Scale statistics | Non-Newtonian calculus
In probability theory and statistics, the geometric standard deviation (GSD) describes how spread out are a set of numbers whose preferred average is the geometric mean. For such data, it may be preferred to the more usual standard deviation. Note that unlike the usual arithmetic standard deviation, the geometric standard deviation is a multiplicative factor, and thus is dimensionless, rather than having the same dimension as the input values. Thus, the geometric standard deviation may be more appropriately called geometric SD factor. When using geometric SD factor in conjunction with geometric mean, it should be described as "the range from (the geometric mean divided by the geometric SD factor) to (the geometric mean multiplied by the geometric SD factor), and one cannot add/subtract "geometric SD factor" to/from geometric mean. (Wikipedia).
How to calculate Mean and Standard Deviation
A review of average and standard deviation Like us on: http://www.facebook.com/PartyMoreStudyLess
From playlist Standard Deviation
The dispersion of data by means of the standard deviation.
From playlist Medical Statistics
Learning how to find the variance and standard deviation from a set of data
👉 Learn how to find the variance and standard deviation of a set of data. The variance of a set of data is a measure of spread/variation which measures how far a set of numbers is spread out from their average value. The standard deviation of a set of data is a measure of spread/variation
From playlist Variance and Standard Deviation
How to find the variance and standard deviation from a set of data
👉 Learn how to find the variance and standard deviation of a set of data. The variance of a set of data is a measure of spread/variation which measures how far a set of numbers is spread out from their average value. The standard deviation of a set of data is a measure of spread/variation
From playlist Variance and Standard Deviation
How to find the number of standard deviations that it takes to represent all the data
👉 Learn how to find the variance and standard deviation of a set of data. The variance of a set of data is a measure of spread/variation which measures how far a set of numbers is spread out from their average value. The standard deviation of a set of data is a measure of spread/variation
From playlist Variance and Standard Deviation
How To Calculate The Standard Deviation In Excel
This video tutorial explains how to calculate the standard deviation in excel. It also discusses the concept of standard deviation which is the dispersion or variability of the data around the mean.
From playlist Excel Tutorial
Measuring Variation: Range and Standard Deviation
This lesson explains how to determine the range and standard deviation for a set of data. Site: http://mathispower4u.com
From playlist Statistics: Describing Data
Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
https://www.patreon.com/ProfessorLeonard Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
From playlist Statistics (Full Length Videos)
Standard Deviation and Variance (Explaining Formulas)
Step by Step tutorial on how to calculate the standard deviation and variance for statistics class. Related Videos Play List On Standard Deviation http://www.youtube.com/playlist?list=PLWtoq-EhUJe3sQoAWPiLi0M75HUAmOjbx Calculating Standard Deviation And Variance Using Excel http://you
From playlist Standard Deviation
Level 1 Chartered Financial Analyst (CFA ®): Measures of dispersion including volatility
Session 2, Reading 8 (Part 2): A previous video in this CFA playlist looked at classic measures of central tendency. This is also called the first moment of the distribution or the distributions the location where is the distribution centered. When we say that I think most of us think of t
From playlist Level 1 Chartered Financial Analyst (CFA ®) Volume 1
Lecture 2 - Mathematical Preliminaries
This is Lecture 2 of the CSE519 (Data Science) course taught by Professor Steven Skiena [http://www.cs.stonybrook.edu/~skiena/] at Stony Brook University in 2016. The lecture slides are available at: http://www.cs.stonybrook.edu/~skiena/519 More information may be found here: http://www.
From playlist CSE519 - Data Science Fall 2016
Parametric Probability Distribution Fitted to Data with Bayes's Theorem
James Rock explains how he's using Bayes's Theorem to fit data to a parametric distribution with Mathematica in this talk from the Wolfram Technology Conference. For more information about Mathematica, please visit: http://www.wolfram.com/mathematica
From playlist Wolfram Technology Conference 2012
Python for Data Analysis: Probability Distributions
This video covers the basics of working with probability distributions in Python, including the uniform, normal, binomial, geometric, exponential and Poisson distributions. It also includes a discussion of random number generation and setting the random seed. Subscribe: â–º https://www.yout
From playlist Python for Data Analysis
Geometric Distribution: Probability, Mean, and Standard Deviation
This explains how to determine a probability, the mean, and standard deviation of a geometric distribution. http://mathispower4u.com
From playlist Geometric Probability Distribution
Geometric Setting & Distribution in Statistics
I introduce the Geometric Setting & Distribution in statistics and compare it to the Binomial Setting. This video includes setting up a PDF, examples of finding probabilities, and a non-example of a geometric setting. Find free review test, useful notes and more at http://www.mathplane.co
From playlist AP Statistics
Rasch measurement using user-friendly jMetrik | Powerful free software
jMetrik is a free, user-friendly, and open source psychometric software which runs on any Windows, Mac OSX, or Linux platforms that have a current version of Java. In this video, I demonstrate how to run a Rasch measurement on binary data and compare the output with Winsteps. There is sign
From playlist Item response theory
Lognormal property of stock prices assumed by Black-Scholes (FRM T4-10)
Although the Black-Scholes option pricing model makes several assumptions, the most important is the first assumption that stock prices follow a lognormal distribution (and that volatility is constant). Specifically, the model assumes that log RETURNS (aka, continuously compounded returns)
From playlist Valuation and RIsk Models (FRM Topic 4)
Ex: Calculate the Sample Standard Deviation
This video explains how to calculator the sample standard deviation of a data set. http://mathispower4u.com
From playlist Statistics: Describing Data