Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Sampling: Inference and Statistics
Graph Chatbot
Related lectures (28)
Previous
Page 3 of 3
Next
Exploratory Statistics: Data Analysis Fundamentals
Covers the basics of exploratory statistics, including variables, quantiles, central tendency, dispersion, outliers, and robustness.
Probability Distributions in Environmental Studies
Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.
Understanding Statistics & Experimental Design
Explores t-tests, confidence intervals, ANOVA, and hypothesis testing in statistics, emphasizing the importance of avoiding false discoveries and understanding the logic behind statistical tests.
Approximate Query Processing: BlinkDB
Introduces BlinkDB, a framework for approximate query processing using sampling techniques.
Statistical Measures: Mean, Median, and Dispersion Techniques
Discusses statistical measures of central tendency and dispersion, focusing on mean, median, and their implications in data analysis.
Introduction to Comparison Statistics
Introduces comparison statistics, error rates, hypothesis testing, and real-life examples of treatment effectiveness and weightlifting analysis.
Understanding Statistics & Experimental Design
Provides an overview of basic probability theory, ANOVA, t-tests, central limit theorem, metrics, confidence intervals, and non-parametric tests.
Hypothesis Testing: Q-Q Plots and Non-Parametric Tests
Covers hypothesis testing, Q-Q plots, and non-parametric tests in statistics.
