Third Business Moment Decision
The third business moment decision refers to skewness - a measure of how asymmetric a data distribution is around its mean.
Symmetric Distribution
When data is evenly spread on both sides of the mean, the distribution is symmetric and skewness is close to zero - the classic bell-shaped curve is an example.
Positive (Right) Skew
The distribution has a longer tail on the right side, meaning a few unusually high values pull the mean above the median. Income data is a common real-world example.
Negative (Left) Skew
The distribution has a longer tail on the left side, meaning a few unusually low values pull the mean below the median. Exam scores on a very easy test, with most students scoring high and a few scoring very low, often show this pattern.
Calculating Skewness in Pandas
import pandas as pd
scores = pd.Series([85, 92, 78, 90, 20])
print(scores.skew()) # a negative value indicates left skew here
Coming Up Next
Next, you'll look at the fourth and final business moment decision - kurtosis, which describes how "peaked" or "flat" a distribution is.