Regression analysis | Statistical deviation and dispersion
In statistics, a sequence (or a vector) of random variables is homoscedastic (/ˌhoʊmoʊskəˈdæstɪk/) if all its random variables have the same finite variance. This is also known as homogeneity of variance. The complementary notion is called heteroscedasticity. The spellings homoskedasticity and heteroskedasticity are also frequently used. Assuming a variable is homoscedastic when in reality it is heteroscedastic (/ˌhɛtəroʊskəˈdæstɪk/) results in unbiased but inefficient point estimates and in biased estimates of standard errors, and may result in overestimating the goodness of fit as measured by the Pearson coefficient. The existence of heteroscedasticity is a major concern in regression analysis and the analysis of variance, as it invalidates statistical tests of significance that assume that the modelling errors all have the same variance. While the ordinary least squares estimator is still unbiased in the presence of heteroscedasticity, it is inefficient and generalized least squares should be used instead. Because heteroscedasticity concerns expectations of the second moment of the errors, its presence is referred to as misspecification of the second order. The econometrician Robert Engle was awarded the 2003 Nobel Memorial Prize for Economics for his studies on regression analysis in the presence of heteroscedasticity, which led to his formulation of the autoregressive conditional heteroscedasticity (ARCH) modeling technique. (Wikipedia).
Introduction to Homotopy Theory- PART 1: UNIVERSAL CONSTRUCTIONS
The goal of this series is to develop homotopy theory from a categorical perspective, alongside the theory of model categories. We do this with the hope of eventually developing stable homotopy theory, a personal goal a passion of mine. I'm going to follow nLab's notes, but I hope to add t
From playlist Introduction to Homotopy Theory
Homotopic, Enantiotopic, Diastereotopic, and Heterotopic Protons
In doing NMR spectroscopy, we must be able to predict chemical shifts for a variety of protons. When comparing specific pairs of protons, we can assign them a few different relationships, those being homotopic, enantiotopic, diasteretopic, and heterotopic. Let's see what these words mean a
From playlist Organic Chemistry
Homogeneous vs Heterogeneous Catalysts - Basic Introduction
This video provides a basic introduction into homogeneous and heterogeneous catalysts. A Homogeneous catalyst exists in the same phase as the reactants and products. A heterogeneous catalyst exists in a different phase as the reactants and products. New Chemistry Video Playlist: https
From playlist New AP & General Chemistry Video Playlist
Homogeneous and Heterogeneous Mixtures Examples, Classification of Matter, Chemistry
This chemistry video tutorial explains the difference between homogeneous and heterogeneous mixtures within the subtopic of the classification of matter. It contains plenty of examples. Homogeneous mixtures have constant composition. Salt water is a homogeneous mixture - it has one visi
From playlist New AP & General Chemistry Video Playlist
Heterogeneous Equilibrium - Homogeneous Equilibrium
Watch more videos on http://www.brightstorm.com/science/chemistry SUBSCRIBE FOR All OUR VIDEOS! https://www.youtube.com/subscription_center?add_user=brightstorm2 VISIT BRIGHTSTORM.com FOR TONS OF VIDEO TUTORIALS AND OTHER FEATURES! http://www.brightstorm.com/ LET'S CONNECT! Facebook ► h
From playlist Chemistry
See all my videos here: http://www.zstatistics.com/videos/ See the whole regression series here: https://www.youtube.com/playlist?list=PLTNMv857s9WUI1Nz4SssXDKAELESXz-bi 0:00 Introduction 1:41 Techincal definition 5:25 Why care? 8:12 Detection method 1 - Resiudal plots 8:42 Detection me
From playlist Regression series (10 videos)
Regression assumptions explained!
See all my videos at http://www.zstatistics.com/ See the whole regression series here: https://www.youtube.com/playlist?list=PLTNMv857s9WUI1Nz4SssXDKAELESXz-bi 0:00 Introduction 8:08 Linearity (correct functional form) 14:10 Constant error variance (homoskedasticity) 19:18 Independent e
From playlist Regression series (10 videos)
R - Multilevel Models Lecture (Updated)
Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2017 This video is a rerecording of a multilevel model lecture I gave a while back - covers the ideas behind MLM and how to run a model in R using nlme. The example is new! Lecture materials and assignment available at sta
From playlist Advanced Statistics Videos
A Level Chemistry Revision "Heterogeneous and Homogeneous Catalysts"
In this video, we look at heterogeneous and homogeneous catalysts. First we explore heterogeneous catalysts, using the Haber process as an example. We look at how heterogeneous catalysts work in terms of adsorption and desorption. We then look at homogeneous catalysts using the reactions o
From playlist A Level Chemistry "Kinetics and Equilibria"
R - Moderation Analyses (Manual) Example
Lecturer: Dr. Erin M. Buchanan Missouri State University Fall 2016 This video covers how to perform a moderation analysis manually, to be able to apply for 3+ way interactions. Other videos on our channel cover how to do moderation with the QuantPsyc package. Data screening (outliers, ho
From playlist Advanced Statistics Videos
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
Understanding Quantum Mechanics #1: It’s not about discreteness
This must be one of the most common misunderstandings about quantum mechanics, that quantum mechanics is about making things discrete. But is an understandable misunderstanding because the word “quantum” suggests that quantum mechanics is about small amounts of something. Indeed, if you as
From playlist Understanding Quantum Mechanics
Geometry - Ch. 1: Basic Concepts (19 of 49) Equal vs Congruent Angles
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what the difference (and similarity) between equal angles and congruent angles. If 2 angles are congruent, their angle measures are equal. If the angle measures are equal then the 2 angles are
From playlist GEOMETRY CH 1 BASIC CONCEPTS
SPSS - Data Screening (Step 4): Assumptions Example
Lecturer: Jessica Willis Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdoom.com/page/advanced-statistics/
From playlist Intermediate Statistics Videos
R & Python - Linear Regression
Lecturer: Dr. Erin M. Buchanan Summer 2020 https://www.patreon.com/statisticsofdoom This video is part of my human language modeling class - this video set covers the updated version with both R and Python. Regression is a popular technique for continuous data - in this example, we talk
From playlist Human Language (ANLY 540)
IntroLinearRegression.4.EqualVarianceAssumption
This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources
From playlist Applied Data Analysis and Statistical Inference
Replication or Exploration? Sequential Design for Stochastic Simulation Experiments
The Data Science Institute (DSI) hosted a virtual seminar by Robert Gramacy from Virginia Tech on March 15, 2021. Read more about the DSI seminar series at https://data-science.llnl.gov/latest/seminar-series. We investigate the merits of replication and provide methods that search for opti
From playlist DSI Virtual Seminar Series
Abundant, Deficient, and Perfect Numbers ← number theory ← axioms
Integers vary wildly in how "divisible" they are. One way to measure divisibility is to add all the divisors. This leads to 3 categories of whole numbers: abundant, deficient, and perfect numbers. We show there are an infinite number of abundant and deficient numbers, and then talk abou
From playlist Number Theory
Lecturer: Dr. Erin M. Buchanan Spring 2021 https://www.patreon.com/statisticsofdoom This video covers the basics of linear regression including assumptions, hypothesis testing, how to understand overall models and coefficients, how to examine for outliers, and how to run categorical va
From playlist Graduate Statistics Flipped