• Provides a reasonable estimate of an unknown population parameter.
• These estimates are calculated using a random sample of the population.

• Sample Mean(\(\overline{x}\)) = \(\frac{\sum_{i=1}^{n} x_{i}}{n}\)
• Sample Variance(\(s^2\)) = \(\frac{\sum_{i=1}^{n} (x_{i}-\overline{x})^2}{n-1}\)
• Sample Standard Deviation(\(s\)) = \(\sqrt\frac{\sum_{i=1}^{n} (x_{i}-\overline{x})^2}{n-1}\)

• A sample of people aged 18 and their insurance cost

• Code to calculate point estimates for mean, variance, and standard deviation in R

len = length(sample$charges)
charges = round(sample$charges)
sample_mean = mean(charges)
sample_variance = var(charges)
sample_standard_deviation = sd(charges)

• Sample Mean(\(\overline{x}\)) = \(\frac{1726+1137+2198+3393+2211+34303}{6}\) = \(7494.6666667\)
• Sample Variance(\(s^2\)) = \(\frac{33281361+40424164+28058209+16826404+27920656+718668864}{5}\) = \(173035931.466667\)
• Sample Standard Deviation(\(s\)) = \(\sqrt\frac{33281361+40424164+28058209+16826404+27920656+718668864}{5}\) = \(13154.3122765\)

• A sample of people aged 60 and their insurance cost

• Sample Mean(\(\overline{x}\)) = \(\frac{1726+1137+2198+3393+2211+34303}{6}\) = \(25738.8103925\)
• Sample Variance(\(s^2\)) = \(\frac{576624169+605258404+554178681+499343716+553566784+73342096}{5}\) = \(280597266.64144\)
• Sample Standard Deviation(\(s\)) = \(\sqrt\frac{576624169+605258404+554178681+499343716+553566784+73342096}{5}\) = \(16751.037778\)