Least squares | Errors and residuals
In statistics, the residual sum of squares (RSS), also known as the sum of squared residuals (SSR) or the sum of squared estimate of errors (SSE), is the sum of the squares of residuals (deviations predicted from actual empirical values of data). It is a measure of the discrepancy between the data and an estimation model, such as a linear regression. A small RSS indicates a tight fit of the model to the data. It is used as an optimality criterion in parameter selection and model selection. In general, total sum of squares = explained sum of squares + residual sum of squares. For a proof of this in the multivariate ordinary least squares (OLS) case, see partitioning in the general OLS model. (Wikipedia).
RegressionANOVA.5.MultiplePredictorsP2
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 Regression and ANOVA
Ex: Find the Error When Using a Partial Sum to Estimate an Infinite Sum (Alternating Series)
This video explains how to find the error when using a partial sum to estimate an infinite sum of a convergent alternating series. Site: http://mathispower4u.com
From playlist Infinite Series
Sum of integers squared explained
Explanation on deriving the equation. In arithmetic, we often come across the sum of n natural numbers. Sum of squares refers to the sum of the squares of numbers. It is basically the addition of squared numbers. Support my channel with this special custom merch! https://www.etsy.com/list
From playlist Math formulas, proofs, ideas explained
I recently uploaded 200 videos that are much more concise with excellent graphics. Click the link in the upper right-hand corner of this video. It will take you to my youtube channel where videos are arranged in playlists. In this older video: Understanding and interpreting residual plot
From playlist Older Statistics Videos and Other Math Videos
Find a Partial Sum Using Summation Formula: Sum((2-3i)^2)
This video explains how to determine a partial sum given in sigma notation using summation formulas. http://mathispower4u.com
From playlist Series (Algebra)
Sum of Squares (Total, Between, Within)
What is "sum of squares" in ANOVA? How to calculate SSW, SST, SSB. 0:00 Intro 0: 11 What is Total Sum of Squares? 0:51 TSS Example 1:25 What are SSW SSB? 1:49 How to Calculate SSW 3:11 How to Calculate SSB 3:54 How to Calculate TSS
From playlist ANOVA
Number Theory | Sums of Squares Part 7.
Our final video in this series where we have examined which natural numbers are expressible as a sum of various numbers of square integers. Here we show that all natural numbers are expressible as a sum of four squares. http://www.michael-penn.net http://www.randolphcollege.edu/mathematic
From playlist Sums of Squares
Sum of Alternating Inverse Squares
The Basel problem, but this time it's alternating! Sum of (-1)^(n-1)/n^2. New math videos every Wednesday. Subscribe to make sure you see them!
From playlist Calculus Problems
Complex analysis: Summing series
This lecture is part of an online undergraduate course on complex analysis. This is a replacement for a previous video, correcting some minor typos. We show how to use the residue calculus to sum series, such as Euler's series 1/1^2 + 1/2^2+ ... Solution to exercise in rot 13: cv phorq
From playlist Complex analysis
Neural Networks Pt. 2: Backpropagation Main Ideas
Backpropagation is the method we use to optimize parameters in a Neural Network. The ideas behind backpropagation are quite simple, but there are tons of details. This StatQuest focuses on explaining the main ideas in a way that is easy to understand. NOTE: This StatQuest assumes that you
From playlist StatQuest
Complex Analysis: Basel Problem Variation
Today, we use the residue theorem from complex analysis to evaluate a similar infinite sum to the Basel problem. Basel Problem using complex analysis: https://www.youtube.com/watch?v=5R0JFhFc7VI
From playlist Contour Integration
Gradient Descent, Step-by-Step
Gradient Descent is the workhorse behind most of Machine Learning. When you fit a machine learning method to a training dataset, you're probably using Gradient Descent. It can optimize parameters in a wide variety of settings. Since it's so fundamental to Machine Learning, I decided to mak
From playlist Optimizers in Machine Learning
Complex Analysis: The Basel Problem
Today, we solve the Basel Problem using complex analysis! Residues at higher order poles: https://www.youtube.com/watch?v=9hdZDHkKoAM This is a long video, so here are some timestamps for each section 1:14 Chapter 1 - Motivation 5:45 Chapter 2 - Finding f(z) 13:51 Chapter 3 - Sum of the
From playlist Contour Integration
Regression Trees, Clearly Explained!!!
Regression Trees are one of the fundamental machine learning techniques that more complicated methods, like Gradient Boost, are based on. They are useful for times when there isn't an obviously linear relationship between what you want to predict, and the things you are using to make the p
From playlist StatQuest
How to Prune Regression Trees, Clearly Explained!!!
Pruning Regression Trees is one the most important ways we can prevent them from overfitting the Training Data. This video walks you through Cost Complexity Pruning, aka Weakest Link Pruning, step-by-step so that you can learn how it works and see it in action. NOTE: This StatQuest assumes
From playlist StatQuest
Simple Linear Regression (Part B)
Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Kharagpur: Regression Analysis | CosmoLearning.org Mathematics
Complex Analysis: Alternating Basel Problem
Today, we use complex analysis and residues to evaluate the alternating Basel problem. Basel problem using complex analysis: https://www.youtube.com/watch?v=5R0JFhFc7VI&t=3242s Residues at higher order poles: https://www.youtube.com/watch?v=9hdZDHkKoAM
From playlist Contour Integration
Backpropagation Details Pt. 1: Optimizing 3 parameters simultaneously.
The main ideas behind Backpropagation are super simple, but there are tons of details when it comes time to implementing it. This video shows how to optimize three parameters in a Neural Network simultaneously and introduces some Fancy Notation. NOTE: This StatQuest assumes that you alrea
From playlist StatQuest
Visual Proof Short: Alternating Sum of Squares II
From playlist Finite Sums