Mixed-design analysis of variance

Automatic Pattern Matching for 3D Geometry in Blender

To help refining the alignment of multiple 3D scans with each other, I have written a new tool for Blender which automatically finds the best fit for mesh objects.

From playlist Random Blender Tests

Mixture Models 4: multivariate Gaussians

Full lecture: http://bit.ly/EM-alg We generalise the equations for the case of a multivariate Gaussians. The main difference from the previous video (part 2) is that instead of a scalar variance we now estimate a covariance matrix, using the same posteriors as before.

From playlist Mixture Models

Variance (4 of 4: Proof of two formulas)

More resources available at www.misterwootube.com

From playlist Random Variables

QAI 2.22: Variance

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

How to find the variance and standard deviation from a set of data

👉 Learn how to find the variance and standard deviation of a set of data. The variance of a set of data is a measure of spread/variation which measures how far a set of numbers is spread out from their average value. The standard deviation of a set of data is a measure of spread/variation

From playlist Variance and Standard Deviation

Stanford CS229: Machine Learning | Summer 2019 | Lecture 18 - Principal & Independent CA

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3E9HJHU Anand Avati Computer Science, PhD To follow along with the course schedule and syllabus, visit: http://cs229.stanford.edu/syllabus-summer2019.html

From playlist Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati)

ANOVA Theory Lecture

Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2018 This video replaces a previous live in-class video that covered an overall lecture to ANOVA,. The video covers a basic background to ANOVA, the F-test, post hoc tests, and effect sizes. List of videos for class on stat

From playlist Advanced Statistics Videos

Blender - New feature test: Smoke

For more information about the 3d software Blender please visit www.blender.org. www.kaikostack.com

From playlist Random Blender Tests

R - ANOVA Theory Lecture

Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2016 This video covers theory of ANOVA, hypothesis testing, F ratios, distributions, df, effect size, power, and post hoc tests. An example of several types of ANOVA will be uploaded next. Note: This video was recorded liv

From playlist PSY 527/627 (R) Advanced Statistics with Dr. B

Mixture Models 3: multivariate Gaussians

Full lecture: http://bit.ly/EM-alg We generalise the equations for the case of a multivariate Gaussians. The main difference from the previous video (part 2) is that instead of a scalar variance we now estimate a covariance matrix, using the same posteriors as before.

From playlist Mixture Models

Melanie Bell - Analytical and Design Issues for Cluster Randomized Trials

Professor Melanie Bell (University of Arizona) presents "Analytical and Design Issues for Cluster Randomized Trials", 24 April 2020.

From playlist Statistics Across Campuses

Statistical modelling of Dengue incidences and climatic variables in India by Ravishankar N

DISCUSSION MEETING : MATHEMATICAL AND STATISTICAL EXPLORATIONS IN DISEASE MODELLING AND PUBLIC HEALTH ORGANIZERS : Nagasuma Chandra, Martin Lopez-Garcia, Carmen Molina-Paris and Saumyadipta Pyne DATE & TIME : 01 July 2019 to 11 July 2019 VENUE : Madhava Lecture Hall, ICTS, Bangalore

From playlist Mathematical and statistical explorations in disease modelling and public health

JASP/Excel - Two-Way Mixed ANOVA Example

Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2017 This video covers the following: Excel: data screening - accuracy, outliers using z scores, missing data, normality, linearity, homogeneity, and homoscedasticity JASP: running a mixed ANOVA, post hocs, effect size, Leve

From playlist Learn and Use G*Power

Lec 15 | MIT 2.830J Control of Manufacturing Processes, S08

Lecture 15: Response surface modeling and process optimization Instructor: Duane Boning, David Hardt View the complete course at: http://ocw.mit.edu/2-830JS08 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 2.830J, Control of Manufacturing Processes S08

Blender Smoothed Particle Hydrodynamics (SPH) Problematic Deflections

Demonstration of a bug in Blender's particle system in combination with SPH-Fluids. http://www.kostackstudio.de

From playlist Random Blender Tests

R - Two Way Between Subjects ANCOVA Example

Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2016 This video covers how to work a two-way between-subjects ANCOVA from power, data screening, ANOVA, post hoc, effect size, and graphs using ggplot2. Note: This video was recorded live during class - it will have pauses

From playlist Learn and Use G*Power

Neuroscience source separation 2a: Spatial separation

This is part two of a three-part lecture series I taught in a masters-level neuroscience course in fall of 2020 at the Donders Institute (the Netherlands). The lectures were all online in order to minimize the spread of the coronavirus. That's good for you, because now you can watch the en

From playlist Neuroscience source separation (3-part lecture series)

Find the Difference of Mixed Numbers - Compare 2 Methods

This video explains how to find the difference of mixed numbers using improper fractions and using mixed numbers. A model is shown. http://mathispower4u.com

From playlist Adding and Subtracting Mixed Numbers

Asymptotic properties of the volatility estimator from high-frequency data modeled by Ananya Lahiri

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

QAICourse6 5ANOVA

From playlist Applied Data Analysis and Statistical Inference