Mpc 006 - 02-01 product moment coefficient of correlationVasant Kothari
1.2 Correlation: Meaning and Interpretation
1.2.1 Scatter Diagram: Graphical Presentation of Relationship
1.2.2 Correlation: Linear and Non-Linear Relationship
1.2.3 Direction of Correlation: Positive and Negative
1.2.4 Correlation: The Strength of Relationship
1.2.5 Measurements of Correlation
1.2.6 Correlation and Causality
1.3 Pearson’s Product Moment Coefficient of Correlation
1.3.1 Variance and Covariance: Building Blocks of Correlations
1.3.2 Equations for Pearson’s Product Moment Coefficient of Correlation
1.3.3 Numerical Example
1.3.4 Significance Testing of Pearson’s Correlation Coefficient
1.3.5 Adjusted r
1.3.6 Assumptions for Significance Testing
1.3.7 Ramifications in the Interpretation of Pearson’s r
1.3.8 Restricted Range
1.4 Unreliability of Measurement
1.4.1 Outliers
1.4.2 Curvilinearity
1.5 Using Raw Score Method for Calculating r
1.5.1 Formulas for Raw Score
1.5.2 Solved Numerical for Raw Score Formula
2.2 Special types of Correlation
2.3 Point Biserial Correlation rPB
2.3.1 Calculation of rPB
2.3.2 Significance Testing of rPB
2.4 Phi Coefficient (φ )
2.4.1 Significance Testing of phi (φ )
2.5 Biserial Correlation
2.6 Tetrachoric Correlation
2.7 Rank Order Correlations
2.7.1 Rank-order Data
2.7.2 Assumptions Underlying Pearson’s Correlation not Satisfied
2.8 Spearman’s Rank Order Correlation or Spearman’s rho (rs)
2.8.1 Null and Alternate Hypothesis
2.8.2 Numerical Example: for Untied and Tied Ranks
2.8.3 Spearman’s Rho with Tied Ranks
2.8.4 Steps for rS with Tied Ranks
2.8.5 Significance Testing of Spearman’s rho
2.9 Kendall’s Tau (ô)
2.9.1 Null and Alternative Hypothesis
2.9.2 Logic of Kendall’s Tau and Computation
2.9.3 Computational Alternative for Kendall’s Tau
2.9.4 Significance Testing for Kendall’s Tau
Mpc 006 - 02-01 product moment coefficient of correlationVasant Kothari
1.2 Correlation: Meaning and Interpretation
1.2.1 Scatter Diagram: Graphical Presentation of Relationship
1.2.2 Correlation: Linear and Non-Linear Relationship
1.2.3 Direction of Correlation: Positive and Negative
1.2.4 Correlation: The Strength of Relationship
1.2.5 Measurements of Correlation
1.2.6 Correlation and Causality
1.3 Pearson’s Product Moment Coefficient of Correlation
1.3.1 Variance and Covariance: Building Blocks of Correlations
1.3.2 Equations for Pearson’s Product Moment Coefficient of Correlation
1.3.3 Numerical Example
1.3.4 Significance Testing of Pearson’s Correlation Coefficient
1.3.5 Adjusted r
1.3.6 Assumptions for Significance Testing
1.3.7 Ramifications in the Interpretation of Pearson’s r
1.3.8 Restricted Range
1.4 Unreliability of Measurement
1.4.1 Outliers
1.4.2 Curvilinearity
1.5 Using Raw Score Method for Calculating r
1.5.1 Formulas for Raw Score
1.5.2 Solved Numerical for Raw Score Formula
2.2 Special types of Correlation
2.3 Point Biserial Correlation rPB
2.3.1 Calculation of rPB
2.3.2 Significance Testing of rPB
2.4 Phi Coefficient (φ )
2.4.1 Significance Testing of phi (φ )
2.5 Biserial Correlation
2.6 Tetrachoric Correlation
2.7 Rank Order Correlations
2.7.1 Rank-order Data
2.7.2 Assumptions Underlying Pearson’s Correlation not Satisfied
2.8 Spearman’s Rank Order Correlation or Spearman’s rho (rs)
2.8.1 Null and Alternate Hypothesis
2.8.2 Numerical Example: for Untied and Tied Ranks
2.8.3 Spearman’s Rho with Tied Ranks
2.8.4 Steps for rS with Tied Ranks
2.8.5 Significance Testing of Spearman’s rho
2.9 Kendall’s Tau (ô)
2.9.1 Null and Alternative Hypothesis
2.9.2 Logic of Kendall’s Tau and Computation
2.9.3 Computational Alternative for Kendall’s Tau
2.9.4 Significance Testing for Kendall’s Tau
Mpc 006 - 02-03 partial and multiple correlationVasant Kothari
3.2 Partial Correlation (rp)
3.2.1 Formula and Example
3.2.2 Alternative Use of Partial Correlation
3.3 Linear Regression
3.4 Part Correlation (Semipartial correlation) rsp
3.4.1 Semipartial Correlation: Alternative Understanding
3.5 Multiple Correlation Coefficient (R)
Basic Mathematics (non-calculus) for k-12 students in B.C. Canada. Intended as a guide for teaching basic math to young learners, and uploaded as a personal favor to my friend Oliver Cougur. This is a supplement teaching/learning material, and functions as a 'cheat sheet' for instructors and/or students.
This is not intended as curriculum material. I guarantee nothing. I claim no ownership or discovery of any of the material in this document, however I reserve my right of creative expression for materials contained. This document may not be sold, copied or altered in anyway by anyone.
Please report any errors to s.grantwilliam@ieee.org
Helmholtz equation (Motivations and Solutions)Hassaan Saleem
Solutions of Helmholtz equation in cartesian, cylindrical and spherical coordinates are discussed and the applications to the problem of a quantum mechanical particle in a cubical box is discussed.
IOSR Journal of Mathematics(IOSR-JM) is an open access international journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Basic concepts of integration, definite and indefinite integrals,properties of definite integral, problem based on properties,method of integration, substitution, partial fraction, rational , irrational function integration, integration by parts, reduction formula, improper integral, convergent and divergent of integration
Every material has certain strength, expressed in terms of stress or strain, beyond which it
fractures or fails to carry the load. Failure Criterion: A criterion used to hypothesize the failure.
Failure Theory: A Theory behind a failure criterion.
Need of Failure Theories:
(a) To design structural components and calculate margin of safety.
(b) To guide in materials development.
(c) To determine weak and strong directions.
PROBABILITY DISTRIBUTION OF SUM OF TWO CONTINUOUS VARIABLES AND CONVOLUTIONJournal For Research
All physical subjects, involving random phenomena, something depending upon chance, naturally find their own way to theory of Statistics. Hence there arise relations between the results derived for hose random phenomena in different physical subjects and the concepts of Statistics. Convolution theorem has a variety of applications in field of Fourier transforms and many other situations, but it bears beautiful applications in field of statistics also .Here in this paper authors want to discuss some notions of Electrical Engineering in terms of convolution of some probability distributions.
Mpc 006 - 02-03 partial and multiple correlationVasant Kothari
3.2 Partial Correlation (rp)
3.2.1 Formula and Example
3.2.2 Alternative Use of Partial Correlation
3.3 Linear Regression
3.4 Part Correlation (Semipartial correlation) rsp
3.4.1 Semipartial Correlation: Alternative Understanding
3.5 Multiple Correlation Coefficient (R)
Basic Mathematics (non-calculus) for k-12 students in B.C. Canada. Intended as a guide for teaching basic math to young learners, and uploaded as a personal favor to my friend Oliver Cougur. This is a supplement teaching/learning material, and functions as a 'cheat sheet' for instructors and/or students.
This is not intended as curriculum material. I guarantee nothing. I claim no ownership or discovery of any of the material in this document, however I reserve my right of creative expression for materials contained. This document may not be sold, copied or altered in anyway by anyone.
Please report any errors to s.grantwilliam@ieee.org
Helmholtz equation (Motivations and Solutions)Hassaan Saleem
Solutions of Helmholtz equation in cartesian, cylindrical and spherical coordinates are discussed and the applications to the problem of a quantum mechanical particle in a cubical box is discussed.
IOSR Journal of Mathematics(IOSR-JM) is an open access international journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Basic concepts of integration, definite and indefinite integrals,properties of definite integral, problem based on properties,method of integration, substitution, partial fraction, rational , irrational function integration, integration by parts, reduction formula, improper integral, convergent and divergent of integration
Every material has certain strength, expressed in terms of stress or strain, beyond which it
fractures or fails to carry the load. Failure Criterion: A criterion used to hypothesize the failure.
Failure Theory: A Theory behind a failure criterion.
Need of Failure Theories:
(a) To design structural components and calculate margin of safety.
(b) To guide in materials development.
(c) To determine weak and strong directions.
PROBABILITY DISTRIBUTION OF SUM OF TWO CONTINUOUS VARIABLES AND CONVOLUTIONJournal For Research
All physical subjects, involving random phenomena, something depending upon chance, naturally find their own way to theory of Statistics. Hence there arise relations between the results derived for hose random phenomena in different physical subjects and the concepts of Statistics. Convolution theorem has a variety of applications in field of Fourier transforms and many other situations, but it bears beautiful applications in field of statistics also .Here in this paper authors want to discuss some notions of Electrical Engineering in terms of convolution of some probability distributions.
Differential Geometry for Machine LearningSEMINARGROOT
References:
Differential Geometry of Curves and Surfaces, Manfredo P. Do Carmo (2016)
Differential Geometry by Claudio Arezzo
Youtube: https://youtu.be/tKnBj7B2PSg
What is a Manifold?
Youtube: https://youtu.be/CEXSSz0gZI4
Shape analysis (MIT spring 2019) by Justin Solomon
Youtube: https://youtu.be/GEljqHZb30c
Tensor Calculus
Youtube: https://youtu.be/kGXr1SF3WmA
Manifolds: A Gentle Introduction,
Hyperbolic Geometry and Poincaré Embeddings by Brian Keng
Link: http://bjlkeng.github.io/posts/manifolds/,
http://bjlkeng.github.io/posts/hyperbolic-geometry-and-poincare-embeddings/
Statistical Learning models for Manifold-Valued measurements with application to computer vision and neuroimaging by Hyunwoo J.Kim
Sources:
Visual - various maths sites (credits to original creator)
Questions - Dong Zong's Textbook
suitable for SUEC (Maths), SPM (Maths and Add Maths) too
A deep introduction to supervised and unsupervised Machine Learning with examples in R.
Techniques covered for Regression:
- Linear Regression
- Polynomial Regression
Techniques covered for Classification:
- Simple and Multiple Logistic Regression
- Linear and Quadratic Discriminant Analysis
- K-Nearest Neighbors
Clustering:
- K-Means clustering
- Hierarchical clustering
The twentieth century saw the elevation of Discrete Mathematics from ”the slums of topology” (one of the more polite expressions!) to its current highly regarded position in the mathematical pantheon. Paul Erd˝os played a key role in this transformation. We call discuss some key results, possibly including:
i) Ramsey Theory. In 1946 Erdős showed that you could two-color the complete graph on n vertices so as to avoid a monochromatic clique of size k, where n was exponential in k. To do it, he introduced The Probabilistic Method.
ii) Two-Coloring. In 1963 Erdős showed that given any m = 2 n − 1 sets, each of size n, one could two-color the underlying points so that none of the sets were monochromatic. His proof in two words: Color Randomly! There has been much work on larger m. We give a simple algorithm (together with a subtle analysis) of Cherkashin and Kozik that finds a coloring for the best known (so far!) m.
iii) Number Theory. In 1940 Erdős , with Marc Kac, showed that the number of prime factors of n satisfies (when appropriately defined) a Gaussian distribution. Amazing!
iv) Liar Games. Paul tries to find an integer from 1 to 100 by asking ten Yes/No questions from Carole. BUT, Carole can lie – though at most one time. Can Paul find the number? Or can Carole stop Paul with an Adversary Strategy?
Anecdotes and personal recollections of Paul Erdős will be sprinkled liberally thoughout the presentation.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.