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R: Exploratory Data Analysis (EDA), Multivariate Analysis
 
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One of the first steps to data analysis is to perform Exploratory Data Analysis. In this video we go over the basics of multivariate data analysis, or analyzing the relationship between variables Here's the dataset used in this video: https://drive.google.com/open?id=0B67hcgV97X0mbnRYNzhYLU53X2c
Views: 7270 James Dayhuff
Multivariate Statistical Analysis Part I: Introduction and Mean Comparison (with R demonstration)
 
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For this seminar, I will take you through a general introduction of multivariate analysis and perform an R demonstration of a simple multivariate analysis: mean comparison.
Views: 1538 RenaissanceWoman
R - Multiple Regression (part 1)
 
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Introduction to multiple regression in r. The data set is discussed and exploratory data analysis is performed here using correlation matrix and scatterplot matrix.
Views: 38093 Jalayer Academy
R - Exploring Data (part 5) - Multivariate Summaries
 
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We explore some multivariate descriptive tools here. Scatterplot matrix, side-by-side boxplot, two-way crosstab, correlation matrix, and more.
Views: 10091 Jalayer Academy
Principal Components Analysis Using R - P1
 
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See my new blog at http://rollingyours.wordpress.com Get code used in this video from: https://raw.githubusercontent.com/steviep42/youtube/master/YOUTUBE.DIR/BB_phys_stats_ex1.R Best Viewed in Large or Full Screen Mode Part 1 - This video tutorial guides the user through a manual principal components analysis of some simple data. The goal is to acquaint the viewer with the underlying concepts and terminology associated with the PCA process. This will be helpful when the user employs one of the "canned" R procedures to do PCA (e.g. princomp, prcomp), which requires some knowledge of concepts such as loadings and scores.
Views: 137612 Steve Pittard
Multiple Linear Regression in R (R Tutorial 5.3)
 
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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" commands. You will also learn the "plot" command for producing residual and QQ plots. It will be helpful to first review our video on simple linear regression. The video provides a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topic addressed in this video: 0:00:07 why use Multiple Linear Regression Model 0:00:32 using the "lm" command to fit a linear model 0:00:36 how to access the help menu in R for multiple linear regression by typing "help" 0:01:06 fitting a linear regression model using Age and Height as the explanatory or X variables 0:01:19 producing and interpreting the summary of linear regression model fit in R 0:03:16 how to calculate Pearson's correlation between the two variables 0:03:26 how to interpret the collinearity between two variables 0:03:49 how to create a confidence interval for the model coefficients using the "confint" command 0:03:57 interpreting the confidence interval for our model's coefficients 0:04:13 fitting a linear model using all of the X variables 0:04:27 how to check the model assumptions by examining plots of the residuals or errors using the "plot(model)" command
Introduction to Multivariate Analysis
 
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Paper: Multivariate Analysis Module name: Introduction toMultivariate Analysis Content Writer: Souvik Bandyopadhyay
Views: 55272 Vidya-mitra
R Stats: Multiple Regression - Variable Selection
 
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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: 46117 ironfrown
Multivariate Statistical Analysis Part 2:  MANOVA (with R Demonstration)
 
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For this video, I will give you the background theory and perform R demonstrations for one-way and factorial Multivariate Analysis of Variance (MANOVA). MANOVA is used for comparing mean vectors containing the means of multiple outcome variables between more group variables with more than 2 categories. It's the multivariate extension of the ANOVA. For more details of the 4 Statistics: https://onlinecourses.science.psu.edu/stat505/node/163 Calculate the F approximation of the 4 statistics: https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_introreg_sect012.htm Like Me On FB: https://www.facebook.com/RenaissanceMonaLisa/?pnref=lhc
Views: 1439 RenaissanceWoman
Multivariate Data - Data Analysis with R
 
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This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 2601 Udacity
Multivariate Test of normality - Mardia, Henze - Zirkler, Royston test using R / R studio
 
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Multivariate Test of normality - Mardia, Henze - Zirkler, Royston test using R / R studio Website: http://www.iamsulthan.in Facebook page: https://www.facebook.com/www.iamsulthan.in Twitter:https://twitter.com/sulthankhan LinkedIn: https://in.linkedin.com/in/sulthan-a-6502a446 Google plus: https://plus.google.com/u/0/114871954491126528103 YouTube: https://www.youtube.com/channel/UCvSmgyIUCxxgoHKlwutH7kQ Fb profile page:https://www.facebook.com/iamsulthan.in Instagram: https://www.instagram.com/iamsulthan/ Research Gate: https://www.researchgate.net/profile/sulthan_a2 Google scholar: https://scholar.google.co.in/citations?hl=en&user=nwM3-60AAAAJ Academia: https://jmc.academia.edu/IamSulthan Scopus: https://www.scopus.com/authid/detail.uri?authorId=56127320100 Orcid: http://orcid.org/0000-0003-4379-9046
Views: 1817 Sulthan's Monologue
Session 6 Applied Multivariate statistics - Multivariate hypothesis testing - Demonstration in R
 
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This is the demonstration part related to the Session 6 of the lecture "Applied Multivariate Statistics for Environmental Scientists" that was held at the University Koblenz-Landau, Campus Landau. The demonstration relies on free open source software (R) and can therefore be followed by anyone. The topic of this session is multivariate hypothesis testing. For more information go to the website: https://www.uni-koblenz-landau.de/en/campus-landau/faculty7/environmental-sciences/landscape-ecology/Teaching/r-statistics
Views: 662 Ralf Schaefer
Session 5 Applied Multivariate statistics RDA - Demonstration in R
 
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This is the demonstration part related to the Session 5 of the lecture "Applied Multivariate Statistics for Environmental Scientists" that was held at the University Koblenz-Landau, Campus Landau. The demonstration relies on free open source software (R) and can therefore be followed by anyone. The topic of this session is Redundancy Analysis. For more information go to the website: https://www.uni-koblenz-landau.de/en/campus-landau/faculty7/environmental-sciences/landscape-ecology/Teaching/r-statistics
Views: 3195 Ralf Schaefer
Multiple Linear Regression Using R
 
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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: 51812 statisticsfun
Exploratory Factor Analysis in R
 
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This video tutorial will show you how to conduct an Exploratory factor analysis in R. This is an intermediate level video. You should know how to read data into R, conduct and understand PCA before watching this video.
Views: 40762 Ed Boone
Multivariate Statistical Analysis Part 3: MANCOVA (with R Demonstration)
 
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This is the 3rd part of my Multivariate Statistical Analysis video series on Multivariate Analysis of Covariance (MANCOVA). MANCOVA is a method for looking at if the means of the multiple outcome variables between each group (specified by the group variable) are statistically different while controlling for a covariate which can influence the outcome but is not of study interest. Like Me On FB: https://www.facebook.com/RenaissanceMonaLisa/
Views: 651 RenaissanceWoman
Multiple Linear Regression in R
 
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This video provides a simple example of doing multiple linear regression analysis in R and includes, - developing a linear model - comparing full and reduced model using ANOVA - Prediction - Confidence interval R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 28006 Bharatendra Rai
Session 5 Applied Multivariate statistics Similarity measures and NMDS - Demonstration in R
 
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This is the demonstration part related to the Session 5 of the lecture "Applied Multivariate Statistics for Environmental Scientists" that was held at the University Koblenz-Landau, Campus Landau. The demonstration relies on free open source software (R) and can therefore be followed by anyone. The topic of this session is similarity measures and non-metric multidimensional scaling (NMDS). For more information go to the website: https://www.uni-koblenz-landau.de/en/campus-landau/faculty7/environmental-sciences/landscape-ecology/Teaching/r-statistics
Views: 3171 Ralf Schaefer
Mahalanobis Distance - Outlier Detection for Multivariate Statistics in R
 
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Mahalanobis Distance - Outlier Detection for Multivariate Statistics in R
Views: 4214 Dragonfly Statistics
Learning R in RStudio: Multiple Regression and Team Batting Performance
 
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An introduction to multiple regression using the mtcars data frame and then application to improvement of OPS to predict batting performance. We also use multiple regression to determine the value of different types of hits, walks, stolen bases and outs (Linear Weights).
Views: 5786 R at Colby
Linear Discriminant Analysis in R
 
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This video tutorial shows you how to use the lad function in R to perform a Linear Discriminant Analysis. It also shows how to do predictive performance and cross validation of the Linear Discriminant Analysis. This is an intermediate video. You should feel comfortable reading data in, subsetting data, regression or anova in R.
Views: 48079 Ed Boone
Session 2 Applied Multivariate Statistics Multiple Regression R demo
 
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R demo related to the session 2 of the lecture "Applied Multivariate Statistics for Environmental Scientists". University Koblenz-Landau, Campus Landau in Germany, winter semester 2016/17. The topic of this session is Multiple Linear Regression and includes methods and strategies, including modern approaches such as the LASSO. For more information go to the website: https://www.uni-koblenz-landau.de/en/campus-landau/faculty7/environmental-sciences/landscape-ecology/Teaching/r-statistics
Views: 1400 Ralf Schaefer
Session 5 Applied Multivariate statistics - RDA, similarity measures and NMDS
 
01:15:24
Session 5 of the lecture "Applied Multivariate Statistics for Environmental Scientists". The lecture relies on free open source software (R) and can therefore be followed by anyone. The topic of this session is Redundancy Analysis, similarity measures and non-metric multidimensional scaling (NMDS). For more information go to the website: https://www.uni-koblenz-landau.de/en/campus-landau/faculty7/environmental-sciences/landscape-ecology/Teaching/r-statistics
Views: 5442 Ralf Schaefer
StatQuest: Multiple Regression in R
 
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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/
02417 Lecture 10 part A: Marima package in R for multivariate ARMA models
 
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This is part of the course 02417 Time Series Analysis as it was given in the fall of 2017 and spring 2018. The full playlist is here: https://www.youtube.com/playlist?list=PLtiTxpFJ4k6TZ0g496fVcQpt_-XJRNkbi You can download the slides here: https://drive.google.com/drive/folders/1OYamq8_PONteNHEdgkEG-jLvraeaGOp6?usp=sharing The course is based on the book: Time Series Analysis by Henrik Madsen: http://henrikmadsen.org/books/time-series-analysis/
Session 6 Applied Multivariate statistics PERMANOVA (by Eduard Szöcs)
 
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Session 6 of the lecture "Applied Multivariate Statistics for Environmental Scientists" that was held at the University Koblenz-Landau, Campus Landau in Germany in the winter semester 2015/2016. The lecture relies on free open source software (R) and can therefore be followed by anyone. The topic of this session is permutational multivariate analysis of variance (PERMANOVA). By Eduard Szöcs. For more information go to the website: https://www.uni-koblenz-landau.de/en/campus-landau/faculty7/environmental-sciences/landscape-ecology/Teaching/r-statistics
Views: 5693 Ralf Schaefer
Session 4 Applied Multivariate statistics Principal component analysis demonstration in R
 
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This is the demonstration part related to the Session 4 of the lecture "Applied Multivariate Statistics for Environmental Scientists" that was held at the University Koblenz-Landau, Campus Landau. The demonstration relies on free open source software (R) and can therefore be followed by anyone. The topic of this session is Introduction to multivariate analysis and Principal Component Analysis (PCA). For more information go to the website: https://www.uni-koblenz-landau.de/en/campus-landau/faculty7/environmental-sciences/landscape-ecology/Teaching/r-statistics
Views: 699 Ralf Schaefer
Principal Component Analysis and Factor Analysis in R
 
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Principal Component Analysis and Factor Analysis in R https://sites.google.com/site/econometricsacademy/econometrics-models/principal-component-analysis
Views: 98254 econometricsacademy
Simulation of Multivariate Normal Distribution in R
 
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Generating Multivariate Normal Distribution in R Install Package "MASS" Create a vector mu. mu is a vector of means. mu=c(2,3) Create a matrix sigma that is variance-covariance matrix of variables. This matrix is a positive definite symmetric matrix. sigma=matrix(c(9,6,6,16),2,2) #A 2x2 matrix Now we can generate two variables having correlation=0.5, variance(1)=9, Variance(2)=16, Covariance=6. (No. of variables is order of sigma matrix i.e 2 here) variables=mvrnorm(1000,mu,sigma) produces 1000 observations of 2 normally distributed variables with predefined mu and sigma
Views: 16130 Sarveshwar Inani
Tableau 8.1: Predictive Analytics with R
 
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The release of Tableau 8.1 included capability for connecting Tableau to R for performing complex statistical analysis right within Tableau. This video will focus on predictive analytics, specifically multivariate regression. See how R can be used in conjunction with Tableau for performing regression analysis using multiple variables for better predictive modeling.
Views: 49828 ThorogoodBI
boral: R package for multivariate data analysis in Ecology
 
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boral is an R package designed for Bayesian analysis of multivariate data (e.g., community composition data) in ecology. UPDATE June 2016: - There is a software article now on boral, available on the Methods in Ecology and Evolution website: http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12514/full - A second video discussing some of the updates to boral that have been made since 2014 can be found here: https://www.youtube.com/watch?v=XmrVVMG1HXI Check it out: http://cran.r-project.org/web/package... Disclaimer: I am in no way affiliated with the construction company in Australia also known as BORAL, although my voice is probably as dry as their cement =P
Views: 5383 Francis Hui
What are Multivariate Time Series Models
 
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Multivariate time series models are different from that of Univariate Time Series models in a way that it also takes structural forms that is it includes lags of different time series variable apart from the lags of it's own. For Study Packs Visit : http://analyticuniversity.com/
Views: 24309 Analytics University
Testing Multivariate Normality using R [Bengali]
 
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This video explains how to test multivariate normality assumption of data-set/ a group of variables using R software. Two formal tests along with Q-Q plot are also demonstrated. #Research #Academia #Multivariate #Univariate #Normality #Test #Normal #Distribution #Bengali #Bangladesh #West-Bengal #Education #Statistics #Econometric #Economics #Mardia #Henze-Zirkler #Q-Q #plot #Standard #R #Codes install.packages("MVN") library(MVN) describe(dataset) hist(dataset) #multivariate normality test #mardia test result=mardiaTest(dataset, qqplot=TRUE) result #Henze-Zirkler test result=hzTest(dataset, qqplot=TRUE) result #bonus #univariate plots uniPlot(dataset, type="qqplot") #creates univariate Q-Q plots uniPlot(dataset, type="histogram") #creates univariate histograms
Views: 2391 Research HUB
Logistic Regression in R, Clearly Explained!!!!
 
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This video describes how to do Logistic Regression in R, step-by-step. We start by importing a dataset and cleaning it up, then we perform logistic regression on a very simple model, followed by a fancy model. Lastly we draw a graph of the predicted probabilities that came from the Logistic Regression. The code that I use in this video can be found on the StatQuest website: https://statquest.org/2018/07/23/statquest-logistic-regression-in-r/#code For more details on what's going on, check out the following StatQuests: For a general overview of Logistic Regression: https://youtu.be/yIYKR4sgzI8 The odds and log(odds), clearly explained: https://youtu.be/ARfXDSkQf1Y The odds ratio and log(odds ratio), clearly explained: https://youtu.be/8nm0G-1uJzA Logistic Regression, Details Part 1, Coefficients: https://youtu.be/vN5cNN2-HWE Logistic Regression, Details Part 2, Fitting a line with Maximum Likelihood: https://youtu.be/BfKanl1aSG0 Logistic Regression Details Part 3, R-squared and its p-value: https://youtu.be/xxFYro8QuXA Saturated Models and Deviance Statistics, Clearly Explained: https://youtu.be/9T0wlKdew6I Deviance Residuals, Clearly Explained: https://youtu.be/JC56jS2gVUE 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/
Multivariate Statistical Anlaysis in Water Quality
 
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Multivariate statistical techniques are the application of statistics to simultaneous observations and can include the analysis of more than one outcome (dependent) variable. Good multivariate analysis starts with exploratory and graphical analyses to reveal potential relations in the data and to highlight potential outliers. First, this presentation will discuss how to extend univariate and bivariate methods for graphical analysis to multivariate data, as well as methods unique to multivariate data. Second, multivariate outlier detection will be presented. Third, there will be a brief discussion of multivariate statistical analysis methods, such as multiple regression, principal component analysis, and cluster analysis, including examples and suggestions as to when one might want to use these techniques.
StatQuest: Principal Component Analysis (PCA) clearly explained (2015)
 
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NOTE: On April 2, 2018 I updated this video with a new video that goes, step-by-step, through PCA and how it is performed. Check it out! https://youtu.be/FgakZw6K1QQ RNA-seq results often contain a PCA or MDS plot. This StatQuest explains how these graphs are generated, how to interpret them, and how to determine if the plot is informative or not. I've got example code (in R) for how to do PCA and extract the most important information from it on the StatQuest website: https://statquest.org/2015/08/13/pca-clearly-explained/ 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/
Multivariate Analysis (HRM)
 
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Subject:Human Resource Management Paper: Research Methodology
Views: 3449 Vidya-mitra
Univariate, Bivariate and Multivariate analysis EDA Lecture 13@Applied AI Course
 
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for more details visit the following link https://www.appliedaicourse.com/course/applied-ai-course/lessons/summarizing-plots-univariate-bivariate-and-multivariate-analysis-1/
Views: 4621 Applied AI Course
Stata: Multivariate Statistics – General Explanatory Modeling
 
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Topics: Manual backward stepwise logistic regression
Views: 10850 Dana R Thomson
Time Series In R | Time Series Forecasting | Time Series Analysis | Data Science Training | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) In this Edureka YouTube live session, we will show you how to use the Time Series Analysis in R to predict the future! Below are the topics we will cover in this live session: 1. Why Time Series Analysis? 2. What is Time Series Analysis? 3. When Not to use Time Series Analysis? 4. Components of Time Series Algorithm 5. Demo on Time Series For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 72069 edureka!
Factoshiny: interactive graphs in exploratory multivariate data analysis
 
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How to use Factoshiny, the library that allows us to use FactoMineR with a graphical user interface and that allow us to make interactive graphs.
Views: 5207 François Husson
How to Calculate Multiple Linear Regression with SPSS
 
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Tutorial on how to calculate Multiple Linear Regression using SPSS. I show you how to calculate a regression equation with two independent variables. I also show you how to create a Pearson r correlation matrix using output from SPSS. Playlist on Using SPSS For Multiple Linear Regression http://www.youtube.com/playlist?list=PLWtoq-EhUJe2Z8wz0jnmrbc6S3IwoUPgL Like MyBookSucks on Facebook at http://www.MyBookSucks.Com/PartyMoreStudyLess Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 189931 statisticsfun

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