mean and average

μ = 1/n ∑x[i]

• The “mean” of a sample is the summary statistic computed with the previous formula.

• An “average” is one of many summary statistics you might choose to describe the typical value or the central tendency of a sample.

mean and variance

σ² = 1/n ∑(x[i] − μ)²

• The mean is intended to describe the central tendency.

• The variance is intended to describe the spread.

probability distribution and representation

matplotlib.pyplot plotting

histogram

hist = {}
for x in t:
    hist[x] = hist.get(x, 0) + 1

probability mass function

n = float(len(t))
pmf = {}
for x, freq in hist.items():
    pmf[x] = freq / n

outliers

trim the data by discarding some fraction of the highest and lowest values

relative risk

conditional probability

reporting results

The answer might depend on who is asking the question.