Statistical charts and diagrams
The probability plot correlation coefficient (PPCC) plot is a graphical technique for identifying the shape parameter for a distributional family that best describes the data set. This technique is appropriate for families, such as the Weibull, that are defined by a single shape parameter and location and scale parameters, and it is not appropriate or even possible for distributions, such as the normal, that are defined only by location and scale parameters. Many statistical analyses are based on distributional assumptions about the population from which the data have been obtained. However, distributional families can have radically different shapes depending on the value of the shape parameter. Therefore, finding a reasonable choice for the shape parameter is a necessary step in the analysis. In many analyses, finding a good distributional model for the data is the primary focus of the analysis. The technique is simply "plot the probability plot correlation coefficients for different values of the shape parameter, and choose whichever value yields the best fit". (Wikipedia).
Estimate the Correlation Coefficient Given a Scatter Plot
This video explains how to estimate the correlation coefficient given a scatter plot.
From playlist Performing Linear Regression and Correlation
This video explains how to find the correlation coefficient which describes the strength of the linear relationship between two variables x and y. My Website: https://www.video-tutor.net Patreon: https://www.patreon.com/MathScienceTutor Amazon Store: https://www.amazon.com/shop/theorga
From playlist Statistics
Ex: Matching Correlation Coefficients to Scatter Plots
This video provides several examples of how to match the value of a correlation coefficient to a scatter plot. Site: http://mathispower4u.com
From playlist TI-84: Regression on the Graphing Calculator
Scatterplots, Part 3: The Formula Behind the Correlation Coefficient
We use the Scatterplots & Correlation app to explain the formula behind the correlation coefficient. The app allows you to find and plot the z-scores, showing the 4 quadrants in which points on the scatterplot can fall.
From playlist Chapter 3: Relationships between two variables
Statistics: Ch 3 Bivariate Data (18 of 25) Predictive Value
Visit http://ilectureonline.com for more math and science lectures! We will learn the correlation coefficient, r, is is a good predictive value for determining the accuracy of the linear regression equation, y=mx+b. To donate: http://www.ilectureonline.com/donate https://www.patreon.com/
From playlist STATISTICS CH 3 BIVARIATE DATA
Covariance (12 of 17) Covariance Matrix wth 3 Data Sets and Correlation Coefficients
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will find the correlation coefficients of the 3 data sets form the previous 2 videos. Next video in this series can be seen at:
From playlist COVARIANCE AND VARIANCE
Covariance (9 of 17) What is the Correlation Coefficient?
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will calculate the correlation coefficients of 2 separate 2 data sets and graph the 2 graphs and see how the graphs corresponds t
From playlist COVARIANCE AND VARIANCE
05 Machine Learning: Multivariate Analysis
Some prerequisite multivariate analysis concepts to support machine learning workflows. Follow along with the demonstration workflow in Python: https://github.com/GeostatsGuy/PythonNumericalDemos/blob/master/SubsurfaceDataAnalytics_Multivariate.ipynb This is an undergraduate / graduate c
From playlist Machine Learning
08 Data Analytics: Correlation
Lecture on bivariate statistics and correlation.
From playlist Data Analytics and Geostatistics
Table of Contents: 01:19 - 1. Construct a scatterplot using ME and 02:04 - Scatterplot in Minitab Express 04:09 - 2. Identify the explanatory and response 06:35 - 3. Identify situations in which correlat 09:58 - 4. Compute Pearson r using Minitab Expre 15:28 - Correlation in
From playlist STAT 200 Video Lectures
Chapter 10.1 from "Introduction to Statistics, Think & Do" by Scott Stevens (http://www.StevensStats.com) Textbook from Publisher, $29.95 print, $9.95 PDF http://www.centerofmathematics.com/wwcomstore/index.php/thinkdov4-1.html Textbook from Amazon: https://amzn.to/2zJRCjL
From playlist Statistics Lecture Videos
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
Covariance (14 of 17) Covariance Matrix "Normalized" - Correlation Coefficient
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will find the “normalized” matrix (or the correlation coefficients) from the covariance matrix from the previous video using 3 sa
From playlist COVARIANCE AND VARIANCE
16 Data Analytics: Cosimulation
Lecture on cosimulation for spatial modeling with more than one variance at a time.
From playlist Data Analytics and Geostatistics
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
JASP - Multiple Linear Regression
Lecturer: Dr. Erin M. Buchanan Spring 2020 Finish out the regression series by checking out this video on multiple linear regression. This video follows our simple linear regression model from JASP! Learn more and find our documents on our OSF page: https://osf.io/t56kg/. Look at our bas
From playlist Learn JASP + Statistics
RELATIONSHIPS Between Variables: Standardized Covariance (7-1)
Correlation is a way of measuring the extent to which two variables are related. The term correlation is synonymous with “relationship.” Variables are related when changes in one variable are consistently associated with changes in another variable. Dr. Daniel reviews Variance, Covariance,
From playlist Correlation And Regression in Statistics (WK 07 - QBA 237)
Statistical Rethinking - Lecture 05
Lecture 05, Multivariate models, from Statistical Rethinking: A Bayesian Course with R Examples
From playlist Statistical Rethinking Winter 2015