What is the definition of a geometric sequence
👉 Learn about sequences. A sequence is a list of numbers/values exhibiting a defined pattern. A number/value in a sequence is called a term of the sequence. There are many types of sequence, among which are: arithmetic and geometric sequence. An arithmetic sequence is a sequence in which
From playlist Sequences
Determining the sum of a geometric sum when there is no sum
👉 Learn how to find the geometric sum of a series. A series is the sum of the terms of a sequence. A geometric series is the sum of the terms of a geometric sequence. The formula for the sum of n terms of a geometric sequence is given by Sn = a[(r^n - 1)/(r - 1)], where a is the first term
From playlist Series
Learn about the geometric mean of numbers. The geometric mean of n numbers is the nth root of the product of the numbers. To find the geometric mean of n numbers, we first multiply the numbers and then take the nth root of the product.
From playlist Geometry - GEOMETRIC MEAN
How to determine the altitude by using the geometric mean
Learn about the geometric mean of numbers. The geometric mean of n numbers is the nth root of the product of the numbers. To find the geometric mean of n numbers, we first multiply the numbers and then take the nth root of the product.
From playlist Geometry - GEOMETRIC MEAN
How to determine the rule for a geometric sequence given two values
👉 Learn how to write the explicit formula for a geometric sequence. A sequence is a list of numbers/values exhibiting a defined pattern. A number/value in a sequence is called a term of the sequence. A geometric sequence is a sequence in which each term of the sequence is obtained by multi
From playlist Sequences
Excel Statistical Analysis 11: Geometric Mean to Calculate Average Compounding Rate per Period
Download Excel File: https://excelisfun.net/files/Ch03-ESA.xlsm Learn about what the geometric mean is and how to use it. Great Historical Microsoft Stock Price Example. Topics: 1. (00:00) Introduction 2. (00:37) Define Geometric Mean 3. (01:09) Look at variable in the formulas for calcula
From playlist Excel Statistical Analysis for Business Class Playlist of Videos from excelisfun
Determine if a sequence is geometric or not
👉 Learn how to determine if a sequence is arithmetic, geometric, or neither. A sequence is a list of numbers/values exhibiting a defined pattern. A number/value in a sequence is called a term of the sequence. There are many types of sequence, among which are: arithmetic and geometric seque
From playlist Sequences
Determine if a sequence is geometric or not
👉 Learn how to determine if a sequence is arithmetic, geometric, or neither. A sequence is a list of numbers/values exhibiting a defined pattern. A number/value in a sequence is called a term of the sequence. There are many types of sequence, among which are: arithmetic and geometric seque
From playlist Sequences
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
James Arthur: The Langlands program: arithmetic, geometry and analysis
Abstract: As the Abel Prize citation points out, the Langlands program represents a grand unified theory of mathematics. We shall try to explain in elementary terms what this means. We shall describe an age old question concerning the arithmetic prime numbers, together with a profound gene
From playlist Abel Lectures
Lecture 13 - Financial Time Series Data
This is Lecture 13 of the COMP510 (Computational Finance) course taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Hong Kong University of Science and Technology in 2008. The lecture slides are available at: http://www.algorithm.cs.sunysb.edu/computationalfinance/pd
From playlist COMP510 - Computational Finance - 2007 HKUST
Qing Qu: "Landscape Analysis for Overcomplete Tensor and Neural Collapse"
Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop IV: Efficient Tensor Representations for Learning and Computational Complexity "Landscape Analysis for Overcomplete Tensor and Neural Collapse" Qing Qu - University of Michigan, Center for Data Scienc
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
Ming Ng - Adelic Geometry via Topos Theory
Talk at the school and conference “Toposes online” (24-30 June 2021): https://aroundtoposes.com/toposesonline/ Slides: https://aroundtoposes.com/wp-content/uploads/2021/07/NgSlidesToposesOnline.pdf Joint work with Steve Vickers In this talk, I will give a leisurely introduction to the t
From playlist Toposes online
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: ► https://www.yout
From playlist Python for Data Analysis
How to determine the sum of an finite geometric series
👉 Learn how to find the geometric sum of a series. A series is the sum of the terms of a sequence. A geometric series is the sum of the terms of a geometric sequence. The formula for the sum of n terms of a geometric sequence is given by Sn = a[(r^n - 1)/(r - 1)], where a is the first term
From playlist Series
Parvaneh Joharinad (7/27/22): Curvature of data
Abstract: How can one determine the curvature of data and how does it help to derive the salient structural features of a data set? After determining the appropriate model to represent data, the next step is to derive the salient structural features of data based on the tools available for
From playlist Applied Geometry for Data Sciences 2022
Elisabeth Gassiat - Manifold Learning with Noisy Data
It is a common idea that high dimensional data (or features) may lie on low dimensional support making learning easier. In this talk, I will present a very general set-up in which it is possible to recover low dimensional non-linear structures with noisy data, the noise being totally unkno
From playlist 8th edition of the Statistics & Computer Science Day for Data Science in Paris-Saclay, 9 March 2023
An introduction to the idea of Dimensional Analysis
From playlist Mathematical Physics I Uploads