In civil
Understanding conditional probability, independent events, and Bayes' Theorem.
Study of continuous distributions such as Normal, Exponential, Gamma, and Weibull.
Measures of central tendency and dispersion, including mean, variance, and standard deviation.
Analysis of discrete random variables including Binomial, Poisson, and Geometric distributions.
Point estimation and confidence intervals for means, proportions, and variances.
Overview of statistics in engineering, data collection methods, and sampling techniques.
Joint, marginal, and conditional distributions, covariance, and correlation.
Core concepts of probability: sample spaces, events, axioms, and counting rules.
Simple linear regression, least squares method, and correlation analysis.
Sampling distributions of the mean and variance, and the Central Limit Theorem.
Hypothesis testing procedures, Type I/II errors, and tests for means and proportions.