Obesity dataset mathematical statistics:
From the statistics we can observe that:
1: The median value is 18.3, indicating that approximately half of the data points fall below this value, and half fall above it.
2: The mean is very close to the median (18.3), indicating that the data distribution is approximately symmetric.
3: A standard deviation of 1.0369 indicates that the data values are relatively close to the mean, with low variability.
4: A negative skewness value (-2.6851) indicates that the data distribution is strongly negatively skewed (left-skewed), with a tail extending to the left. This suggests that most of the data points are concentrated on the right side of the distribution, toward lower values.
5: A kurtosis value of 12.3225 suggests that the data distribution has very heavy tails compared to a normal distribution (very leptokurtic). This indicates a high likelihood of extreme values compared to a normal distribution.
The obesity dataset statistics describe a strong negative skewness (left-skewed) and very heavy tails. The mean is close to the median, suggesting approximate symmetry, but the strong negative skewness and high kurtosis indicate that the data distribution has a significant concentration of values on the right side with the potential for extreme values on the left side.