Distributions

It is hard to compare distributions, so we use summary statistics to simplify the task and compare the data with each other.

4 ways to characterize the distribution
1) Central Tendency
1) Arithmetic Average
2) Median (Divides the sample of data in half)
3) Most frequently observed value
2) Dispersion from center (What is the average departure from the centre)
1) Range of deviation
2) Mean absolute deviation. (Average distance from the mean)
3) Variance: Average squared distance from the mean
3) Symmetry
1)Skewness: - am i more likely to see more observations above the mean or below the mean.
4) Pointiness: Kurtosis: Does my tail look fat to you. Relative measure of the pointedness of the distribution and tails. More kurtosis means that we can expect more extreme observations than we do in the normal distribution.

Real worlds is negative skewed and excess kurtosis
These summary statistics help us get the shape and the location of the distribution