Applied Statistical Modeling for Data Analysis in R
Free Download Applied Statistical Modeling for Data Analysis in R
Last updated 11/2023
Duration: 9h53m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 5.08 GB
Genre: eLearning | Language: English
Your Complete Guide to Statistical Data Analysis and Visualization For Practical Applications in R


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Data science tools Statistical Hypothesis Testing–1
Free Download Data science tools Statistical Hypothesis Testing–1
Last updated 6/2023
Created by Mohammad Rafiqul Islam
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 43 Lectures ( 4h 24m ) | Size: 2.32 GB


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Statistical Analysis with Wolfram Language
Free Download Statistical Analysis with Wolfram Language
Released 1/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 39m | Size: 224 MB
Analyze your data using a framework of model fitting and statistical analysis built into the Wolfram Language. Whether it is basic descriptive and exploratory statistics or advanced modeling with statistical distributions, you can follow this video course to gain an understanding of the statistical functionality available in the Wolfram Language. Topics covered include descriptive measures, transformations, basic clustering, statistical distributions, parameter estimation and hypothesis testing. Advanced topics on using optimization functions, linear algebra functions, analysis of variance (ANOVA) and generalized logit and probit linear models are also explored.


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Statistical Physics – Relation To Quanta And Thermodynamics
Free Download Statistical Physics – Relation To Quanta And Thermodynamics
Last updated 11/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 6.87 GB | Duration: 7h 51m
The mathematics used in the discovery of quantum physics, the foundations of thermodynamics, phase transitions.


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Statistical Panic Cultural Politics and Poetics of the Emotions
Free Download Statistical Panic: Cultural Politics and Poetics of the Emotions By Kathleen Woodward
2009 | 316 Pages | ISBN: 0822343541 | PDF | 30 MB
In this moving and thoughtful book, Kathleen Woodward explores the politics and poetics of the emotions, focusing on American culture since the 1960s. She argues that we are constrained in terms of gender, race, and age by our culture&;s scripts for &;emotional&; behavior and that the accelerating impoverishment of interiority is a symptom of our increasingly media-saturated culture. She also shows how we can be empowered by stories that express our experience, revealing the value of our emotions as a crucial form of intelligence.Referring discreetly to her own experience, Woodward examines the interpenetration of social structures and subjectivity, considering how psychological emotions are social phenomena, with feminist anger, racial shame, old-age depression, and sympathy for non-human cyborgs (including robots) as key cases in point. She discusses how emerging institutional and discursive structures engender &;new&; affects that in turn can help us understand our changing world if we are attentive to them&;the &;statistical panic&; produced by the risk society, with its numerical portents of disease and mortality; the rage prompted by impenetrable and bloated bureaucracies; the brutal shame experienced by those caught in the crossfire of the media; and the conservative compassion that is not an emotion at all, only an empty political slogan.The orbit of Statistical Panic is wide, drawing in feminist theory, critical phenomenology, and recent theories of the emotions. But at its heart are stories. As an antidote to the vacuous dramas of media culture, with its mock emotions and scattershot sensations, Woodward turns to the autobiographical narrative. Stories of illness&;by Joan Didion, Yvonne Rainer, Paul Monette, and Alice Wexler, among others&;receive special attention, with the inexhaustible emotion of grief framing the book as a whole.


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Post–Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data
Free Download Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data by Syed Ejaz Ahmed
English | May 25, 2023 | ISBN: 0367763443 | 408 pages | MOBI | 22 Mb
This book presents some post-estimation and predictions strategies for the host of useful statistical models with applications in data science. It combines statistical learning and machine learning techniques in a unique and optimal way. It is well-known that machine learning methods are subject to many issues relating to bias, and consequently the mean squared error and prediction error may explode. For this reason, we suggest shrinkage strategies to control the bias by combining a submodel selected by a penalized method with a model with many features. Further, the suggested shrinkage methodology can be successfully implemented for high dimensional data analysis. Many researchers in statistics and medical sciences work with big data. They need to analyse this data through statistical modelling. Estimating the model parameters accurately is an important part of the data analysis. This book may be a repository for developing improve estimation strategies for statisticians. This book will help researchers and practitioners for their teaching and advanced research, and is an excellent textbook for advanced undergraduate and graduate courses involving shrinkage, statistical, and machine learning.


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Advanced Statistical Computing
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English | 2022 | ISBN: n/a | 107 Pages | PDF | 2 MB
The journey from statistical model to useful output has many steps, most of which are taught in other books and courses. The purpose of this book is to focus on one particular aspect of this journey: the development and implementation of statistical algorithms. It's often nice to think about statistical models and various inferential philosophies and techniques, but when the rubber meets the road, we need an algorithm and a computer program implementation to get the results we need from a combination of our data and our models. This book is about how we fit models to data and the algorithms that we use to do so. Examples are given using the R programming language.


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An Introduction to Statistical Learning With Applications in Python
Free Download An Introduction to Statistical Learning: With Applications in Python
English | 2023 | ISBN: 3031391896 | 617 Pages | PDF (True) | 13 MB
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data.


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Statistical Physics
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English | 2024 | ISBN: 1032223960 | 451 Pages | PDF (True) | 14 MB
This book presents an introduction to the main concepts of statistical physics, followed by applications to specific problems and more advanced concepts, selected for their pedagogical or practical interest. Particular attention has been devoted to the presentation of the fundamental aspects, including the foundations of statistical physics, as well as to the discussion of important physical examples. Comparison of theoretical results with the relevant experimental data (with illustrative curves) is present through the entire textbook. This aspect is facilitated by the broad range of phenomena pertaining to statistical physics, providing example issues from domains as varied as the physics of classical and quantum liquids, condensed matter, liquid crystals, magnetic systems, astrophysics, atomic and molecular physics, superconductivity and many more. This textbook is intended for graduate students (MSc and PhD) and for those teaching introductory or advanced courses on statistical physics.


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