Search results “Data mining and statistics pdf and cdf”
Binomial distribution | Probability and Statistics | Khan Academy
PWatch the next lesson: https://www.khanacademy.org/math/probability/random-variables-topic/binomial_distribution/v/visualizing-a-binomial-distribution?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/random-variables-topic/expected-value/v/law-of-large-numbers?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it! About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to KhanAcademy’s Probability and Statistics channel: https://www.youtube.com/channel/UCRXuOXLW3LcQLWvxbZiIZ0w?sub_confirmation=1 Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 952273 Khan Academy
Percentiles and Quartiles
statisticslectures.com - where you can find free lectures, videos, and exercises, as well as get your questions answered on our forums!
Views: 400895 statslectures
Distribution Analysis Using SAS Studio
In this video, you learn how to use the Distribution Analysis task in SAS Studio. You learn how to request histograms with overlaid density curves and inset statistics, as well as a normal probability plot and fit statistics for assessing normality.
Views: 4234 SAS Software
Weibull++ Example 1: Complete and Right Censored Data Analysis
Use the complete and right censored data from the test to determine the unreliability for a mission duration of 226 hr. Learn more about Weibull++: https://www.reliasoft.com/products/reliability-analysis/weibull-yt
Views: 6783 ReliaSoft Software
Student's t-test
Excel file: https://dl.dropboxusercontent.com/u/561402/TTEST.xls In this video Paul Andersen explains how to run the student's t-test on a set of data. He starts by explaining conceptually how a t-value can be used to determine the statistical difference between two samples. He then shows you how to use a t-test to test the null hypothesis. He finally gives you a separate data set that can be used to practice running the test. Do you speak another language? Help me translate my videos: http://www.bozemanscience.com/translations/ Music Attribution Intro Title: I4dsong_loop_main.wav Artist: CosmicD Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/ Creative Commons Atribution License Outro Title: String Theory Artist: Herman Jolly http://sunsetvalley.bandcamp.com/track/string-theory All of the images are licensed under creative commons and public domain licensing: Critical Values of the Student’s-t Distribution. (n.d.). Retrieved April 12, 2016, from http://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm File:Hordeum-barley.jpg - Wikimedia Commons. (n.d.). Retrieved April 11, 2016, from https://commons.wikimedia.org/wiki/File:Hordeum-barley.jpg Keinänen, S. (2005). English: Guinness for strenght. Retrieved from https://commons.wikimedia.org/wiki/File:Guinness.jpg Kirton, L. (2007). English: Footpath through barley field. A well defined and well used footpath through the fields at Nuthall. Retrieved from https://commons.wikimedia.org/wiki/File:Footpath_through_barley_field_-_geograph.org.uk_-_451384.jpg pl.wikipedia, U. W. on. ([object HTMLTableCellElement]). English: William Sealy Gosset, known as “Student”, British statistician. Picture taken in 1908. Retrieved from https://commons.wikimedia.org/wiki/File:William_Sealy_Gosset.jpg The T-Test. (n.d.). Retrieved April 12, 2016, from http://www.socialresearchmethods.net/kb/stat_t.php
Views: 466501 Bozeman Science
Normal Quantile-Quantile Plots
An introduction to normal quantile-quantile (QQ) plots (a graphical method for assessing whether a set of observations is approximately normally distributed). I discuss the motivation for the plot, the construction of the plot, then look at several examples. In the examples I look at what a normal quantile-quantile plot looks like when sampling from various other distributions. I then illustrate what normal QQ plots look like when sampling from a normal distribution by simulating several samples, for two different sample sizes.
Views: 124996 jbstatistics
ECC3004  Engineering Statistics (PDF)
This is a group assignment video for ECC3004 Statistic Engineering. Please like and share. Thankyou for watching ! :D
Views: 972 Syahmi Azhari
Applying Flags in Windographer 2
This video demonstrates the ways of applying flags to data in Windographer 2.
Views: 1489 Windographer
BigDataX: Power law distributions
Big Data Fundamentals is part of the Big Data MicroMasters program offered by The University of Adelaide and edX. Learn how big data is driving organisational change and essential analytical tools and techniques including data mining and PageRank algorithms. Enrol now! http://bit.ly/2rg1TuF
26. Data Visualisation in R - 2 Dimensional Density Plots
Create 2 dimensional density plots using R.
Views: 359 Gary Hutson
Introduction (4): Complexity and Overfitting
Simple vs complex models; training vs testing error; overfitting
Views: 9870 Alexander Ihler
Statistical Sampling - Part II: Rejection Sampling (Accept-Reject Algorithm)
Rejection Sampling basics 4 Parts: - Basics of rejection sampling: 0:00 - Detailed example: 5:22 - Algorithm: 10:53 - Pros and Cons: 14:54
Views: 54 Milan Berka
Warranty Analysis
This video explains how to predict Warranty performance using the Warranty Analysis tool in Minitab.
Views: 2348 Vishwanathan C
The Weibull as a Model of Shortest Path Distributions in Random Networks
Christian Bauckhage, Kristian Kersting, Bashir Rastegarpanah International Workshop on Mining and Learning with Graphs (MLG 2013)
Views: 84 sciTrailer
Central Limit Theorem | Application of CLT in R | Statistics
Central Limit theorem is one of the foundation & fundamental concept in whole of mathematics and in particular Statistics and Probability theory. It stated that the average of a given random variable would tend to behave normally (normal distribution) when the average has been taken for a infinite number of time irrespective of what is the original distribution of the random variable X This has wide application in real world problems where we mostly deal with averages such as stock price, stock return, experimental results etc. ANalytics Study Pack : http://analyticuniversity.com/ Analytics University on Twitter : https://twitter.com/AnalyticsUniver Analytics University on Facebook : https://www.facebook.com/AnalyticsUniversity Logistic Regression in R: https://goo.gl/S7DkRy Logistic Regression in SAS: https://goo.gl/S7DkRy Logistic Regression Theory: https://goo.gl/PbGv1h Time Series Theory : https://goo.gl/54vaDk Time ARIMA Model in R : https://goo.gl/UcPNWx Survival Model : https://goo.gl/nz5kgu Data Science Career : https://goo.gl/Ca9z6r Machine Learning : https://goo.gl/giqqmx Data Science Case Study : https://goo.gl/KzY5Iu Big Data & Hadoop & Spark: https://goo.gl/ZTmHOA
How to discretize a continuous variable with XLSTAT?
This tutorial is designed to help you discretize a continuous variable. The data and explaination are available on our website. http://www.xlstat.com/en/support/tutorials/discretization.htm
Views: 4483 XLSTAT
Python Integration, Interpolation, and Curve Fitting
iPython Notebook, using numpy and scipy interpolation, integration, and curve fitting functions
Views: 28033 ignite.byu.edu
Precision Data Imaging www.pdi-inc.net
Precision Data Imaging, Inc. www.pdi-inc.net scans documents on the industries latest high speed scanners for pennies per page. Single sided, double sided, letter size to legal size, to aperture cards, Black and White, Gray scale or color, we do it all. Whatever your requirements are give us a call. Need fast turn around time? Need ten thousand documents scanned same day? No problem, Precision Data Imaging Inc. can turn your project around. Day or Night, your site or ours, feel safe knowing that Precision Data Imaging is your handling your project. Precision Data Imaging Inc offers a total solution to your document imaging & scanning needs. In addition, to providing Back File Conversions, we offer full System Integrations, Data processing services, Claims processing services, Networking, Training, and Support.
13 Snapshot of Data Visualization: box-plot and categorical variables
Course material: https://github.com/DrWaleedAYousef/Teaching
Views: 322 FCIH OCW
Scaling and Distribution of Data Using Scikit learn in Python - Tutorial 16 Jupyter Notebook
In this Python for data science tutorial, you will learn how to scale your data and data-set distribution in python using scikit learn preprocessing. How to transform your data using scikit-learn in jupyter notebook. This is the 16th Video of Python for Data Science Course! In This series I will explain to you Python and Data Science all the time! It is a deep rooted fact, Python is the best programming language for data analysis because of its libraries for manipulating, storing, and gaining understanding from data. Watch this video to learn about the language that make Python the data science powerhouse. Jupyter Notebooks have become very popular in the last few years, and for good reason. They allow you to create and share documents that contain live code, equations, visualizations and markdown text. This can all be run from directly in the browser. It is an essential tool to learn if you are getting started in Data Science, but will also have tons of benefits outside of that field. Harvard Business Review named data scientist "the sexiest job of the 21st century." Python pandas is a commonly-used tool in the industry to easily and professionally clean, analyze, and visualize data of varying sizes and types. We'll learn how to use pandas, Scipy, Sci-kit learn and matplotlib tools to extract meaningful insights and recommendations from real-world datasets. Download Link for Cars Data Set: https://www.4shared.com/s/fWRwKoPDaei Download Link for Enrollment Forecast: https://www.4shared.com/s/fz7QqHUivca Download Link for Iris Data Set: https://www.4shared.com/s/f2LIihSMUei https://www.4shared.com/s/fpnGCDSl0ei Download Link for Snow Inventory: https://www.4shared.com/s/fjUlUogqqei Download Link for Super Store Sales: https://www.4shared.com/s/f58VakVuFca Download Link for States: https://www.4shared.com/s/fvepo3gOAei Download Link for Spam-base Data Base: https://www.4shared.com/s/fq6ImfShUca Download Link for Parsed Data: https://www.4shared.com/s/fFVxFjzm_ca Download Link for HTML File: https://www.4shared.com/s/ftPVgKp2Lca
Views: 2531 TheEngineeringWorld
Data Fundamentals - MSc in Data Science
From the course description page: This course will cover computational approaches to working with numerical data on a large scale. Computation on arrays of continuous variables underpins machine learning, information retrieval, data analytics, computer vision and signal processing. This course will cover vectorised operations on numerical arrays, fundamental stochastic and probabilistic methods and scientific visualisation. The first video in the series: what was I doing the last six months? John Williamson: http://www.johnhw.com/ Link to the course: https://www.gla.ac.uk/coursecatalogue/course/?code=COMPSCI4073 Slides: http://bit.ly/dfh-video-slides BLOG http://thatcsharpguy.com REDES SOCIALES https://twitter.com/io_exception https://www.facebook.com/thatcsharpguy https://github.com/ThatCSharpGuy/ Foto por Julio Montaño: https://www.instagram.com/jmz7v/ music by Dyalla Swain https://soundcloud.com/dyallas
Views: 264 That CS guy
10. Exercises on Normal Distribution
The lecture spends more time reinforcing the properties of a normal distribution discussed in previous lectures. We talk area under the curve within 1/2/3 standard deviations from the mean as per the normal/z table. Post this lecture the student should be able to grasp the concept of normally distributed variables, how mean and standard deviations can be used to create 90/95/99% confidence intervals around the mean. This playlist provides approximately 10 hours of our Analytics Training series. For more information, please visit www.learnanalytics.in . For enquiries drop an email to [email protected] . The training covers basic business statistics concepts and using tools such as SAS, SPSS , Statistica and R using Rattle. The objective of the training series is to prepare the student for a career in Data Analysis and the Analytics Industry in general. Please visit our website for further details. If you wish to subscribe to our full Analytics Training module, please visit http://goo.gl/nIJJHg for our paid Youtube Channel which contains additional hours covering more extensive topics including Linear Regression/Logistic Regression, building and testing predictive models using Logistic / Decision Trees and Ensembling. All videos on our paid channel are available without advertisement interruptions and you can enrol for a 14 day free subscription trial. You pay only if you want to continue. Additionally, you get access to the datasets discussed in the videos and all SAS Codes.
Views: 5083 Learn Analytics
Hazard Function 1 of 2
Hazard Function 1 of 2
Views: 9806 Farrokh Alemi
(PP 4.2) Expectation for random variables with densities
(0:00) Definition of expectation for r.v.s. with densities. (2:30) E(X) for a uniform random variable. (5:05) Well-defined expectation. (7:15) E(X) may exist and be infinite. (8:00) E(X) might fail to exist. A playlist of the Probability Primer series is available here: http://www.youtube.com/view_play_list?p=17567A1A3F5DB5E4
Views: 6657 mathematicalmonk
What does PDF stand for?
PDF has been around for 22 years -- but what does it stand for? Here's what a few people had to say on the streets of Salt Lake CIty.
Views: 21798 Adobe Document Cloud
Mining Data from Genome Browsers (2010)
February 02, 2010. Tyra Wolfsberg, Ph.D. Current Topics in Genome Analysis 2010 Handout: http://www.genome.gov/Pages/Research/IntramuralResearch/DIRCalendar/CurrentTopicsinGenomeAnalysis2010/CTGA2010_Lec04_color.pdf More: http://www.genome.gov/12514286
Leverage Scores, the Column Subset Selection Problem, and Least squares Problems, Petros Drineas
In this talk we will discuss the notion of leverage scores: a simple statistic that reveals columns (or rows) of a matrix that lie well within the subspace spanned by the top prin-cipal components. Sampling with respect to leverage scores has been used to speed up solving least-squares problems, as well as to approximately solve variants of the column subset selection problem. Finally, leverage scores are deeply con-nected to the so-called effective resistances of the edges of undirected, positively weighted graphs; effective resistances have been critical in approximately solving systems of linear equations with Laplacian matrices as inputs, in time nearly linear to the number of non-zero entries in the input matrix.
Views: 153 MMDS Foundation
Edward J. Hannan: "The statistical theory of linear systems"
The Second International Tampere Conference in Statistics, University of Tampere, Finland, 1-4 June, 1987. Keynote speaker Edward J. Hannan, The Australian National University, Canberra, Australia: "The statistical theory of linear systems". Chair: Manfred Deistler.
Views: 651 UniversityOfTampere
Introduction To Copula - Financial Engineering - IIQF
Post Graduate Program in Financial Engineering Lecture Series - Introduction to Copula - Part 1
Views: 603 iiqf
Using Excel to illustrate a uniform probability distribution
This is for Data Management courses where we study uniform PDs as one kind of many probability distributions. We are using an Excel simulation to show that dice rolls give a uniform probability distributions by examining their relative frequencies ... ( or *are* they uniform...?)
Views: 17705 Paul King
Outage Probability Analysis in Generalized Fading Channels with Co Channel Interference and Backgrou
Outage Probability Analysis in Generalized Fading Channels with Co Channel Interference and Backgrou +91-9994232214,8144199666, [email protected], www.ieeeprojectsin.com, www.ieee-projects-chennai.com IEEE PROJECTS 2014 ----------------------------------- Contact:+91-9994232214,+91-8144199666 Email:[email protected] http://ieeeprojectsin.com/Cloud-Computing http://ieeeprojectsin.com/Data-Mining http://ieeeprojectsin.com/Android http://ieeeprojectsin.com/Image-Processing http://ieeeprojectsin.com/Networking http://ieeeprojectsin.com/Network-Security http://ieeeprojectsin.com/Mobile-Computing http://ieeeprojectsin.com/Parallel-Distributed http://ieeeprojectsin.com/Wireless-Communication http://ieeeprojectsin.com/NS2-Projects http://ieeeprojectsin.com/Matlab Support: ------------- Projects Code Documentation PPT Projects Video File Projects Explanation Teamviewer Support
Views: 274 PROJECTS2014
Webinar:  Industrial IoT and failure prediction on event signals | Part 1
Attend our 3 part webinar series on “Industrial IoT and failure prediction on event signals”. In this series, we will highlight how companies can seize the opportunity to monetize the trillion dollar opportunity in IIoT by “connecting the unconnected” for cognitive insights. These cognitive insights from real time sensor/machine data can empower companies to achieve ground-breaking results in plant efficiency, improved productivity and “digital readiness for smart factory”. In our first part, aptly titled “Feature Engineering for failure prediction on time series data” Adurthi Ashwin Swarup, Sr. Data Scientist, at DataRPM will introduce the concept of how imprecise business problems are translated to precise data science solutions, how data is transformed and whitened for algorithms that are essential to predictive maintenance use-cases.
Views: 410 DataRPM
Entropy with Dr. Green
Dr. Green fills in some gaps in entropy.
Views: 639 William Green
Data Mining ou Mineração de Dados consiste em um processo analítico projetado para explorar grandes quantidades de dados (tipicamente relacionados a negócios, mercado ou pesquisas científicas), na busca de padrões consistentes e/ou relacionamentos sistemáticos entre variáveis e, então, validá-los aplicando os padrões detectados a novos subconjuntos de dados. O processo consiste basicamente em 3 etapas: exploração; construção de modelo ou definição do padrão; e validação/verificação.
Views: 3902 professormarcebrito
कक्षा 8 गणित: बेर्नौली वितरण | Bernoulli distribution in hindi (CBSE/NCERT)
Today we will learn 'Class 8 Maths -Bernoulli distribution' in hindi. If you have any doubts, let us know in the comments section. Download Toppr App: Andriod Play Store: http://bit.ly/2jTmjef iOS App Store: http://apple.co/2A8pIdz Download Doubts on Chat App: Andriod Play Store:http://bit.ly/2B6w7oy iOS App Store: http://apple.co/2ziAA75 About Toppr: Toppr is an after school learning app for K12 students. Our vision is to personalise education using technology. We cater to the curricular learning needs of students who are preparing for various school board exams, olympiads and scholarship tests as well as for engineering and medical college entrance exams. The award winning Toppr platform leverages 4 methods of learning, each delivering a tailor-made experience for the student: * 2000+ hours of byte sized video lectures * More than half a million information rich practice questions * Instant, always on assisted learning; ask doubts over chat * Massive take-from-anywhere tests, benchmarking performance These modules leverage our proprietary content of over a million learning pieces, that give each student a unique learning path and the best value for the time spent studying. In a market where education is either a walled garden, with those that need help getting the least attention or a "one size fits all" one-to-many content distribution engine; Toppr offers effective learning that works for each and every student. Subscribe to Toppr: https://www.youtube.com/toppr Facebook: https://www.facebook.com/beingToppr Twitter: https://twitter.com/mytoppr Instagram: https://instagram.com/mytoppr LinkedIn: https://www.linkedin.com/company/toppr-com
Views: 253 Toppr
Method of Moments and Maximum Likelihood estimate Numerical
Training on Method of Moments and Maximum Likelihood estimate Numerical for CT 6 by Vamsidhar Ambatipudi
Belajar Python: Teori Probabilitas
Belajar Python Teori Probabilitas
Views: 405 Ageng Rikhmawan
Simulación de Distribución Normal y Solución de Ejercicios en Python
Simulación de una Distribución Normal y solución de ejercicios en el lenguaje de programación Python.
Views: 277 Savage Consultores
2.4 Histograms and Density Plots (Visualizing Data Using ggplot2)
See here for the course website, including a transcript of the code and an interactive quiz for this segment: http://dgrtwo.github.io/RData/lessons/lesson2/segment4/
How to Build a Financial Model in Excel - Tutorial | Corporate Finance Institute
How to Build a Financial Model in Excel - Tutorial | Corporate Finance Institute Learn how to build a financial model in Excel with our video course (part 1). Enroll in the FULL course to earn your certificate and advance your degree: http://www.corporatefinanceinstitute.com In this course you will learn to build a financial model from scratch by working in Excel and following along with the video. Upon successfully completing the course and all quizzes you will obtain your Financial Modeling Certificate from the Corporate Finance Institute. -- FREE COURSES & CERTIFICATES -- Enroll in our FREE online courses and earn industry-recognized certificates to advance your career: ► Introduction to Corporate Finance: https://courses.corporatefinanceinstitute.com/courses/introduction-to-corporate-finance ► Excel Crash Course: https://courses.corporatefinanceinstitute.com/courses/free-excel-crash-course-for-finance ► Accounting Fundamentals: https://courses.corporatefinanceinstitute.com/courses/learn-accounting-fundamentals-corporate-finance ► Reading Financial Statements: https://courses.corporatefinanceinstitute.com/courses/learn-to-read-financial-statements-free-course ► Fixed Income Fundamentals: https://courses.corporatefinanceinstitute.com/courses/introduction-to-fixed-income -- ABOUT CORPORATE FINANCE INSTITUTE -- CFI is a leading global provider of online financial modeling and valuation courses for financial analysts. Our programs and certifications have been delivered to thousands of individuals at the top universities, investment banks, accounting firms and operating companies in the world. By taking our courses you can expect to learn industry-leading best practices from professional Wall Street trainers. Our courses are extremely practical with step-by-step instructions to help you become a first class financial analyst. Explore CFI courses: https://courses.corporatefinanceinstitute.com/collections -- JOIN US ON SOCIAL MEDIA -- LinkedIn: https://www.linkedin.com/company/corporate-finance-institute-cfi- Facebook: https://www.facebook.com/corporatefinanceinstitute.cfi Instagram: https://www.instagram.com/corporatefinanceinstitute Google+: https://plus.google.com/+Corporatefinanceinstitute-CFI YouTube: https://www.youtube.com/c/Corporatefinanceinstitute-CFI
Consumer Test Evaluation Using a Combination of JMP® Functionality Plus Customized JSL Scripts
Mondelēz empowers its staff by developing user-friendly tools for customized data handling, calculation and reporting. JMP software houses a multiproduct consumer test evaluation (MCTE) tool used by the global Consumer Science function. The MCTE tool has significantly reduced training and analysis time and ensured use of good statistical practices. Its success results from a close collaboration between Mondelēz UK and SAS Professional Services in Marlow. Read the paper by Jeff Stagg and David Rose given at 2014 JMP Discovery Summit. https://community.jmp.com/docs/DOC-6649
Views: 393 JMPSoftwareFromSAS
How to calculate Chi Square Two Way Test (Independence) Using Excel
Tutorial on how to use Microsoft excel to calculate two way chi square test (test for independence). Includes chi square analysis example. Playlist on Chi Square Analysis http://www.youtube.com/course?list=ECD2EE7A6284364CA2 Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet http://www.MyBookSucks.Com
Views: 40756 statisticsfun
Matplotlib Python Tutorial Part 1: Basics and your first Graph!
Sample code: http://pythonprogramming.net/matplotlib-basics-first-graph/ Introduction of downloading matplotlib, the basic functions, and charting your first graph! To start, you will obviously need Matplotlib, as well as Python. This tutorial series uses Python 2.7. Almost everything can be ported to Python 3+ so long as you know the basic syntax differences. Matplotlib is one of the most popular modules for creating graphs and charts in Python. It is simple to use, yet has a wide range of abilities for data visualization. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 145157 sentdex
Sesión 4: Análisis exploratorio de datos
Presentación: https://docs.google.com/presentation/d/1FAPRsrA93QHtRrOxaiUSOs2u4KM6GCGM6m1YC8zICcc/edit Código: https://github.com/CodeandoMonterrey/RPP_DesafioSP/tree/master/sesion4 Plan de Estudios: https://docs.google.com/document/d/1KkH3w7X8lh2vmsRU75Bs6Ma8G2A0TJq27TOKFSboOs0/edit#
Views: 219 Ricardo Alanís