Related lectures (53)
Heat Equation: Diffusion
Covers the heat equation for diffusion and conservation of thermal energy.
Neural Networks: Training and Activation
Explores neural networks, activation functions, backpropagation, and PyTorch implementation.
Two-Sample T-Test
Explains the two-sample t-test for comparing means of independent samples, including hypothesis testing steps and test statistic calculation.
Confidence Intervals and T-Test
Explores confidence intervals, T-test, and hypothesis testing, including assumptions and critical regions.
Genomic Data Analysis: Identifying Differentially Expressed Genes
Discusses methods for identifying differentially expressed genes in genomic data analysis.
Synchronization
Covers the principles of synchronization in parallel computing, focusing on shared memory synchronization and different methods like locks and barriers.
Z-Test: Hypothesis Testing
Introduces hypothesis testing, focusing on the Z-test and critical regions.
Statistics & Experimental Design
Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.
Statistics Essentials: The t-test
Introduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.
Bayesian Statistics: Hypothesis Testing and Estimation
Covers hypothesis testing, p-values, significance levels, and Bayesian estimation.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.