Home
Search results “Statistics and data analysis for financial engineering pdf”
1. Introduction to Statistics
 
01:18:03
*NOTE: This video was recorded in Fall 2017. The rest of the lectures were recorded in Fall 2016, but video of Lecture 1 was not available. MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: https://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet In this lecture, Prof. Rigollet talked about the importance of the mathematical theory behind statistical methods and built a mathematical model to understand the accuracy of the statistical procedure. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
Views: 219638 MIT OpenCourseWare
Stock Market Probability and Odds Analysis
 
09:11
http://optionalpha.com - Video tutorial on Stock Market Probability and Odds Analysis ================== Listen to our #1 rated investing podcast on iTunes: http://optionalpha.com/podcast ================== Download a free copy of the "The Ultimate Options Strategy Guide": http://optionalpha.com/ebook ================== Still working a day job? Then our "Take 5" segment is for you. 5 mins videos each day on 1 thing you can apply trading options: http://www.youtube.com/playlist?list=PLhKnvfWKsu40z0EnsX0TNqCgUzb8tmM04 ================== Start our 4-part video course (HINT: these videos are NOT posted anywhere else online): http://optionalpha.com/free-options-trading-course ================== Just getting started or new to options trading? Here's a quick resource page we made that you'll love: http://optionalpha.com/start-here ================== Register for one of our 5-star reviewed webinars: http://optionalpha.com/webinars ================== - Kirk & The Option Alpha Team
Views: 13898 Option Alpha
Introduction to Data Science with R - Data Analysis Part 1
 
01:21:50
Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 860401 David Langer
Engineering Data Analysis (with R and ggplot2)
 
58:35
Google Tech Talk (more info below) June 6, 2011 Presented by Hadley Wickham, Assistant Professor, Dobelman Family Junior Chair, Department of Statistics, Rice University. ABSTRACT Data analysis, the process of converting data into knowledge, insight and understanding, is a critical part of statistics, but there's surprisingly little research on it. In this talk I'll introduce some of my recent work, including a model of data analysis. I'm a passionate advocate of programming that data analysis should be carried out using a programming language, and I'll justify this by discussing some of the requirement of good data analysis (reproducibility, automation and communication). With these in mind, I'll introduce you to a powerful set of tools for better understanding data: the statistical programming language R, and the ggplot2 domain specific language (DSL) for visualisation.
Views: 86673 GoogleTechTalks
Data Analysis with Python for Excel Users
 
21:01
A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. See http://apmonitor.com/che263/index.php/Main/PythonDataAnalysis
Views: 152078 APMonitor.com
5 free must read machine learning book for Data Scientists
 
02:01
1. Think Stats – Probability and Statistics for Programmers http://greenteapress.com/thinkstats/thinkstats.pdf 2. Probabilistic Programming & Bayesian Methods for Hackers http://ptgmedia.pearsoncmg.com/images/9780133902839/samplepages/9780133902839.pdf 3. Bayesian reasoning and machine learning http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf 4. Understanding Machine Learning: From Theory to Algorithms https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf 5. Understanding Machine Learning: From Theory to Algorithms http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Sixth%20Printing.pdf
Views: 203 tathya
Working with Time Series Data in MATLAB
 
53:29
See what's new in the latest release of MATLAB and Simulink: https://goo.gl/3MdQK1 Download a trial: https://goo.gl/PSa78r A key challenge with the growing volume of measured data in the energy sector is the preparation of the data for analysis. This challenge comes from data being stored in multiple locations, in multiple formats, and with multiple sampling rates. This presentation considers the collection of time-series data sets from multiple sources including Excel files, SQL databases, and data historians. Techniques for preprocessing the data sets are shown, including synchronizing the data sets to a common time reference, assessing data quality, and dealing with bad data. We then show how subsets of the data can be extracted to simplify further analysis. About the Presenter: Abhaya is an Application Engineer at MathWorks Australia where he applies methods from the fields of mathematical and physical modelling, optimisation, signal processing, statistics and data analysis across a range of industries. Abhaya holds a Ph.D. and a B.E. (Software Engineering) both from the University of Sydney, Australia. In his research he focused on array signal processing for audio and acoustics and he designed, developed and built a dual concentric spherical microphone array for broadband sound field recording and beam forming.
Views: 41344 MATLAB
The Complete MATLAB Course: Beginner to Advanced!
 
04:22:09
Get The Complete MATLAB Course Bundle for 1 on 1 help! https://josephdelgadillo.com/product/matlab-course-bundle/ Get the courses directly on Udemy! Go From Beginner to Pro with MATLAB! http://bit.ly/2v1e0lL Machine Learn Fundamentals with MATLAB! http://bit.ly/2v3sQs6 The Ultimate Guide for MATLAB App Development! http://bit.ly/2GOodDN MATLAB for Programming and Data Analysis! http://bit.ly/2IIwpWL Enroll in the FREE Teachable course! http://jtdigital.teachable.com/p/matlab Time Stamps 00:51 What is Matlab, how to download Matlab, and where to find help 07:52 Introduction to the Matlab basic syntax, command window, and working directory 18:35 Basic matrix arithmetic in Matlab including an overview of different operators 27:30 Learn the built in functions and constants and how to write your own functions 42:20 Solving linear equations using Matlab 53:33 For loops, while loops, and if statements 1:09:15 Exploring different types of data 1:20:27 Plotting data using the Fibonacci Sequence 1:30:45 Plots useful for data analysis 1:38:49 How to load and save data 1:46:46 Subplots, 3D plots, and labeling plots 1:55:35 Sound is a wave of air particles 2:05:33 Reversing a signal 2:12:57 The Fourier transform lets you view the frequency components of a signal 2:27:25 Fourier transform of a sine wave 2:35:14 Applying a low-pass filter to an audio stream 2:43:50 To store images in a computer you must sample the resolution 2:50:13 Basic image manipulation including how to flip images 2:57:29 Convolution allows you to blur an image 3:02:51 A Gaussian filter allows you reduce image noise and detail 3:08:55 Blur and edge detection using the Gaussian filter 3:16:39 Introduction to Matlab & probability 3:19:47 Measuring probability 3:26:53 Generating random values 3:35:40 Birthday paradox 3:43:25 Continuous variables 3:48:00 Mean and variance 3:55:24 Gaussian (normal) distribution 4:03:21 Test for normality 4:10:32 2 sample tests 4:16:28 Multivariate Gaussian
Views: 925125 Joseph Delgadillo
Statistics intro: Mean, median, and mode | Data and statistics | 6th grade | Khan Academy
 
08:54
This is a fantastic intro to the basics of statistics. Our focus here is to help you understand the core concepts of arithmetic mean, median, and mode. Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/mean-and-median/e/calculating-the-mean?utm_source=YT&utm_medium=Desc&utm_campaign=6thgrade Watch the next lesson: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/mean-and-median/v/mean-median-and-mode?utm_source=YT&utm_medium=Desc&utm_campaign=6thgrade Missed the previous lesson? https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/histograms/v/interpreting-histograms?utm_source=YT&utm_medium=Desc&utm_campaign=6thgrade Grade 6th on Khan Academy: By the 6th grade, you're becoming a sophisticated mathemagician. You'll be able to add, subtract, multiply, and divide any non-negative numbers (including decimals and fractions) that any grumpy ogre throws at you. Mind-blowing ideas like exponents (you saw these briefly in the 5th grade), ratios, percents, negative numbers, and variable expressions will start being in your comfort zone. Most importantly, the algebraic side of mathematics is a whole new kind of fun! And if that is not enough, we are going to continue with our understanding of ideas like the coordinate plane (from 5th grade) and area while beginning to derive meaning from data! (Content was selected for this grade level based on a typical curriculum in the United States.) About Khan Academy: Khan Academy is a nonprofit with a mission to provide a free, world-class education for anyone, anywhere. We believe learners of all ages should have unlimited access to free educational content they can master at their own pace. We use intelligent software, deep data analytics and intuitive user interfaces to help students and teachers around the world. Our resources cover preschool through early college education, including math, biology, chemistry, physics, economics, finance, history, grammar and more. We offer free personalized SAT test prep in partnership with the test developer, the College Board. Khan Academy has been translated into dozens of languages, and 100 million people use our platform worldwide every year. For more information, visit www.khanacademy.org, join us on Facebook or follow us on Twitter at @khanacademy. And remember, you can learn anything. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to Khan Academy‰Ûªs 6th grade channel: https://www.youtube.com/channel/UCnif494Ay2S-PuYlDVrOwYQ?sub_confirmation=1 Subscribe to Khan Academy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 1850554 Khan Academy
Probability density functions | Probability and Statistics | Khan Academy
 
10:02
Probability density functions for continuous random variables. Practice this yourself on Khan Academy right now: https://www.khanacademy.org/e/probability-models?utm_source=YTdescription&utm_medium=YTdescription&utm_campaign=YTdescription Watch the next lesson: https://www.khanacademy.org/math/probability/random-variables-topic/expected-value/v/term-life-insurance-and-death-probability?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/random-variables-topic/random_variables_prob_dist/v/discrete-probability-distribution?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 is a nonprofit with a mission to provide a free, world-class education for anyone, anywhere. We believe learners of all ages should have unlimited access to free educational content they can master at their own pace. We use intelligent software, deep data analytics and intuitive user interfaces to help students and teachers around the world. Our resources cover preschool through early college education, including math, biology, chemistry, physics, economics, finance, history, grammar and more. We offer free personalized SAT test prep in partnership with the test developer, the College Board. Khan Academy has been translated into dozens of languages, and 100 million people use our platform worldwide every year. For more information, visit www.khanacademy.org, join us on Facebook or follow us on Twitter at @khanacademy. And remember, you can learn anything. 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: 1559871 Khan Academy
Interview with a Data Scientist
 
02:54
This video is part of the Udacity course "Intro to Programming". Watch the full course at https://www.udacity.com/course/ud000
Views: 282177 Udacity
SAS Tutorials For Beginners | SAS Training | SAS Tutorial For Data Analysis | Edureka
 
57:36
This SAS Tutorial is specially designed for beginners, it starts with Why Data Analytics is needed, goes on to explain the various tools in Data Analytics, and why SAS is used among them, towards the end we will see how we can install SAS software and a short demo on the same! In this SAS Tutorial video you will understand: 1) Why Data Analytics? 2) What is Data Analytics? 3) Data Science Analytics Tools 4) Why SAS? 5) What is SAS? 6) What SAS Solves? 7) Components of SAS 8) How can we practice Base SAS? 9) Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete SAS Training playlist here: https://goo.gl/MMLyuN #SASTraining #SASTutorial #SASCertification How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course The SAS training course is designed to provide knowledge and skills to become a successful Analytics professional. It starts with the fundamental concepts of rules of SAS as a Language to an introduction to advanced SAS topics like SAS Macros. - - - - - - - - - - - - - - Why Learn SAS? The Edureka SAS training certifies you as an ‘in demand’ SAS professional, to help you grab top paying analytics job titles with hands-on skills and expertise around data mining and management concepts. SAS is the primary analytics tool used by some of the largest KPOs, Banks like American Express, Barclays etc., financial services irms like GE Money, KPOs like Genpact, TCS etc., telecom companies like Verizon (USA), consulting companies like Accenture, KPMG etc use the tool effectively. - - - - - - - - - - - - - - Who should go for this course? This course is designed for professionals who want to learn widely acceptable data mining and exploration tools and techniques, and wish to build a booming career around analytics. The course is ideal for: 1. Analytics professionals who are keen to migrate to advanced analytics 2. BI /ETL/DW professionals who want to start exploring data to eventually become data scientist 3. Project Managers to help build hands-on SAS knowledge, and to become a SME via analytics 4. Testing professionals to move towards creative aspects of data analytics 5. Mainframe professionals 6. Software developers and architects 7. Graduates aiming to build a career in Big Data as a foundational step Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. Website: https://www.edureka.co/sas-training Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Sidharta Mitra, IBM MDM COE Head @ CTS , says, "Edureka has been an unique and fulfilling experience. The course contents are up-to-date and the instructors are industry trained and extremely hard working. The support is always willing to help you out in various ways as promptly as possible. Edureka redefines the way online training is conducted by making it as futuristic as possible, with utmost care and minute detailing, packaged into the a unique virtual classrooms. Thank you Edureka!"
Views: 38609 edureka!
Importing Financial Statements 1: Excel and VBA
 
21:12
In this tutorial, we cover how to import financial statements dynamically within Excel. We achieve this by using the webtables attribute of the QueryTables function within Excel. We will pull the financial statements from Nasdaq's website, which derives them from the SEC's database platform, Edgar. The benefit to pulling the data into Excel dynamically is that we can create a subroutine that will carry out a detailed analysis of any of the big three financial statement that will go beyond just the essentials covered by NASDAQ or even Yahoo Finance. In the next tutorial, we will clean up the data being pulled in. Link to Workbook: http://programmingforfinance.com/2017/11/importing-financial-statements-dynamically-into-excel/ My Website: http://programmingforfinance.com/
Views: 6444 codebliss
A Day in the Life of a Data Analyst
 
02:56
Take a look behind the scenes at the Intermountain Healthcare employees that keep us running smoothly! Our Data Analyst's work hard each day using data, research, numbers, and demographics to help people live the healthiest lives possible.
Views: 107511 Intermountain Healthcare
Range, variance and standard deviation as measures of dispersion | Khan Academy
 
12:34
Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/e/variance?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Watch the next lesson: https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/v/variance-of-a-population?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/descriptive-statistics/box-and-whisker-plots/v/range-and-mid-range?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: 1193026 Khan Academy
Corporations Use "Financial Engineering" at Their Own Peril
 
03:07
http://www.elliottwave.com/r.asp?rcn=ytvideos1403&url=http://www.elliottwave.com/free_newsletters/free_newsletters-ind.aspx A recent study reveals that the corporate stock buy-backs are the largest category of equity buying. Corporations bought back over $338 billion of their stock in the first half of 2014. Learn what could derail this "financial engineering" strategy.
Top Numerical Reasoning Test Tips & Tutorials
 
04:31
Welcome to JobTestPrep’s numerical reasoning test tips tutorial. This series of videos will help you learn how to pass numerical reasoning tests found in assessment companies’ psychometric tests. The hardest part of the numerical reasoning aptitude tests is the rigorous time limits. Learn some pro tips that will help you overcome the pressure and get that job you’re after! https://goo.gl/i175yD Numerical reasoning tips have 3 goals: reduce your response time, achieve a higher score and alleviate stress. No matter what type of numerical reasoning test revision you’re doing, for SHL, Kenexa or any other assessment company, have these numerical tips at your fingertips can have a big impact. To make your work more efficient, it’s important to know how to reduce your response time. The biggest problem with numerical aptitude tests is the rigorous time limits. The average time frame you have to answer each question is 45-75 seconds! But, if you plan out your calculations course to avoid repetitive steps, you will find yourself working much more efficiently. There are a few ways to do this. Using a common multiplier cuts down calculation time by a lot as you cover more ground at once. Ignoring multiplication factors when possible also increases efficiency by avoiding messy calculations. Finally, mastering your calculator can insure you accomplish your work as smoothly as possible. Find out what JTP has to say about getting to know your calculator https://goo.gl/JM1aV3 Top numerical reasoning test tips tutorials are all about finding those shortcuts. That way, you spend less time on calculations, leaving more time for the trickier questions. With the right tips and numerical reasoning test revision up your sleeve, these tricky tests can be a lot easier and quicker. Psychometric tests are a challenge for many but overcoming them gets you one step closer to getting that job! Whether you are facing tests at an assessment centre or in the comfort of your home, numeracy tips are an important thing to know and you can check out a few more by visiting https://goo.gl/i175yD Good luck from Jobtestprep!
Views: 253766 JobTestPrep
Statistics with R Programming Part 2 | Random Variables in R Studio | Data Science Tutorial
 
12:43
Statistics with R Programming Part 2 | Random Variables in R Studio | Data Science Tutorial https://acadgild.com/big-data/data-science-training-certification?aff_id=6003&source=youtube&account=cwJ-B_4zP0I&campaign=youtube_channel&utm_source=youtube&utm_medium=random-variables-gaurav-stats-with-R2&utm_campaign=youtube_channel Hello and welcome back to another tutorial that is ‘Statistics Tutorial with R Studio’ powered by Acadgild. In this video, we will discuss the random variables, a very important topic in the domain of engineering statistics. Almost every type of data exists in today’s world, can be said to be a result of random experiments moreover, this data will tend to show a pattern of its existence. It is essential that the uncertainties in them need to be evaluated and modeled with maximum accuracy. The very first step lies in considering the data as random variables and understanding the unique conditions associated with them. So, let’s have a look at the sections that this topic dealing with. Random Variables can be classified into ‘Discrete’ and ‘Continuous’ random variables. Discrete Random Variables: • Bernoulli’s distribution • Binomial distribution • Poisson distribution • Geometric distribution Continuous Random Variables: • Normal/Gaussian distribution • Lognormal distribution • Gamma distribution • Exponential distribution • Weibull distribution • Gumbel distribution What is a Random Variable? In statistics, the Random variable is a function that can take on either a finite number of values, each with an associated probability or an infinite number of values, whose probabilities are summarized by a density function. In other words, it is a variable which takes up possible values whose outcomes are numerical and are the result of a random phenomenon. It is usually represented by X. • Discrete Random Variables: When all the possible outcomes of the random variable are finite and distinct, it is called discrete and the probabilities of the outcomes sum to 1. It can be represented by the discontinuous histogram. • Continuous Random Variables: If the possible outcomes are infinite within an interval, the Random variable is called continuous and the probabilities correspond to a density function whose integral over the entire range of outcomes equals 1. It is represented by the area under a curve. Kindly, go through the complete video and please like, share and subscribe the channel. #randomvariables, #discrete, #continuous, #datascience Please like share and subscribe the channel for more such video. For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 276 ACADGILD
Data Analysis Presentation CAEG June 1 2017
 
01:45:10
"Automating Complex Data Analysis" Presentation by John F. McGowan, Ph.D. for the Caltech Alumni Entrepreneurship Group (CAEG) on June 1, 2017 Automating Complex Data Analysis: A Disruptive Business Opportunity Complex data analysis is a multi-billion dollar business. Major data analysis tool makers alone report revenues totaling over $4 billion per year: SAS Institute ($3 Billion), IBM SPSS ($0.3-1.0 Billion), MathWorks ($800 Million), Wolfram Research (at least $40 million), and a number of less well known smaller firms. Medical businesses, financial firms, and science and engineering organizations spend billions of dollars per year on these tools and the salaries of the analysts, scientists, and engineers performing the analyses. Complex data analysis increasingly determines the approval of new drugs and medical treatments, medical treatment decisions for individual patients, investment decisions for banks, pensions, and individuals, important public policy decisions, and the design and development of products from airplanes and cars to smart watches and children’s toys. State-of-the-art complex data analysis is labor intensive, time consuming, and error prone — requiring highly skilled analysts, often Ph.D.’s or other highly educated professionals, using tools with large libraries of built-in statistical and data analytical methods and tests: Excel, MATLAB, the R statistical programming language and similar tools. Results often take months or even years to produce, are often difficult to reproduce, difficult to present convincingly to non-specialists, difficult to audit for regulatory compliance and investor due diligence, and sometimes simply wrong, especially where the data involves human subjects or human society. Many important problems in business and society remain unsolved despite modern computer-intensive data analysis methods. A widely cited report from the McKinsey management consulting firm suggests that the United States may face a shortage of 140,000 to 190,000 such human analysts by 2018: http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/big-data-the-next-frontier-for-innovation Automating complex data analysis using Artificial Intelligence (AI) and similar technologies can substantially reduce the cost, time to completion, increase the quality, and yield results that are currently impossible. New tools that automate complex data analysis are a disruptive business opportunity. This talk discusses the current state-of-the-art in attempts to automate complex data analysis. It discusses widely used tools such as SAS, MATLAB and Excel and their current limitations. It discusses current products that attempt to automate complex data analysis from companies such as Skytree and research prototypes such as the Automatic Statistician from Cambridge University — funded in part by Google. It discusses what the automation of complex data analysis may look like in the future, possible methods of automating complex data analysis, and problems and pitfalls of automating complex data analysis. The talk will include a demonstration of a prototype system for automating complex data analysis. PDF of Slides: https://goo.gl/uOkocB A written version of my presentation is available online at: http://wordpress.jmcgowan.com/wp/wp-content/uploads/2017/06/Automating-Complex-Data-Analysis-White-Paper.pdf
Views: 125 John McGowan
R Shiny Tutorial | How to integrate PDF Document in Shiny
 
03:05
In this R Shiny Tutorial video I've talked about how to integrate PDF document in shiny that will be helpful for the end user. This opens up possibilities like adding help document that user can download etc.
Research Methods - Introduction
 
04:02
In this video, Dr Greg Martin provides an introduction to research methods, methedology and study design. Specifically he takes a look at qualitative and quantitative research methods including case control studies, cohort studies, observational research etc. Global health (and public health) is truly multidisciplinary and leans on epidemiology, health economics, health policy, statistics, ethics, demography.... the list goes on and on. This YouTube channel is here to provide you with some teaching and information on these topics. I've also posted some videos on how to find work in the global health space and how to raise money or get a grant for your projects. Please feel free to leave comments and questions - I'll respond to all of them (we'll, I'll try to at least). Feel free to make suggestions as to future content for the channel. SUPPORT: —————- This channel has a crowd-funding campaign (please support if you find these videos useful). Here is the link: http://bit.ly/GH_support OTHER USEFUL LINKS: ———————— Channel page: http://bit.ly/GH_channel Subscribe: http://bit.ly/GH_subscribe Google+: http://bit.ly/GH_Google Twitter: @drgregmartin Facebook: http://bit.ly/GH_facebook HERE ARE SOME PLAYLISTS ——————————————- Finding work in Global Health: http://bit.ly/GH_working Epidemiology: http://bit.ly/GH_epi Global Health Ethics: http://bit.ly/GH_ethics Global Health Facts: http://bit.ly/GH_facts WANT CAREER ADVICE? ———————————— You can book time with Dr Greg Martin via Google Helpouts to get advice about finding work in the global health space. Here is the link: http://bit.ly/GH_career -~-~~-~~~-~~-~- Please watch: "Know how interpret an epidemic curve?" https://www.youtube.com/watch?v=7SM4PN7Yg1s -~-~~-~~~-~~-~-
Normal Distribution - Explained Simply (part 1)
 
05:04
I describe the standard normal distribution and its properties with respect to the percentage of observations within each standard deviation. I also make reference to two key statistical demarcation points (i.e., 1.96 and 2.58) and their relationship to the normal distribution. Finally, I mention two tests that can be used to test normal distributions for statistical significance. normal distribution, normal probability distribution, standard normal distribution, normal distribution curve, bell shaped curve
Views: 972531 how2stats
Module 1: What is Supply Chain Management? (ASU-WPC-SCM) - ASU's W. P. Carey School
 
08:05
Part 1 of 12 - This module introduces viewers to the field of supply chain management. It describes the complex supply chain of a simple product, a bottle of water. The video also illustrates the importance of supply chain managers and their skill sets in our modern global economy for both manufacturing and service industries. In defining supply chain management, the video also hopes to educate and inspire business students, young and old, about the opportunities available to those with supply chain management degrees. This is the first installment in Arizona State University's twelve-part introduction to supply chain management video series. ASU, the W. P. Carey School of Business, and the Supply Chain Management Department are proud and happy to share this video series with supply chain management departments, supply chain instructors, career specialists in high schools and universities, as well as industry leaders in an effort to inspire a new generation of supply chain management professionals across the country and around the world. Further installments in this series will be made available during the spring of 2010. For more information, visit W. P. Carey's SCM Web site at http://wpcarey.asu.edu/scm or send an e-mail to [email protected]
Time Series - 1 Method of Least Squares - Fitting of Linear Trend - Odd number of years
 
14:40
#Statistics #Time #Series #Business #Forecasting #Linear #Trend #Values #LeastSquares #Fitting #Odd Definitions  “A time series may be defined as a sequence of values of same variable corresponding to successive points in time.” – W. Z. Hersch  “A time series may be defined as a sequence of repeated measurement of a variable made periodically through time.” – Cecil H. Mayers Analysis of Time Series “The main object of analyzing time series is to understand, interpret and evaluate changes in economic phenomena in the hope of more correctly anticipating the course of future events.” – Hersch A time series is a dynamic distribution, which reveals a good deal of variations over time. Statistical methods are, therefore, required to analyze various types of movements in a time series. There may be cyclical variations in general business activity and there may be short duration seasonal variations. There are also some accidental and random variables. The primary purpose of the analysis of time series is to discover and measure all such types of variations, which characterize a time series. Time series analysis means analyzing the historical patterns of the variable that have occurred in past as a means of predicting the future value of the variable. It helps to identify and explain the following: (i) Any regular or systematic variation in the series of data which is due to seasonality- the ‘seasonal’ (ii) Cyclical patterns. (iii) Trends in the data. (iv) Growth rates of these trends. This method can be useful when no major environmental changes are expected and it does highlight seasonal variations in sales and consumer demand. However, time series analysis is limited when organizations face volatile environments. Components of Time series – The time series are classified into four basic types of variations which are analyzed below: T = Trend S = Seasonal variations C = Cyclic variations I = Irregular fluctuations. This composite series is symbolized by the following general terms: O = T x S x C x I Where O = Original data T = Trend S = Seasonal variations C = Cyclic variations I = Irregular components. This Multiplicative model is to be used when S, C, and I are given in percentages. If, however, their true (absolute) values are known the model takes the additive form i.e., O=T+C+S+I. Algebraic Method For Finding Trend (Method of curve fitting by the principle of Least Squares) Fitting of Linear Trend Let the straight line trend between the given time series values (y) and time (x) be given by the standard equation: y = a + bx Then for any given time ‘x’ the estimated value of ye as given by the equation is ye = a + bx The following two normal equations are used for estimating 'a' and 'b'. Σy = na + bΣx Σxy = aΣx + bΣx^2 When Odd No. of Years, [X = (Year – Origin) / Interval] Case Given below are the figures of sales (in '000 units) of a certain shop. Fit a straight line by the method of least square and show the estimate for the year 2017: Year: 2010 2011 2012 2013 2014 2015 2016 Sales: 125 128 133 135 140 141 143 Time Series, Linear Trend, Method of Least Squares, Statistics, MBA, MCA, BE, CA, CS, CWA, CMA, CPA, CFA, BBA, BCom, MCom, BTech, MTech, CAIIB, FIII, Graduation, Post Graduation, BSc, MSc, BA, MA, Diploma, Production, Finance, Management, Commerce, Engineering , Grade-11, Grade- 12 - www.prashantpuaar.com
Views: 79122 Prashant Puaar
Introduction to R Programming Part 1
 
02:29:18
***Part 1 starts at 1 min and 50 seconds with about 28 minutes of tech support to get the program installed. Formal lecture begins at 30 minutes and 30 seconds. Instructor: David Ruau, PhD - http://www.stanford.edu/people/druau By the end of parts I and II, participants will be able to: · Interact with R using commands passed through the console · Import and export data in various formats and transform those data in R · Make statistical graphics plots (and more) · Write small scripts and functions using the R language. For a complete description of the classes & Installing "R" and other packages prior to the class: please see instructions for "Introduction to R programming I & II course" [pdf] http://elane/laneconnex/public/media/documents/R_Workshops_Description_And_Instructions.pdf
Views: 233467 Lane Medical Library
Complete MATLAB Tutorial for Beginners
 
50:55
Get The Complete MATLAB Course Bundle! https://josephdelgadillo.com/product/matlab-course-bundle/ Limited FREE coupons! https://goo.gl/xejcB1 Get the courses directly on Udemy! Go From Beginner to Pro with MATLAB! http://bit.ly/2v1e0lL Machine Learn Fundamentals with MATLAB! http://bit.ly/2v3sQs6 The Ultimate Guide for MATLAB App Development! http://bit.ly/2GOodDN MATLAB for Programming and Data Analysis! http://bit.ly/2IIwpWL MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language which is frequently being used by engineering and science students. In this course, we will start learning MATLAB from a beginner level, and will gradually move into more technical and advanced topics. This course is designed to be general in scope which means that it will be beneficial to students in any major. Once, passed a certain learning thresholds, you will definitely enjoy MATLAB Programming. The key benefit of MATLAB is that it makes the programming available to everyone and is very fast to turn ideas into working products compared to some of the conventional programming languages such as Java, C, C++, visual basic and others. Topics covered in the course: Instructor and Course Introduction Handling variables and Creating Scripts Doing Basic Math in MATLAB Operations on Matrices Advance Math Functions with Symbolic Data Type Interacting with MATLAB and Graphics Importing Data into MATLAB File Handling and Text Processing MATLAB Programming Sharing Your MATLAB Results Cell Data Type Tables and Time Tables Working with Structures and Map Container Data Type Converting between Different Data Types
Views: 175070 Joseph Delgadillo
Predicting the Winning Team with Machine Learning
 
29:37
Can we predict the outcome of a football game given a dataset of past games? That's the question that we'll answer in this episode by using the scikit-learn machine learning library as our predictive tool. Code for this video: https://github.com/llSourcell/Predicting_Winning_Teams Please Subscribe! And like. And comment. More learning resources: https://arxiv.org/pdf/1511.05837.pdf https://doctorspin.me/digital-strategy/machine-learning/ https://dashee87.github.io/football/python/predicting-football-results-with-statistical-modelling/ http://data-informed.com/predict-winners-big-games-machine-learning/ https://github.com/ihaque/fantasy https://www.credera.com/blog/business-intelligence/using-machine-learning-predict-nfl-games/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 78902 Siraj Raval
Introduction to Logarithms
 
09:49
An introduction to logarithms About Khan Academy: Khan Academy is a nonprofit with a mission to provide a free, world-class education for anyone, anywhere. We believe learners of all ages should have unlimited access to free educational content they can master at their own pace. We use intelligent software, deep data analytics and intuitive user interfaces to help students and teachers around the world. Our resources cover preschool through early college education, including math, biology, chemistry, physics, economics, finance, history, grammar and more. We offer free personalized SAT test prep in partnership with the test developer, the College Board. Khan Academy has been translated into dozens of languages, and 100 million people use our platform worldwide every year. For more information, visit www.khanacademy.org, join us on Facebook or follow us on Twitter at @khanacademy. And remember, you can learn anything.
Views: 1422056 Khan Academy
Transportation problem [ MODI method - U V method - Optimal  Solution ] :-by #kauserwise
 
31:43
NOTE: Formula "pij = ui+vi-Cij" according to this formula the optimal values should be Zero or less than Zero which mean Zero or negative values, and in this formula if we did not reach the optimality then we should select the maximum positive value to proceed further. If you use this Cij-(u1+vj) formula then the values should be zero or positive value to reach the optimality, and in this formula if we did not reach the optimality then we should select the maximum negative value to proceed further. We can apply either any any one of the formula to find out the optimality. So both the formulas are doing same thing only but the values of sign (- +) will be differ. Here is the video about Transportation problem in Modi method-U V method using north west corner method, optimum solution in operation research, with sample problem in simple manner. Hope this will help you to get the subject knowledge at the end. Thanks and All the best. To watch more tutorials pls use this: www.youtube.com/c/kauserwise * Financial Accounts * Corporate accounts * Cost and Management accounts * Operations Research * Statistics ▓▓▓▓░░░░───CONTRIBUTION ───░░░▓▓▓▓ If you like this video and wish to contribute lls use Paytm. * Paytm a/c : 7401428918 [Every contribution is helpful] Thanks & All the Best!!! ───────────────────────────
Views: 1780076 Kauser Wise
Introduction to R Programming Part 2
 
02:29:18
Formal lecture starts at 30 min and 50 seconds. Instructor: David Ruau, PhD - http://www.stanford.edu/people/druau By the end of parts I and II, participants will be able to: · Interact with R using commands passed through the console · Import and export data in various formats and transform those data in R · Make statistical graphics plots (and more) · Write small scripts and functions using the R language. For a complete description of the classes & Installing "R" and other packages prior to the class: please see instructions for "Introduction to R programming I & II course" [pdf] http://elane/laneconnex/public/media/documents/R_Workshops_Description_And_Instructions.pdf
Views: 29309 Lane Medical Library
Introduction to Pivot Tables, Charts, and Dashboards in Excel (Part 1)
 
14:48
WATCH PART 2: https://www.youtube.com/watch?v=g530cnFfk8Y Download file used in the video: http://www.excelcampus.com/pivot-table-checklist-yt In this video series you will learn how to create an interactive dashboard using Pivot Tables and Pivot Charts. Works with Excel 2003, 2007, 2010, 2013 for Windows & Excel 2011 for Mac Don't worry if you have never created a Pivot Table before, I cover the basics of formatting your source data and creating your first Pivot Table as well. You will also get to see an add-in I developed named PivotPal that makes it easier to work with some aspects of Pivot Tables. Download the files to follow along at the following link. http://www.excelcampus.com/pivot-table-checklist-yt I have another video that shows how to reformat the pivot chart in Excel 2010. In the video above I'm using Excel 2013 and the menus are different from Excel 2007/2010. Here is the link to that video. http://www.youtube.com/watch?v=Jt_QqG-vRRw Get PivotPal: http://www.excelcampus.com/pivotpal Free webinar on The 5 Secrets to Understanding Pivot Tables: https://www.excelcampus.com/pivot-webinar-yt Subscribe to my free newsletter: http://www.excelcampus.com/newsletter
Views: 6117232 Excel Campus - Jon
Game theory #1||Pure & Mixed Strategy||in Operations research||Solved problem||By:- Kauserwise
 
21:40
Here is the video about Game theory with Pure Strategy and Mixed Strategy - In operations research, in this video we have solved a problem on Pure strategy and Mixed Strategy with some basic terminologies and necessary information about Game theory, What is Player in Game theory, What is Strategy in Game theory, What is Pure strategy and What is Mixed strategy in game theory, What is Payoff matrix in game theory, What is MiniMax properties and What is Maximin property in game theory, what is saddle point in game theory, What is Value of the Game in game theory and Two persons Zero sum game in game theory in simple manner, hope this will help you to get the subject knowledge at the end. if you like this please like, comment, share and subscribe. Thanks and All the best. To watch more tutorials pls visit: www.youtube.com/c/kauserwise * Financial Accounts * Corporate accounts * Cost and Management accounts * Operations Research Playlists: For Financial accounting - https://www.youtube.com/playlist?list=PLabr9RWfBcnojfVAucCUHGmcAay_1ov46 For Cost and Management accounting - https://www.youtube.com/playlist?list=PLabr9RWfBcnpgUjlVR-znIRMFVF0A_aaA For Corporate accounting - https://www.youtube.com/playlist?list=PLabr9RWfBcnorJc6lonRWP4b39sZgUEhx For Operations Research - https://www.youtube.com/playlist?list=PLabr9RWfBcnoLyXr4Y7MzmHSu3bDjLvhu
Views: 246412 Kauser Wise
Linear Programming
 
11:11
Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! **DOH! There is a STUPID arithmetic mistake by me at the very end!** Sorry! Linear Programming. I do a complete example! For more free math videos, visit http://PatrickJMT.com
Views: 909888 patrickJMT
Introduction to matrices
 
11:51
What a matrix is. How to add and subtract them. Practice this yourself on Khan Academy right now: https://www.khanacademy.org/e/matrix_dimensions?utm_source=YTdescription&utm_medium=YTdescription&utm_campaign=YTdescription About Khan Academy: Khan Academy is a nonprofit with a mission to provide a free, world-class education for anyone, anywhere. We believe learners of all ages should have unlimited access to free educational content they can master at their own pace. We use intelligent software, deep data analytics and intuitive user interfaces to help students and teachers around the world. Our resources cover preschool through early college education, including math, biology, chemistry, physics, economics, finance, history, grammar and more. We offer free personalized SAT test prep in partnership with the test developer, the College Board. Khan Academy has been translated into dozens of languages, and 100 million people use our platform worldwide every year. For more information, visit www.khanacademy.org, join us on Facebook or follow us on Twitter at @khanacademy. And remember, you can learn anything.
Views: 1740243 Khan Academy
Statistical Inference Part 1
 
02:11
Statistical Inference Part 1
Views: 248 Rushad Faridi
Probability in R Discrete Random Variables in Financial Engineering
 
09:57
Binomial tree is a method of financial derivatives pricing based on binomial distribution. The tutorial shows an example of calculating call option price using three period binomial tree. As an exercise you can build in R option pricing function and submit yous solution to https://github.com/infermath/R
Views: 70 Infermath
[#1]Assignment Problem|Hungarian Method|Operations Research[Solved Problem using Algorithm]
 
21:46
NOTE: After row and column scanning, If you stuck with more than one zero in the matrix, please do the row scanning and column scanning (REPEATEDLY) as much as possible to cover that zeros with lines, based on algorithm If you still find some zeros without covered by lines, then we need to go for [DIAGONAL selection RULE ]for that I have uploaded a separate video to understand that method easily., please watch this link [ [#2]Assignment Problem||Hungarian Method[DIAGONAL RULE] When we Find More than one Zero ] https://youtu.be/-0DEQmp7B9o ▓▓░───CONTRIBUTION ─░▓▓ If you like this video and wish to support this kauserwise channel, please contribute via, * Paytm a/c : 7401428918 * Western Union / MoneyGram [ Name: Kauser, Country: India & Email: [email protected] ] [Every contribution is encouraging US] Thanks & All the Best!!! ──────────────────── Here is the video about assignment problem - Hungarian method on Operations research, In this video we discussed what is assignment problem and how to solve using Hungarian method with step by step procedure of algorithm, hope this will help you to get the subject knowledge at the end. Thanks and All the best. To watch more tutorials pls use this: www.youtube.com/c/kauserwise * Financial Accounts * Corporate accounts * Cost and Management accounts * Operations Research
Views: 1147803 Kauser Wise
minimal example of using knitr in R
 
10:20
This is a very basic example for using knitr in R. you will see how to produce a pdf with your code and plots in a simple way using R.
Views: 18880 Riccardo Klinger

How to write a cover letter for job application as receptionist
Writing dissertation service
Example of resume cover letters with salary requirements
Layout of a cover letter uk example
Examples of a cover letter for a retail job descriptions