Related lectures (33)
Multiple Testing Problem
Explores the challenges of multiple testing in genomic data analysis, covering error rate control, adjusted p-values, permutation tests, and pitfalls in hypothesis testing.
Understanding ROC Curves
Explores the ROC curve, True Positive Rate, False Positive Rate, and prediction probabilities in classification models.
Probability: Quiz
Covers probability scenarios and includes a quiz using Kahoot.
Strategy Selection
Explores strategy selection challenges, performance evaluation, and statistical testing in finance, emphasizing the importance of strategy portfolios.
GLM: Statistical Hypothesis Testing
Explores statistical hypothesis testing, error types, thresholding, and multiple comparisons in GLM.
Understanding Statistics & Experimental Design
Provides an overview of basic probability theory, ANOVA, t-tests, central limit theorem, metrics, confidence intervals, and non-parametric tests.
Signal Detection Theory
Explores Signal Detection Theory and its impact on decision-making processes in statistics and experimental design.
Principal Component Analysis: Understanding Data Structure
Explores Principal Component Analysis, dimensionality reduction, data quality assessment, and error rate control.
Hypothesis Testing: T-Test and Chi-Square Test
Explains hypothesis testing using T-test and Chi-square test to compare means and assess independence of variables.
Evaluation of Binary Classifiers
Discusses the evaluation of binary classifiers, including recall, sensitivity, specificity, ROC curves, and performance measures.

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