Concept
Karl Pearson
Related lectures (22)
Data Handling: Problems and Distributions
Covers common data problems and important distributions, along with correlation and dependencies analysis.
Confidence Intervals and Hypothesis Tests
Covers confidence intervals, hypothesis tests, standard errors, statistical models, likelihood, Bayesian inference, ROC curve, Pearson statistic, goodness of fit tests, and power of tests.
Statistical Tests: Wald and p-values
Explores statistical tests like the Wald test and p-values, emphasizing their calculation and interpretation.
Optimal Testing Methods
Explores optimal testing methods in statistics, focusing on the Neyman-Pearson framework and the construction of test functions for different types of hypotheses.
Statistical Hypothesis Testing
Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.
Confidence Intervals and Hypothesis Testing
Explores confidence intervals, hypothesis testing, and ROC curves in statistical analysis.
Optimal Tests for Simple Hypotheses
Discusses optimal tests for simple hypotheses and the significance of standardized distance in hypothesis testing.
Linear Regression: Pearson Correlation
Covers the Pearson correlation, relationship direction, form, strength, and regression model assessment.
Estimation and Correlation
Explains estimation, correlation, and Pearson correlation in statistics, focusing on measuring and describing relationships between variables.
Hydrologic and Hydraulic Design
Explores the design of engineering works for floods, focusing on 100-year flood determination and the collapse of levees during extreme events.