Home
Search results “Multiple regression analysis what is”
This video directly follows part 1 in the StatQuest series on General Linear Models (GLMs) on Linear Regression https://youtu.be/nk2CQITm_eo . Here I show how the exact same principles from "simple" linear regression also apply multiple regression. At the end, I show how to test if a multiple regression is better than a simple regression. To see how to do multiple regression in R, check out https://youtu.be/hokALdIst8k For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/
Overview of multiple regression including the selection of predictor variables, multicollinearity, adjusted R-squared, and dummy variables. If you find these videos useful, I hope that you will consider signing up for my online statistics workshop on Udemy, which contains additional videos and lots of problems to help you apply and reinforce the important concepts: https://www.udemy.com/statshelp/?couponCode=coefficient
Views: 179394 George Ingersoll
This video demonstrates how to interpret multiple regression output in SPSS. This example includes two predictor variables and one outcome variable. Unstandardized and standardized coefficients are reviewed.
Views: 142132 Dr. Todd Grande
It covers in details the meaning of Multiple Regression, various methods of framing Multiple Regression Equations and Standard Error of Estimate in Multiple Regression. Lecture by: Prof. Rajinder Kumar Arora, Head of Department (Commerce & Management)
In this video, I will be talking about a parametric regression method called “Linear Regression” and it's extension for multiple features/ covariates, "Multiple Regression". You will gain an understanding of how to estimate coefficients using the least squares approach (scalar and matrix form) - fundamental for many other statistical learning methods. If you thought this content was useful, SHARE it with your friend – you know, the one with the stats exam tomorrow and trying to binge watch YouTube tutorials. SUBSCRIBE to my channel for more amazing content! More on Matrix Calculus: https://atmos.washington.edu/~dennis/MatrixCalculus.pdf
Views: 46939 CodeEmporium
I demonstrate how to perform a multiple regression in SPSS. This is the in-depth video series. I cover all of the main elements of a multiple regression analysis, including multiple R, R squared, model development (via stepwise method), intercept, unstandardized beta weights, standardized beta weights, semi-partial correlation, standard errors, as well as basic heteroscedasticity tests.
Views: 493993 how2stats
Views: 378817 Dave Your Tutor
This updated vidcast discusses the conceptual underpinnings of different types of model building in multiple analysis: simultaneous regression, hierarchical regression and stepwise regression. This improved vidcast offers clearer exposition of the concepts and a more readable Powerpoint slide.
Views: 10393 Ray Cooksey
This tutorial covers the basic concepts of Multiple Regression. Before watching this tutorial please make sure you are familiar with the basic concepts of simple linear regression, if you need a review, go to https://youtu.be/BLRjywb0mes. In this tutorial we discuss introduce the multiple regression model and discuss what its parameters mean and how to test the significance of the slopes of each independent variable using a t test. This tutorial also shows how to conduct regression analysis using Excel, and the output for multiple regression hypothesis tests for individual slopes is examined using the t tests statistic and the p value approach. The significance of r and the adjusted r squared values is also discussed. The ANOVA table and F test are not covered in this tutorial.
Views: 45279 Learn Something
From an existing multiple regression output produced with Excel 2007, I show you how to make point predictions and approximate 95% prediction intervals. The basic package of Excel does not have a routine for making predictions intervals, so I suggest a method of inflating the residual standard deviation statistic by 10% to get an approximate standard error of prediction.
Views: 128859 ProfTDub
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 Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 740794 statisticsfun
The Multiple Linear Regression video series is available for FREE as an iTune book for download on the iPad. The ISBN number is 978-1-62407-066-6. The title is "Multiple Linear Regression." Waller and Lumadue are the authors. The iTune text provides accompanying narrative and the SPSS readouts used in the video series. The textbook can be obtained from: https://itunes.apple.com/us/book/multiple-linear-regression/id657084933?ls=1 This video introduces the concept of multiple linear regression
Views: 34368 Lee Rusty Waller
A brief explanation of the output of regression analysis. For more information visit www.calgarybusinessblog.com
Views: 465880 Matt Kermode
This video provides an example of interpreting multiple regression output in excel. The data set comes from Andy Field's "Discovering Statistics Using SPSS" (2009, 3rd Edition).
Views: 326595 TheWoundedDoctor
Multiple Regression in Excel in a nutshell. Focusing on Excel functionality more than presentation of regression theory.
Views: 88118 Jalayer Academy
Multiple regression concept explained in simple words along with solution of a numerical question. FOR ALL VIDEOS PLEASE CLICK youtube.com/kokabmanzoor/videos
Views: 3732 Kokab Manzoor
This video covers standard statistical tests for multiple regression. I cover: - assumptions placed on the error term - the F test of overall or joint significance - hypotheses - F test statistic - p-value and its interpretatoin - the F test of overall or joint significance - hypotheses - F test statistic - p-value and its interpretation - the t test of individual significance - hypotheses - F test statistic - p-value and its interpretation
Views: 121149 Jason Delaney
We review what the main goals of regression models are, see how the linear regression models tie to the concept of linear equations, and learn to interpret the coefficients of a simple linear regression model with an example. TABLE OF CONTENTS: 00:00 Simple Linear Regression 00:17 Objectives of Regressions 02:54 Variable’s Roles 03:30 The Magic: A Linear Equation 04:21 Linear Equation Example 05:24 Changing the Intercept 06:02 Changing the Slope 07:00 But the world is not linear! 07:44 Simple Linear Regression Model 08:25 Linear Regression Example 09:16 Data for Example 09:46 Simple Linear Regression Model 10:17 Regression Result 11:02 Interpreting the Coefficients 12:38 Estimated vs. Actual Values
Views: 346619 dataminingincae
I demonstrate how to create a scatter plot to depict the model R results associated with a multiple regression/correlation analysis.
Views: 87178 how2stats
Today we're going to introduce one of the most flexible statistical tools - the General Linear Model (or GLM). GLMs allow us to create many different models to help describe the world - you see them a lot in science, economics, and politics. Today we're going to build a hypothetical model to look at the relationship between likes and comments on a trending YouTube video using the Regression Model. We'll be introducing other popular models over the next few episodes. Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Mark Brouwer, Kenneth F Penttinen, Trevin Beattie, Satya Ridhima Parvathaneni, Erika & Alexa Saur, Glenn Elliott, Justin Zingsheim, Jessica Wode, Eric Prestemon, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Brian Thomas Gossett, Khaled El Shalakany, Indika Siriwardena, SR Foxley, Sam Ferguson, Yasenia Cruz, Eric Koslow, Caleb Weeks, D.A. Noe, Shawn Arnold, Malcolm Callis, Advait Shinde, William McGraw, Andrei Krishkevich, Rachel Bright, Mayumi Maeda, Kathy & Tim Philip, Jirat, Ian Dundore -- Want to find Crash Course elsewhere on the internet? Facebook - http://www.facebook.com/YouTubeCrashCourse Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids
Views: 59313 CrashCourse
https://github.com/codebasics/py/tree/master/ML/2_linear_reg_multivariate (Exercise is at the end of the ipynb notebook so just open that file and read through) In this machine learning tutorial with python, we will write python code to predict home prices using multivariate linear regression in python (using sklearn linear_model). Home prices are dependant on 3 independant variables: area, bedrooms and age. Pandas dataframe is used to fill missing values first and then use that dataset to train a multivariate regression model.You can use exercise at the end to consolidate your understanding on whatever you have learnt in this machine learning tutorial. Website: http://codebasicshub.com/ Facebook: https://www.facebook.com/codebasicshub Twitter: https://twitter.com/codebasicshub Google +: https://plus.google.com/106698781833798756600
Views: 21924 codebasics
Learn how to make predictions using Simple Linear Regression. To do this you need to use the Linear Regression Function (y = a + bx) where "y" is the dependent variable, "a" is the y intercept, "b" is the slope of the regression line, and "x" is the independent variable. This video also shows you how to determine the slope (b) of the regression line, and the y intercept (a). In order to determine the slope of a line you will need to first determine the Pearson Correlation Coefficient - this is described in a separate video (https://www.youtube.com/watch?v=2SCg8Kuh0tE).
Views: 463730 Eugene O'Loughlin
Using multiple predictor variables to predict a single quantitative outcome.
This video is a companion to the StatQuest on Multiple Regression https://youtu.be/zITIFTsivN8 It starts with a simple regression in R and then shows how multiple regression can be used to determine which parameters are the most valuable. If you want the code, you can get it from the StatQuest website, here: https://statquest.org/2017/10/30/statquest-multiple-regression-in-r/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/
Views: 10067 BI Excel
Interpretation of the coefficients on the predictors in multiple linear regression made easy.
Views: 383186 Phil Chan
I demonstrate how to perform and interpret a hierarchical multiple regression in SPSS. I pay particular attention to the different blocks associated with a hierarchical multiple regression, as well as R squared change and F change.
Views: 119773 how2stats
Applied Multivariate Statistical Modeling by Dr J Maiti,Department of Management, IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
Views: 9808 nptelhrd
Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
Views: 43962 nptelhrd
Multiple Linear Regression Model in R; Fitting the model and interpreting the outcomes! Practice Dataset: (https://bit.ly/2rOfgEJ); Linear Regression Concept and with R (https://bit.ly/2z8fXg1) More Statistics and R Programming Tutorial (https://goo.gl/4vDQzT) Learn how to fit and interpret output from a multiple linear regression model in R and produce summaries. ▶︎ You will learn to use "lm", "summary", "cor", "confint" functions. ▶︎ You will also learn to use "plot" function for producing residual and QQ plots in R. ▶︎ We recommend that you first watch our video on simple linear regression concept (https://youtu.be/vblX9JVpHE8) and in R (https://youtu.be/66z_MRwtFJM) ▶︎▶︎Download the dataset here: https://statslectures.com/r-scripts-datasets ▶︎▶︎Like to support us? You can Donate https://statslectures.com/support-us or Share our Videos and help us reach more people! ◼︎ Table of Content: 0:00:07 Multiple Linear Regression Model 0:00:32 How to fit a linear model in R? using the "lm" function 0:00:36 How to access the help menu in R for multiple linear regression 0:01:06 How to fit a linear regression model in R with two explanatory or X variables 0:01:19 How to produce and interpret the summary of linear regression model fit in R 0:03:16 How to calculate Pearson's correlation between the two variables in R 0:03:26 How to interpret the collinearity between two variables in R 0:03:49 How to create a confidence interval for the model coefficients in R? using the "confint" function 0:03:57 How to interpret the confidence interval for our model's coefficients in R 0:04:13 How to fit a linear model using all of the X variables in R 0:04:27 how to check the linear regression model assumptions in R? by examining plots of the residuals or errors using the "plot(model)" function ►► Watch More: ►Linear Regression Concept and with R https://bit.ly/2z8fXg1 ►R Tutorials for Data Science https://bit.ly/1A1Pixc ►Getting Started with R (Series 1): https://bit.ly/2PkTneg ►Graphs and Descriptive Statistics in R (Series 2): https://bit.ly/2PkTneg ►Probability distributions in R (Series 3): https://bit.ly/2AT3wpI ►Bivariate analysis in R (Series 4): https://bit.ly/2SXvcRi ►Linear Regression in R (Series 5): https://bit.ly/1iytAtm ►ANOVA Concept and with R https://bit.ly/2zBwjgL ►Linear Regression Concept and with R https://bit.ly/2z8fXg1 ► Intro to Statistics Course: https://bit.ly/2SQOxDH ►Statistics & R Tutorials: Step by Step https://bit.ly/2Qt075y This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support some courses at The University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
FinTree website link: http://www.fintreeindia.com FB Page link :http://www.facebook.com/Fin... This series of videos covers the following key areas: Multiple Regression Basics, Multiple Regression Equation, Estimated regression coefficients and their p-values Alternative Hypothesis, Hypothesis tests of regression coefficients Confidence interval for the population value of regression Predicted value for the depedendent variable F-statistic, R2 and adjusted R2 in Multiple Regression ANOVA table Types of heterosketdasticity Multicollinearity, We love what we do, and we make awesome video lectures for CFA and FRM exams. Our Video Lectures are comprehensive, easy to understand and most importantly, fun to study with! This Video lecture was recorded by our popular trainer for CFA, Mr. Utkarsh Jain, during one of his live CFA Level II Classes in Pune (India).
Views: 4526 FinTree
The data set used in this video is taken from my book 'Six Sigma Statistics using Minitab 17'. You can work along with the video by downloading the data set from www.rmksixsigma.com.
Views: 8447 RMK Six Sigma
For introductory statistics. Apologies for the background music, and for the fact that I will never have time to re-record this. The dataset can be found here: https://drive.google.com/file/d/12wk1zlFiJmw6d1gUm3Dh4TORkE2cWt97/view?usp=sharing It orginates from "Introduction to Linear Regression Analysis" by Montgomery, et. al.
Views: 52956 Matthias Kullowatz
Predicting a quantittive outcome from 2+ predictior variables while controlling for potential confounding-covariate variables.
Views: 851 Arthur Bangert
Views: 85390 weislearners
Multiple Regression Intro video series: (4 parts) part 1: https://www.youtube.com/watch?v=e0o7oINrWuI&feature=youtu.be part 2: https://www.youtube.com/watch?v=bTUrTObthug&feature=youtu.be part 3: https://www.youtube.com/watch?v=46biqSoZxqY&feature=youtu.be part 4: https://www.youtube.com/watch?v=JhMrgo97YHA&feature=youtu.be Performing Multiple Regression in Microsoft Excel: https://www.youtube.com/watch?v=cXiZ_t2NK1k&index=18&list=PLjPbBibKHH1_FxwPpGxBeUAu_o87fFYoQ Performing a Multiple Regression in Google Sheets with XL Miner: https://www.youtube.com/watch?v=YhBU92eyNRo&feature=youtu.be
Views: 15026 Jalayer Academy
I demonstrate how to perform a linear regression analysis in SPSS. The data consist of two variables: (1) independent variable (years of education), and (2) dependent variable (weekly earnings). It was hypothesized that years of education would be positively associated with weekly earnings. Additionally, the slope (unstandardized beta weight) and intercept (value of Y when X is 0) were identified and interpreted.
Views: 509378 how2stats
Currell: Scientific Data Analysis. Analysis for Fig 9.10(a) http://ukcatalogue.oup.com/product/9780198712541.do © Oxford University Press
This video gives a quick overview of constructing a multiple regression model using R to estimate vehicles price based on their characteristics. The video focuses on how to employ a method of improving a linear model, and thus its linear equation, by stepwise regression with backward elimination of variables. It will demonstrate the process of building a model by starting with all candidate predictors and eliminating them one by one to optimize the model. The lesson also explains how to guide this optimization process by relying on the measures of model quality, such as R-Squared and Adjusted R-Squared statistics, and how to assess the variables usefulness to the model by judging their p-values, which represent the confidence in their coefficients which are to be used in the linear equation. The final model will be evaluated by calculating the correlation between the predicted and actual vehicle price for both the training and validation data sets. The explanation will be quite informal and will avoid the more complex statistical concepts. Note that a more complex process of building a multiple linear model, with details of variables transformation, checking for their multiple collinearity and extreme values, will be explained in the next lesson. The data for this lesson can be obtained from the well-known UCI Machine Learning archives: * https://archive.ics.uci.edu/ml/datasets/automobile The R source code for this video can be found here (some small discrepancies are possible): * http://visanalytics.org/youtube-rsrc/r-stats/Demo-D1-Multiple-Reg-Var-Selection.r Videos in data analytics and data visualization by Jacob Cybulski, visanalytics.org.
Views: 48491 ironfrown
Dummy coding for multiple regression in SPSS For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below: Introductory statistics: https://sites.google.com/view/statisticsfortherealworldagent/home Multivariate statistics: https://sites.google.com/view/statistics-for-the-real-world/home
Views: 23558 Mike Crowson
Learn how to conduct multiple linear regression using Excel data analysis toolpak
Views: 111337 KnowledgeVarsity
Simple Linear Regression using Microsoft Excel
Views: 276710 Jalayer Academy
This video moves us from simple linear regression to multiple regression. I discuss the differences introduced by increasing the number of regressors, and we cover: - the multiple regression model - the regression equation and estimated regression equation - the least-squares approach - the SST, SSE, and SSR - the R-squared and adjusted R-squared
Views: 128742 Jason Delaney
Views: 7962 Statistics
The concepts behind linear regression, fitting a line to data with least squares and R-squared, are pretty darn simple, so let's get down to it! NOTE: This StatQuest comes with a companion video for how to do linear regression in R: https://youtu.be/u1cc1r_Y7M0 You can also find example code at the StatQuest website: https://statquest.org/2017/07/25/statquest-linear-regression-aka-glms-part-1/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/
How to use R to calculate multiple linear regression. http://www.MyBookSucks.Com/R/Multiple_Linear_Regression.R http://www.MyBookSucks.Com/R Playlist on on Understanding Multiple Linear Regression Results (Watch videos 2 - 4) http://www.youtube.com/playlist?list=PLWtoq-EhUJe2Z8wz0jnmrbc6S3IwoUPgL
Views: 56875 statisticsfun