Statistical algorithms | Robust regression
In robust statistics, repeated median regression, also known as the repeated median estimator, is a robust linear regression algorithm.The estimator has a breakdown point of 50%. Although it is equivariant under scaling, or under linear transformations of either its explanatory variable or its response variable, it is not under affine transformations that combine both variables. It can be calculated in time by brute force, in time using more sophisticated techniques, or in randomized expected time. It may also be calculated using an on-line algorithm with update time. (Wikipedia).
How to calculate Linear Regression using R. http://www.MyBookSucks.Com/R/Linear_Regression.R http://www.MyBookSucks.Com/R Playlist http://www.youtube.com/playlist?list=PLF596A4043DBEAE9C
From playlist Linear Regression.
Linear regression is used to compare sets or pairs of numerical data points. We use it to find a correlation between variables.
From playlist Learning medical statistics with python and Jupyter notebooks
An Introduction to Linear Regression Analysis
Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Lon
From playlist Linear Regression.
Brief intro the the linear regression formula and errors.
From playlist Regression Analysis
Ex: Comparing Linear and Exponential Regression
This video provides an example on how to perform linear regression and exponential regression on the TI84. The best model is identified based up the value of R^2. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com
From playlist Solving Applications Using Exponential Equations / Compounded and Continuous Interest / Exponential Regression
From playlist STAT 501
Ex: Make a Prediction Given the Results of Performing Linear Regression
This video provides and example of how to use the results of performing linear regression to make a prediction. Site:http://mathispower4u.com
From playlist Performing Linear Regression and Correlation
Statistical Rethinking - Lecture 20
Lecture 20 - Measurement error, missing data imputation, false-positive science - Statistical Rethinking: A Bayesian Course with R Examples
From playlist Statistical Rethinking Winter 2015
Tilmann Gneiting: Isotonic Distributional Regression (IDR) - Leveraging Monotonicity, Uniquely So!
CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 02, 2020 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians
From playlist Virtual Conference
Statistical data analysis | Statistical Data Science | Part 1
In this course you will learn how to analyze data. #Statistic plays important role in terms of data analysis. Here you will get exposed to utilize and understand various statistical method to analyse data. The following topic has discussed in this course. - Central tendency (mean and me
From playlist Data Analysis
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From playlist Simplilearn Free Courses [2022 Updated]
An introduction to Regression Analysis
Regression Analysis, R squared, statistics class, GCSE Like us on: http://www.facebook.com/PartyMoreStudyLess Related Videos Playlist on Linear Regression http://www.youtube.com/playlist?list=PLF596A4043DBEAE9C Using SPSS for Multiple Linear Regression http://www.youtube.com/playlist?li
From playlist Linear Regression.
SPSS Tutorial for data analysis | SPSS for Beginners | Part 2
SPSS Statistics is a software package used for interactive, or batched, statistical analysis. Long produced by SPSS Inc., it was acquired by IBM in 2009. The current versions are named IBM SPSS Statistics. In this course you will how to use SPSS for data analysis. This #SPSS course is begi
From playlist SPSS data Analysis
Google Tech Talk September 17, 2009 ABSTRACT Presented by Lindsey Simon and Steve Souders. This talk covers two open source projects being released by Googlers. Browserscope (http://browserscope.org/) is a community-driven project for profiling web browsers. The goals are to f
From playlist Web Exponents
Statistical Rethinking Fall 2017 - week02 lecture04
Week 02, lecture 04 for Statistical Rethinking: A Bayesian Course with Examples in R and Stan, taught at MPI-EVA in Fall 2017. This lecture covers Chapter 4. Slides are available here: https://speakerdeck.com/rmcelreath Additional information on textbook and R package here: http://xcel
From playlist Statistical Rethinking Fall 2017
Lecture 18 - Gradient Descent Search and Regularization
This is Lecture 18 of the CSE519 (Data Science) course taught by Professor Steven Skiena [http://www.cs.stonybrook.edu/~skiena/] at Stony Brook University in 2016. The lecture slides are available at: http://www.cs.stonybrook.edu/~skiena/519 More information may be found here: http://www
From playlist CSE519 - Data Science Fall 2016
In this episode of data talks we go over the Cinesift movie rating dataset with this question in mind: Do critics rate action movies worse than users? Today's hosts are Nathaniel, Vinod and Rock. The prominent tools used were colaboratory.jupyter.org, pandas, seaborn, and statsmodels. An
From playlist Data Talks
Introduction to Regression Analysis
This video introduced analysis and discusses how to determine if a given regression equation is a good model using r and r^2.
From playlist Performing Linear Regression and Correlation
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From playlist Simplilearn Live