skewed or negatively skewed data.
🔹 For example
Marks scored by 5 students are
95, 94, 93, 94, 26
🔹In left skewed --> mean < median < mode
🔺Right skewed or positively skewed
🔹If outlier is higher than other observations, it causes right skewed data.
For examples :
The bilirubin levels of 5 patients are 1.1, 1.2, 1.1, 1.8 and 10
Here,
Mean > median > mode
🌟Most affected measure of central tendency --> mean
🌟Least affected measure of central tendency --> mode
🌟Most preffered measure of central tendency in asymmetrical distribution --> median
🌟In asymmetrical distribution
Mode = 3 median - 2 mean