Bivariate analysis is one of the simplest forms of quantitative (statistical) analysis. It involves the analysis of two variables (often denoted as X, Y), for the purpose of determining the empirical relationship between them. Bivariate analysis can be helpful in testing simple hypotheses of association. Bivariate analysis can help determine to what extent it becomes easier to know and predict a value for one variable (possibly a dependent variable) if we know the value of the other variable (possibly the independent variable) (see also correlation and simple linear regression). Bivariate analysis can be contrasted with univariate analysis in which only one variable is analysed. Like univariate analysis, bivariate analysis can be descriptive or inferential. It is the analysis of the relationship between the two variables. Bivariate analysis is a simple (two variable) special case of multivariate analysis (where multiple relations between multiple variables are examined simultaneously). (Wikipedia).
G*Power 3.1 Tutorial: Bivariate Regression Power Analysis (Episode 3)
In this episode, I explain how to complete a priori power analysis for a bivariate regression and discuss the several ways to calculate effect size if not known but other information is. G*Power 3.1 download: https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeits
From playlist G*Power 3.1 Tutorials
Evaluating the composition of cosine and sine inverse
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Four things to keep in mind about connectivity
This video lesson is part of a complete course on neuroscience time series analyses. The full course includes - over 47 hours of video instruction - lots and lots of MATLAB exercises and problem sets - access to a dedicated Q&A forum. You can find out more here: https://www.udemy.
From playlist NEW ANTS #4) Synchronization
Evaluate the composition of sine and sine inverse
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
05c Machine Learning: Feature Selection
Lecture on methods for feature selection for machine learning workflows. Follow along with the demonstration workflows in Python: o. Feature Selection / Ranking: https://github.com/GeostatsGuy/PythonNumericalDemos/blob/master/SubsurfaceDataAnalytics_Feature_Ranking.ipynb Subsurface Mach
From playlist Machine Learning
Evaluating the composition of sine and cosine functions
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Evaluating the composition of Functions
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
More resources available at www.misterwootube.com
From playlist Bivariate Data Analysis
Pearson's Correlations 2: Sorting output by groups
I this video, I will demonstrate how to sort output by groups in Pearson's Correlations. Data used in this demonstration is from the CORE2016 project (ID: OER29/15 CCY), the National Institute of Education, Nanyang Technological University, Singapore.
From playlist Pearson Correlation in SPSS
Intro to connectivity, volume conduction, and time- vs. trial-based connectivity
This lecturelet will introduce you to four considerations to keep in mind when performing or evaluating functional connectivity analyses with EEG/LFP data. For more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/
From playlist OLD ANTS #7) Connectivity
08 Data Analytics: Correlation
Lecture on bivariate statistics and correlation.
From playlist Data Analytics and Geostatistics
Feature Ranking and Selection Teacher: Dr. Michael Pyrcz For more webinars & events please checkout: http://daytum.io/events Website: https://www.daytum.io/ Twitter: https://twitter.com/daytum_io?lang=en LinkedIn: https://www.linkedin.com/company/35593451 Data Science Education for Ener
From playlist daytum Free Webinar Series
Learn how to evaluate the composition of a function and inverse function
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions
Statistical Rethinking Fall 2017 - week03 lecture06
Week 03, lecture 06 for Statistical Rethinking: A Bayesian Course with Examples in R and Stan, taught at MPI-EVA in Fall 2017. This lecture covers Chapter 5. Slides are available here: https://speakerdeck.com/rmcelreath Additional information on textbook and R package here: http://xcel
From playlist Statistical Rethinking Fall 2017