Design of experiments | Analysis of variance | Regression analysis
In statistics, an interaction may arise when considering the relationship among three or more variables, and describes a situation in which the effect of one causal variable on an outcome depends on the state of a second causal variable (that is, when effects of the two causes are not additive). Although commonly thought of in terms of causal relationships, the concept of an interaction can also describe non-causal associations (then also called moderation or effect modification). Interactions are often considered in the context of regression analyses or factorial experiments. The presence of interactions can have important implications for the interpretation of statistical models. If two variables of interest interact, the relationship between each of the interacting variables and a third "dependent variable" depends on the value of the other interacting variable. In practice, this makes it more difficult to predict the consequences of changing the value of a variable, particularly if the variables it interacts with are hard to measure or difficult to control. The notion of "interaction" is closely related to that of moderation that is common in social and health science research: the interaction between an explanatory variable and an environmental variable suggests that the effect of the explanatory variable has been moderated or modified by the environmental variable. (Wikipedia).
Statistic vs Parameter & Population vs Sample
This stats video tutorial explains the difference between a statistic and a parameter. It also discusses the difference between the population and sample. It includes examples such as the sample mean, population mean, sample standard deviation, population standard deviation, sample propo
From playlist Statistics
Statistics Lecture 4.5 Part 2: Complementary Events with "At Least One"
From playlist Statistics Playlist 1
This lecturelet will introduce you to the series on statistical analyses of time-frequency data. For more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/
From playlist OLD ANTS #8) Statistics
More Standard Deviation and Variance
Further explanations and examples of standard deviation and variance
From playlist Unit 1: Descriptive Statistics
Statistics Lecture 5.2: A Study of Probability Distributions, Mean, and Standard Deviation
https://www.patreon.com/ProfessorLeonard Statistics Lecture 5.2: A Study of Probability Distributions, Mean, and Standard Deviation
From playlist Statistics (Full Length Videos)
Statistics 5_1 Confidence Intervals
In this lecture explain the meaning of a confidence interval and look at the equation to calculate it.
From playlist Medical Statistics
Statistics Lecture 6.2: Introduction to the Normal Distribution and Continuous Random Variables
https://www.patreon.com/ProfessorLeonard Statistics Lecture 6.2: Introduction to the Normal Distribution and Continuous Random Variables
From playlist Statistics (Full Length Videos)
Populations, Samples, Parameters, and Statistics
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Populations, Samples, Parameters, and Statistics
From playlist Statistics
Covariance (1 of 17) What is Covariance? in Relation to Variance and Correlation
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn the difference between the variance and the covariance. A variance (s^2) is a measure of how spread out the numbers of
From playlist COVARIANCE AND VARIANCE
ANOVA in RStudio Part 2 | ANOVA, Model Fitting, Effect Size, Post-Hoc Analysis & Visualization
In these two installments, I demonstrate how to run an #ANOVA test in #RStudio. Specifically, in the first video, I will discuss: 1 Data visualization 2 Assumption 1. Normality (of residuals) 3 Assumption 2. Homogeneity of variances: Levene's test; Bartlett's test In the second video,
From playlist Repeated Measures ANOVA
Robert E. Kass - Statistical Assessment of Interaction Among Brain Regions...
Statistical Assessment of Interaction Among Brain Regions from Multi-Electrode Recordings ---------------------------------- Institut Henri Poincaré, 11 rue Pierre et Marie Curie, 75005 PARIS http://www.ihp.fr/ Rejoingez les réseaux sociaux de l'IHP pour être au courant de nos actualités
From playlist Workshop "Workshop on Mathematical Modeling and Statistical Analysis in Neuroscience" - January 31st - February 4th, 2022
Extremal statistics in 1d Coulomb gas by Anupam Kundu
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru Large deviation theory made its way into statistical physics as a mathematical framework for studying equilibrium syst
From playlist Large deviation theory in statistical physics: Recent advances and future challenges
Predictive Analytics, Machine Learning, and Recommendation Systems on Hadoop
Originally recorded January 30, 2014. In the world of ever growing data volumes, how do you extract insight, trends and meaning from all that data in Hadoop? Do you need help transforming your big data into big knowledge? Organizations know that the key to competitive advantage is in usin
From playlist O'Reilly Webcasts 3
Thermalization in closed quantum many-body systems I: Basic notions by Stefan Kehrein
Open Quantum Systems DATE: 17 July 2017 to 04 August 2017 VENUE: Ramanujan Lecture Hall, ICTS Bangalore There have been major recent breakthroughs, both experimental and theoretical, in the field of Open Quantum Systems. The aim of this program is to bring together leaders in the Open Q
From playlist Open Quantum Systems
A Brief History of Data Visualization
In this talk, I will chart the course of visual depictions of data over the last 200 years, from the classic data graphics of Playfair and Minard to modern interactive visualization systems. Along the way, we will consider the factors that contribute to the effectiveness of information gra
From playlist Lecture Collection | Human-Computer Interaction Seminar (2009-2010)
Adrian Baddeley: The Poisson-saddlepoint approximation
Gibbs spatial point processes are important models in theoretical physics and in spatial statistics. After a brief survey of Gibbs point processes, we will present a method for approximating their most important characteristic, the intensity of the process. The method has some affinity wit
From playlist Probability and Statistics
Statistical Mechanics (Tutorial) by Chandan Dasgupta
Statistical Physics Methods in Machine Learning DATE: 26 December 2017 to 30 December 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru The theme of this Discussion Meeting is the analysis of distributed/networked algorithms in machine learning and theoretical computer science in the "t
From playlist Statistical Physics Methods in Machine Learning
Statistical Rethinking Winter 2019 Lecture 09
Lecture 09 of the Dec 2018 through March 2019 edition of Statistical Rethinking: A Bayesian Course with R and Stan. Covers interaction effects.
From playlist Statistical Rethinking Winter 2019
Data Science - Part IV - Regression Analysis and ANOVA Concepts
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of linear regression analysis, interaction terms, ANOVA, optimization, log-leve
From playlist Data Science
Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
https://www.patreon.com/ProfessorLeonard Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
From playlist Statistics (Full Length Videos)