Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Statistical significance

Related lectures (32)

Statistical Hypothesis Testing

Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.

Statistical Hypothesis Testing: Unilateral and Bilateral Pairs

Explores unilateral and bilateral pairs in statistical hypothesis testing, covering critical values, test statistics, and p-values.

Headline Analysis: Language Impact & Success

Explores the influence of language on headline success through real-world data analysis and statistical testing.

Hypothesis Testing and Confidence Intervals: An Overview

Covers hypothesis testing, confidence intervals, and their applications in statistics.

Understanding Statistics & Experimental Design

Provides an overview of basic probability theory, ANOVA, t-tests, central limit theorem, metrics, confidence intervals, and non-parametric tests.

From signal to observables

Compares gaseous, scintillator, and semiconductor detectors for radiation detection, emphasizing the importance of understanding uncertainties in measurements.

Hypothesis Testing: State of Nature

Explores hypothesis testing, emphasizing the state of nature and the importance of choosing the most powerful test.

Statistical Hypothesis Testing: Inference and Interpretation

Explores statistical hypothesis testing, including constructing confidence intervals, interpreting p-values, and making decisions based on significance levels.

Specification Testing and Machine Learning

Explores specification testing, machine learning, overfitting, regularization, prediction tests, and variable selection.

GLM: Statistical Hypothesis Testing

Explores statistical hypothesis testing, error types, thresholding, and multiple comparisons in GLM.

Interactive Session: Learning Strategies and Cognitive Reflection

Delves into learning strategies, cognitive reflection, and teaching impact on student performance.

Statistics & Experimental Design

Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.

Statistical Hypothesis Testing

Covers statistical hypothesis testing, likelihood estimation, and confidence intervals construction.

Evaluation in NLP

Delves into NLP evaluation, covering gold standards, precision, recall, and statistical significance.

Pitfalls in Empirical NLP Research

Explores pitfalls in NLP research, emphasizing the importance of standardized metrics and statistical testing.

Statistics: Hypothesis Testing & Confidence Intervals

Covers hypothesis testing, confidence intervals, data distributions, and statistical significance in data analysis.

Property Testing: Uniform Distribution

Covers property testing for uniform distributions and the importance of reliable predictions.

Ionisation and Discharges

Covers ionization, discharges, energy transfer, and star creation on Earth.

Explainable Neural Networks

Explores the concept of explainable neural networks and their significance in improving model interpretability, particularly in finance and house price valuation.

Statistical Significance: Maximum Likelihood Estimation and Confidence Intervals

Explores type I and type II errors, critical values, and confidence intervals in statistical significance.