Text mining provides a means of extracting new information from unstructured data. Milliman's Phil Borba uses text mining to examine accident descriptions and can thereby identify instances of distracted driving—including cell phone use, radio use, and other distractions—that might not otherwise be visible. This is but one example of how text mining can extract hidden meaning that was not previously available to property and casualty insurers. For a video transcript, visit http://www.milliman.com/insight/videos/Improving-claim-analytics-through-text-mining/
Views: 893 Milliman, Inc.
What can text analysis tell us about society? Corpora of news, books, and social media encode human beliefs and culture. But it is impossible for a researcher to read all of today's rapidly growing text archives. My research develops statistical text analysis methods that measure social phenomena from textual content, especially in news and social media data. For example: How do changes to public opinion appear in microblogs? What topics get censored in the Chinese Internet? What character archetypes recur in movie plots? How do geography and ethnicity affect the diffusion of new language? In order to answer these questions effectively, we must apply and develop scientific methods in statistics, computation, and linguistics. In this talk I will illustrate these methods in a project that analyzes events in international politics. Political scientists are interested in studying international relations through *event data*: time series records of who did what to whom, as described in news articles. To address this event extraction problem, we develop an unsupervised Bayesian model of semantic event classes, which learns the verbs and textual descriptions that correspond to types of diplomatic and military interactions between countries. The model uses dynamic logistic normal priors to drive the learning of semantic classes; but unlike a topic model, it leverages deeper linguistic analysis of syntactic argument structure. Using a corpus of several million news articles over 15 years, we quantitatively evaluate how well its event types match ones defined by experts in previous work, and how well its inferences about countries correspond to real-world conflict. The method also supports exploratory analysis; for example, of the recent history of Israeli-Palestinian relations.
Views: 1506 Microsoft Research
Writing is an iterative process comprising exploratory, drafting, revising, and editing stages. This technology assists writers by doing most of the hard work during the exploratory stage. Relevant papers in the literature are automatically discovered and presented to the writers in visually-appealing forms to aid the exploration process.
Views: 255 Wilson Wong
Lesson Overview: This lesson starts with the web with its size, shape (coming from the mutual linkage of pages by URL's) and universal power laws for number of pages with particular number of URL's linking out or in to page. The way Web search is performed by users is discussed. Information retrieval is introduced and a possible DIKW mapping for web search is given. A comparison is given between semantic searches as in databases and the full text search that is base of Web search. The ACM classification illustrates potential complexity of ontologies. Some differences between web search and information retrieval are given. Enroll in this course at https://bigdatacourse.appspot.com/ and download course material, see information on badges and more. It's all free and only takes you a few seconds.
Views: 164 SoIC Data Science Courses
If data need to be approximately normally distributed, this tutorial shows how to use SPSS to verify this. On a side note: my new project: http://howtowritecitations.com. Statistical analyses often have dependent variables and independent variables and many parametric statistical methods require that the dependent variable is approximately normally distributed for each category of the independent variable. Let us assume that we have a dependent variable, exam scores, and an independent variable, gender. In short, we must investigate the following numerical and visual outputs (and the tutorial shows how to do just that): -The Skewness & kurtosis z-values, which should be somewhere in the span -1.96 to +1.96; -The Shapiro-Wilk p-value, which should be above 0.05; -The Histograms, Normal Q-Q plots and Box plots, which should visually indicate that our data are approximately normally distributed. Remember that your data do not have to be perfectly normally distributed. The main thing is that they are approximately normally distributed, and that you check each category of the independent variable. (In our example, both male and female data.) Step 1. In the menu of SPSS, click on Analyze, select Descriptive Statistics and Explore. Step 2. Set exam scores as the dependent variable, and gender as the independent variable. Step 3. Click on Plots, select "Histogram" (you do not need "Stem-and-leaf") and select "Normality plots with tests" and click on Continue, then OK. Step 4. Start with skewness and kurtosis. The skewness and kurtosis measures should be as close to zero as possible, in SPSS. In reality, however, data are often skewed and kurtotic. A small departure from zero is therefore no problem, as long as the measures are not too large compare to their standard errors. As a consequence, you must divide the measure by its standard error, and you need to do this by hand, using a calculator. This will give you the z-value, which, as I said, should be somewhere within -1.96 to +1.96. Let us start with the males in our example. To calculate the skewness z-value, divide the skewness measure by its standard error. All z-values in the tutorial video are within ±1.96. We can conclude that the exam score data are a little skewed and kurtotic, for both males and females, but they do not differ significantly from normality. Step 5. Check the Shapiro-Wilk test statistic. The null hypothesis for this test of normality is that the data are normally distributed. The null hypothesis is rejected if the p-value is below 0.05. In SPSS output, the p-value is labeled "Sig". In our example, the p-values for males and females are above 0.05, so we keep the null hypothesis. The Shapiro-Wilk test thus indicates that our example data are approximately normally distributed. Step 6. Next, let us look at the graphical figures, for both male and female data. Inspect the histograms visually. They should have the approximate shape of a normal curve. Then, look at the normal Q-Q plot. The dots should be approximately distributed along the line. This indicates that the data are approximately normally distributed. Skip the Detrended Q-Q plots. You do not need them. Finally, look at the box plots. They should be approximately symmetrical. The video contains references to books and articles. About writing out the results: I would put it under the sub-heading "Sample characteristics", and the video contains examples of how I would write. In this tutorial, I show you how to check if a dependent variable is approximately normally distributed for each category of an independent variable. I am assuming that you, eventually, want to use a certain parametric statistical methods to explore and investigate your data. If it turns out that your dependent variable is not approximately normally distributed for each category of the independent variable, it is no problem. In such case, you will have to use non-parametric methods, because they make no assumptions about the distributions. Good luck with your research. Text and video (including audio) © Kent Löfgren, Sweden Here are the references that I discuss in the video (thanks Abdul Syafiq Bahrin for typing them our for me): Cramer, D. (1998). Fundamental statistics for social research. London: Routledge. Cramer, D., & Howitt, D. (2004). The SAGE dictionary of statistics. London: SAGE. Doane, D. P., & Seward, L.E. (2011). Measuring Skewness. Journal of Statistics Education, 19(2), 1-18. Razali, N. M., & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Liliefors and Anderson-Darling test. Journal of Statistical Modeling and Analytics, 2(1), 21-33. Shapiro, S. S., & Wilk, M. B. (1965). An Analysis of Variance Test for Normality (Complete Samples). Biometrika, 52(3/4), 591-611.
Views: 452925 Kent Löfgren
Download File: https://people.highline.edu/mgirvin/AllClasses/210Excel2013/Ch00/Excel2013StatisticsChapter00.xlsx All Excel Files for All Video files: http://people.highline.edu/mgirvin/excelisfun.htm. Intro To Excel: Store Raw Data, Data Types, Data Analysis, Formulas, PivotTables, Charts, Keyboards, Number Formatting, Data Analysis & More: (00:08) Introduction to class (00:49) Cells, Worksheets, Workbooks, File Names (02:54) Navigating Worksheets & Workbook (03:58) Navigation Keys (04:15) Keyboard move Active Sheet (05:40) Ribbon Tabs (06:25) Add buttons to Quick Access Tool Bar (07:40) What Excel does: Store Raw Data, Make Calculations, Data Analysis & Charting (08:55) Introduction to Data Analysis (10:37) Data Types in Excel: Text, Numbers, Boolean, Errors, Empty Cells (11:16) Keyboard Enter puts content in cell and move selected cell down (13:00) Data Type DEFAULT Alignments (13:11) First Formula. Entering Cell References in formulas (13:35) Keyboard Ctrl + Enter puts content in cell & keep cell selected (14:45) Why we don’t override DEFAULT Alignments (15:05) Keyboard Ctrl + Z is Undo (17:05) Proper Data Sets & Raw Data (24:21) How To Enter Data & Data Labels (24:21) Stylistic Formatting (26:35) AVERAGE Function (27:31) Format Formulas Differently than Raw Data (28:30) Keyboard Ctrl + C is Copy. Keyboard Ctrl + V is Paste (29:59) Use Eraser remove Formatting Only (29:19) Keyboard Ctrl + B adds Bold (29:57) Excel’s Golden Rule (31:43) Keyboard F2 puts cell in Edit Mode (32:01) Violating Excel’s Golden Rule (34:12) Arrow Keys to put cell references in formulas (35:40) Full Discussion about Formulas & Formulas Elements (37:22) SUM function Keyboard is Alt + = (38:22) Aggregate functions (38:50) Why we use ranges in functions (40:56) COUNT & COUNTA functions (42:47) Edit Formula & change cell references (44:18) Absolute & Relative Cell References (45:52) Use Delete Key, Not Right-click Delete (46:40) Fill Handle & Angry Rabbit to copy formula (47:41) Keyboard F4 Locks Cell Reference (make Absolute) (49:45) Keyboard Tab puts content in Cell and move selected Cell to right (50:55) Order of Operation error (52:17) Range Finder to find formula errors (52:34) Lock Cell Reference after you put cell in Edit Mode (53:58) Quickly copy an edited formula down a column (53:07) F2 key in last cell to find formula errors (54:15) Fix incorrect range in function (54:55) SQRT function & Fractional Exponents (57:20) STDEV.P function (58:10) Navigate Large Data Sets (58:48) Keyboard Ctrl + Arrow jumps to bottom of data set (59:42) Keyboard Ctrl + Shift + Arrow selects to bottom of data set (Current Range) (01:01:41) Keyboard Shift + Enter puts content in Cell and move selected Cell up (01:02:55) Counting with conditions or criteria: COUNTIFS function (01:03:43) Keyboard Ctrl + Backspace jumps back to Active Cell (01:05:31) Counting between an upper & lower limit with COUNTIFS (01:07:36) COUNTIFS copied down column (01:10:08) Joining Comparative Operator with Cell Reference in formula (01:12:50) Data Analysis features in Excel (01:13:44) Sorting (01:16:59) Filtering (01:20:39) Introduction to PivotTables (01:23:39) Create PivotTable dialog box (01:24:33) Dragging & dropping Fields to create PivotTable (01:25:31) Dragging Field to Row area creates a Unique List (01:26:17) Outline/Tabular Layout (01:27:00) Value Field Settings dialog to change: Number Formatting, Function, Name (01:28:12) 2nd & 3rd PivotTable examples (01:31:23) What is a Cross Tabulated Report? (01:33:04) Create Cross Tabulated Report w PivotTable (01:35:05) Show PivotTable Field List (01:36:48) How to Pivot the Report (01:37:50) Summarize Survey Data with PivotTable. (01:38:34) Keyboard Alt, N, V opens PivotTable dialog box (01:41:38) PivotTable with 3 calculations: COUNT, MAX & MIN (01:43:25) Count & Count Number calculations in a PivotTable (01:45:30) Excel 2013 Charts to Visually Articulate Quantitative Data (01:47:00) #1 Rule for Charts: No Chart Junk! (01:47:30) Explain chart types: Column, Bar, Pie, Line and X-Y Scatter Chart (01:51:34) Create Column Chart using Recommended Chart feature (01:53:00) Remove Field Buttons from Pivot Chart (01:54:10) Chart Formatting Task Pane (01:54:45) Vary Fill Color by point (01:55:15) Format Axis with Numbers by Formatting Source Data in PivotTable (01:56:02) Add Data Labels to Chart (01:57:28) Copy Chart & Create Bar Chart (01:57:48) Change Chart Type (01:58:15) Change Gap Width. (01:59:17) Create Pie Chart (01:59:23) Do NOT use 3-D Pie (01:59:42) Add % Data Labels to Pie Chart (02:00:25) Create Line Chart From PivotTable (02:01:20) Link Chart Tile to Cell (02:02:20) Move a Chart (02:02:33) Create an X-Y Scatter Chart (02:03:35) Add Axis Labels (02:05:27) Number Formatting to help save time (02:07:24) Number Formatting is a Façade (02:10:27) General Number Format (02:10:52) Percentage Number Formatting (02:14:03) Don’t Multiply Relative Frequency by 100 (02:17:27) Formula for % Change & End Amount
Views: 431313 ExcelIsFun
http://www.ted.com Have you played with Google Labs' NGram Viewer? It's an addicting tool that lets you search for words and ideas in a database of 5 million books from across centuries. Erez Lieberman Aiden and Jean-Baptiste Michel show us how it works, and a few of the surprising things we can learn from 500 billion words. TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes. Featured speakers have included Al Gore on climate change, Philippe Starck on design, Jill Bolte Taylor on observing her own stroke, Nicholas Negroponte on One Laptop per Child, Jane Goodall on chimpanzees, Bill Gates on malaria and mosquitoes, Pattie Maes on the "Sixth Sense" wearable tech, and "Lost" producer JJ Abrams on the allure of mystery. TED stands for Technology, Entertainment, Design, and TEDTalks cover these topics as well as science, business, development and the arts. Closed captions and translated subtitles in a variety of languages are now available on TED.com, at http://www.ted.com/translate.
Views: 215250 TED
*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: 358636 MIT OpenCourseWare
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Views: 5274 BO Turbo Trader
Welcome to Crash Course Statistics! In this series we're going to take a look at the important role statistics play in our everyday lives, because statistics are everywhere! Statistics help us better understand the world and make decisions from what you'll wear tomorrow to government policy. But in the wrong hands, statistics can be used to misinform. So we're going to try to do two things in this series. Help show you the usefulness of statistics, but also help you become a more informed consumer of statistics. From probabilities, paradoxes, and p-values there's a lot to cover in this series, and there will be some math, but we promise only when it's most important. But first, we should talk about what statistics actually are, and what we can do with them. Statistics are tools, but they can't give us all the answers. Episode Notes: On Tea Tasting: "The Lady Tasting Tea" by David Salsburg On Chain Saw Injuries: https://www.cdc.gov/disasters/chainsaws.html https://www.ncbi.nlm.nih.gov/pubmed/15027558 https://www.hindawi.com/journals/aem/2015/459697/ Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Mark Brouwer, Nickie Miskell Jr., Jessica Wode, Eric Prestemon, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Divonne Holmes à Court, Brian Thomas Gossett, Khaled El Shalakany, Indika Siriwardena, Robert Kunz, SR Foxley, Sam Ferguson, Yasenia Cruz, Daniel Baulig, Eric Koslow, Caleb Weeks, Tim Curwick, Evren Türkmenoğlu, Alexander Tamas, Justin Zingsheim, D.A. Noe, Shawn Arnold, mark austin, Ruth Perez, Malcolm Callis, Ken Penttinen, Advait Shinde, Cody Carpenter, Annamaria Herrera, William McGraw, Bader AlGhamdi, Vaso, Melissa Briski, Joey Quek, Andrei Krishkevich, Rachel Bright, Alex S, Mayumi Maeda, Kathy & Tim Philip, Montather, Jirat, Eric Kitchen, Moritz Schmidt, Ian Dundore, Chris Peters, Sandra Aft, Steve Marshall Want to find Crash Course elsewhere on the internet? Facebook - http://www.facebook.com/YouTubeCrashC... Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids
Views: 547397 CrashCourse
This video is about an Introduction to Statistics. "On Your Own" ANSWERS 1a) Yes, it is a statistical question because you would expect the ages of people who retire early to vary. b) Cluster around 60. Peak at 60 and two gaps, one between 56 and 58 and the other between 62 and 64. c) Most people who retire early are about 60 years old. 2a) 20 students ran the race (there are 20 data points) b) You can collect these data with a stopwatch. The units would be seconds. c) Question: "How long does it take a sixth grade student to run 100 meters?" Answer: It takes most sixth graders about 13.8 seconds to run 100 meters.
Views: 499918 Anywhere Math
ПОЛЕЗНЫЕ СОВЕТЫ: идеи для постов, полезные ссылки, лимиты, рекомендации | Урок 7 # ИНСТАГРАМ спикер Ольга Полякова инстаграм https://www.instagram.com/olgavzlet/ Статистика вашего аккаунта: http://ink361.com/ https://pro.iconosquare.com/ http://www.spellfeed.com/analytics/ Программы для загрузки видео и фото в ваш аккаунт через компьютер: Gramblr (http://gramblr.com/ ) Grum (https://www.grum.co/ ) Программы для обработки фото и видео: Layout –создание коллажей Hyperlapse – стабилизация и ускорение видео Boomerang – создание секундных видео которые проигрываются вперёд и назад. Snapseed – профессиональная обработка снимков в телефоне PicsArt – фоторедактор Instapan - превращает фотопанораму в видеоролик, который медленно прокрутит изображение и поможет продемонстрировать всё, что вас окружает. PhotoRepost – репост публикации в свой профиль InstaShot - выложит ваше необрезанное прямоугольное видео в ленту, а также фотографию. InstaSave – скачивание фотографий из любых публикаций ========================================== Спасибо большое за ваши лайки и комментарии! Если вы хотите добавить это видео на свой канал, под видео Есть кнопочка "+ Добавить в". Нажмите ее и добавьте видео в любой плейлист на своем канале. Если вы скачиваете видео и заливаете на свой канал вручную, то ваш канал может быть заблокирован за размещение чужого контента! Подписаться на канал ПРЕДПРИНИМАТЕЛИ ВЗЛЕТ http://goo.gl/M0oF2B life канал Ольги и Алексея http://goo.gl/2M923F Зарегистрироваться в Орифлэйм: http://ivzlet.com/index/0-3 код активации 1 Инстаграм https://www.instagram.com/olgavzlet/ Перископ https://www.periscope.tv/OlgaPoliakova Наша группа в VK http://vk.com/oriflamevzlet ПРИСОЕДИНЯЙТЕСЬ!!! Другие плейлисты на нашем канале: #ТЕХНИКА ПРОДАЖ https://goo.gl/oRpkYw #ДИАЛОГИ ПО-ШВЕДСКИ https://goo.gl/eLlBfP ВСЕ НАШИ ОБЗОРЫ НОВИНОК ОРИФЛЭЙМ https://goo.gl/vkRu1q #ШКОЛА МАКИЯЖА https://goo.gl/T24b27 #АУДИОКНИГИ https://goo.gl/ZSG5H2
Views: 1383 ВЗЛЕТ
Import Data, Copy Data from Excel (or other spreadsheets) to R: CSV & TXT Files with Free Practice Dataset: (https://bit.ly/2rOfgEJ) Need More Statistics and R Programming Tutorials? (https://bit.ly/2Fhu9XU) How to Import CSV data into R or How to Import TXT files into R from Excel or other spreadsheets using function in R ►How to import CSV data into R? We will be using "read.table" function to import comma separated data into R ► How to import txt data file into R? You will learn to use "read.delim" function to import the tab-delimited text file into R ► You will also learn to use "file.choose" argument for file location, "header" argument to let R know the data has headers or variable names and "sep" argument to let R know how the data values are separated. ►►Download the dataset here: https://statslectures.com/r-scripts-datasets ►►Like to support us? You can Donate https://bit.ly/2CWxnP2 or Share the Videos! ►► Watch More: ► Intro to Statistics Course: https://bit.ly/2SQOxDH ►R Tutorials for Data Science https://bit.ly/1A1Pixc ►Getting Started with R (Series 1): https://bit.ly/2PkTneg ►Graphs and Descriptive Statistics in R (Series 2): https://bit.ly/2PkTneg ►Probability distributions in R (Series 3): https://bit.ly/2AT3wpI ►Bivariate analysis in R (Series 4): https://bit.ly/2SXvcRi ►Linear Regression in R (Series 5): https://bit.ly/1iytAtm ►ANOVA series https://bit.ly/2zBwjgL ►Linear Regression Concept and with R https://bit.ly/2z8fXg1 ►Puppet Master of Statistics: https://bit.ly/2RDAAv4 ►Hypothesis Testing: Concepts in Statistics https://bit.ly/2Ff3J9e ◼︎ Table of Content 0:00:17 What are the two main file types for saving a data file (CSV and TXT) 0:00:36 How to save an Excel file as a CSV file (comma-separated value) 0:01:10 How to open a CSV data file in Excel 0:01:20 How to open a CSV file in a text editor 0:01:36 How to import CSV file into R? using read.csv function 0:01:44 How to access the help menu for different commands/functions in R 0:02:04 How to specify file location for R? using file.choose argument on read.csv function 0:02:31 How to let R know our data has headers or variable names when importing the data into R? By using the “header” argument on read.csv function 0:03:22 How to import CSV file into R? using read.table function 0:03:38 How to specify the file location for the read.table function in R? using file.choose argument 0:03:46 How to specify how variables/columns are separated when importing data into R? the "sep" argument on read.table function will do that; for example if you don't specify that your data is comma separated, R ends up reading it all in as one variable 0:04:10 How to save a file in Excel as tab-delimited text (TXT) file 0:04:50 How to open a tab-delimited (.TXT) data file in a text editor 0:05:07 How to open a tab-delimited (.TXT) data file in excel 0:05:20 How to import tab-delimited (.TXT) data file into R? using read.delim function 0:05:44 How to specify the file path for read.delim function in R? using file.choose argument 0:06:06 How to import tab-delimited (.TXT) data file into R? using read.table function 0:06:23 How to specify that the data has headers or variable names when importing the data into R? using header argument on read.table function This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support some courses at The University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Views: 594529 MarinStatsLectures- R Programming & Statistics
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: 184082 APMonitor.com
Reference: (Book) An Introduction to Statistical Learning with Applications in R (Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani) http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Fourth%20Printing.pdf Reference (Lecture Notes)  With permission from Dr. Tibshirani and Dr. Hastie, the Lecture notes are adopted from Stanford-Online StatLearning Statistical Learning  With permission from Dr. Al Sharif (USC) part of the Lecture notes were adopted from "DSO 530: Applied Modern Statistical Learning Techniques".
Views: 35401 Hamed Hasheminia
George Orwell is the most famous English language writer of the 20th century, the author of Animal Farm and 1984. What was he trying to tell us and what is his genius? If you like our films, take a look at our shop (we ship worldwide): https://goo.gl/vSiVRh Join our exclusive mailing list: http://bit.ly/2e0TQNJ Or visit us in person at our London HQ https://goo.gl/90vzcY FURTHER READING You can read more on our great thinkers at our blog: TheBookofLife.org at this link: https://goo.gl/Ne28ro MORE SCHOOL OF LIFE Our website has classes, articles and products to help you think and grow: https://goo.gl/7w22rM Watch more films on Literature and our Curriculum in our playlist: http://bit.ly/TSOLcapitalism Do you speak a different language to English? Did you know you can submit Subtitles on all of our videos on YouTube? For instructions how to do this click here: https://goo.gl/rU7lhw SOCIAL MEDIA Feel free to follow us at the links below: Facebook: https://www.facebook.com/theschooloflifelondon/ Twitter: https://twitter.com/TheSchoolOfLife Instagram: https://www.instagram.com/theschooloflifelondon/ CREDITS Produced in collaboration with: Mike Booth http://www.youtube.com/somegreybloke #TheSchoolOfLife
Views: 939884 The School of Life
Could society actually be on the brink of a paradigm shift on how we use books? Will digital actually make us read more than ever before? And how will the way we read change? In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
Views: 1395 TEDx Talks
Keyword search provides a user-friendly information dis- covery mechanism for web users to easily access XML data without the need of learning a structured query language or studying possibly complex and evolving data schemas. How- ever, due to the lack of expressivity and inherent ambiguity, there are two main challenges in performing keyword search on XML data intelligently. 1. First, unlike XQuery, where the connection among data nodes matching a query is speci¯ed precisely using variable bindings and where clauses, we need to au- tomatically connect the keyword matches in a mean- ingful way. 2. Second, unlike XQuery, where the data nodes to be returned are speci¯ed using a return clause, we should e®ectively identify the desired return information. Several attempts have been made to address the ¯rst chal- lenge [3, 2, 9, 7] by selecting and connecting keyword matches through a variant concept of lowest common ancestor, named as VLCA (such as SLCA , MLCA , interconnection , etc.). However, it is an open problem of how to automat- ically and e®ectively infer return nodes, the names of the data nodes that are the goal of user searches. There are two baseline approaches for determining return nodes adopted in the existing work. One is to return the subtrees rooted at VLCA nodes [3, 9], named as Subtree Return. Alternatively, we can return the paths in the XML tree from each VLCA node to its descendants that match an input keyword, as described in [1, 4], named as Path Return. However, neither approach is e®ective in identifying return information as the following examples show. Let us look at the sample queries listed in Figure 2 on XML data in Figure 1(a). For Q1, it is likely that a user is interested in the information about Rockets. Both Subtree Return and Path Return ¯rst compute the VLCA of keyword matches, which is the match node itself: Rockets (0.2.0.0), then output this node. However, to echo print the user FOR MORE INFORMATION VISIT US AT http://www.seocertification.org.in/ http://www.seocertification.org.in/seo-training.php http://www.seocertification.org.in/sem-training.php http://www.seocertification.org.in/ppc.php http://www.seocertification.org.in/books.php http://www.seocertification.org.in/online-examination.php
Views: 112 seocertification
Presented June 13, 2018. Data mining in PubMed may require the analysis of thousands of records. The E-utilities efetch service often limits your ability to retrieve large numbers of records in a short time. As you will see in this webinar, EDirect allows you much faster access by operating on a local copy of PubMed. EDirect includes an archive-pubmed script that fully automates the download, update, extraction, and storage process. EDirect's Local Data Cache uses a hierarchy of 1 million folders to organize the 28 million PubMed files and provides direct and rapid access to any record. These features use recent advances in computer file system technology to repackage all of PubMed as individual files on an inexpensive 500 gigabyte external solid state drive. In this webinar, you will learn how to use EDirect to install PubMed locally and then search and retrieve records from the local instance. You will also see an analysis example that shows the significant speed improvement with the Local Cache and employs some advanced EDirect xtract options to aid with processing records. EDirect: https://www.ncbi.nlm.nih.gov/books/NBK179288/ To get video updates, subscribe to the NCBI YouTube channel: www.youtube.com/ncbinlm
Views: 1062 NCBI
How to create a bar chart in SPSS is illustrated. Check out our next text, 'SPSS Cheat Sheet,' here (google tiny url link): http://goo.gl/b8sRHa. Amazon Prime and 'Unlimited' members, get our text for free. (Currently only $4.99 otherwise, but may increase in the coming months.) Step by step instructions provided. For our SPSS video series, click here: SPSS Descriptive Statistics Videos: http://tinyurl.com/m4srgoh SPSS Inferential Statistics Videos: http://tinyurl.com/lm9hpwc To create a histogram in SPSS, click here: http://youtu.be/06QOdHv68pM For a stem and leaf plot: http://youtu.be/XZtf-n_lWDI Lifetime access to SPSS videos: http://tinyurl.com/kuejrzz Lifetime access to SPSS videos: http://tinyurl.com/m2532td YouTube Channel: https://www.youtube.com/user/statisticsinstructor Transcript of Video - How to Create a Bar Chart in SPSS - Bar Graph In this tutorial we'll look at how to construct a bar graph or bar chart in SPSS. And here we have the variable car color, where we have 15 different cars that were observed ; as people drove by, someone noted the color of the car. And what I've done in this example is I've already entered my value labels so, for example, if I click this button right up here [the value labels button is clicked], then I'll see the colors that the different numbers correspond to. So notice that we have 4 white cars that were observed and so forth. I'm going to turn the value label off for now, but you'll see how they're very useful in a moment when we produce a bar graph. To produce a bar graph in spss, let's go to analyze and then descriptive statistics and, we can actually use the frequencies command to produce a bar graph, and the we can also use the graphs command - I'll show you both ways. To produce a bar graph using the frequencies procedure, go to Analyze, and then Descriptive Statistics, and then Frequencies, and then you should see your window open and it should look like this. I'm going to move car color over to the variables box, select charts, and then here we want to select bar chart, click continue. Let's deselect the display frequencies table and then click OK. Notice here we get a bar chart where the variable is car color on the x-axis, the frequency is on the y-axis. We have our different car colors here and the height of the bar indicates the frequency or how many of each color car was observed. So we have 2 black cars were observed, 4 white cars, 6 blue cars, 2 red cars, and 1 green car. Now, many of the options on this chart can be modified, and I'll show you one quick modification we can do. If I double-click on this chart, what will happen is the chart editor will open as you see here, and I'm going to double-click on any of these bars. When I do that the properties dialog box opens. Let's go ahead and go to fill and border (click on that tab); and I'll select this blue color right here and then click apply. Then close this window out. Notice what happened here -- now my bars are blue. This is one of the many options that can be modified in our charts. Let's go ahead and close this out -- so click X -- now we have our chart and notice the blue color has been applied. As I said at the beginning I was going to show you how to obtain this exact same chart using the graphs menu command in spss. To do so, select Graphs, and then Legacy Dialogs, and then Bar. Now here a bar chart dialog box opens; I want to leave the default options in place. So just click define. You should see a window like this with car color on the left. Go ahead and move that to the category axis box and then click ok. You should see that this gives us the exact same bar chart with the only exception that I haven't modified the color to be blue. In summary, we saw how to obtain a bar chart using two different approaches -- both the frequencies procedure and the graphs legacy dialog command. This concludes the tutorial on obtaining a bar chart in SPSS. Channel Description: For step by step help with statistics, with a focus on SPSS. Both descriptive and inferential statistics covered. For descriptive statistics, topics covered include: mean, median, and mode in spss, standard deviation and variance in spss, bar charts in spss, histograms in spss, bivariate scatterplots in spss, stem and leaf plots in spss, frequency distribution tables in spss, creating labels in spss, sorting variables in spss, inserting variables in spss, inserting rows in spss, and modifying default options in spss. For inferential statistics, topics covered include: t tests in spss, anova in spss, correlation in spss, regression in spss, chi square in spss, and MANOVA in spss. New videos regularly posted. Videos series coming soon include: multiple regression in spss, factor analysis in spss, nonparametric tests in spss, multiple comparisons in spss, linear contrasts in spss, and many more. Subscribe today! YouTube Channel: https://www.youtube.com/user/statisticsinstructor
Views: 244606 Quantitative Specialists
www.epcgroup.net | [email protected] | Phone: (888) 381-9725 * SharePoint Server 2013, SharePoint Server 2010, and SharePoint 2007: Review, Architecture Development, Planning, Configuration & Implementations, Upgrades, Global Initiatives, Training, and Post Go-live Support with Extensive Knowledge Transfer * Health Check and Assessments (Roadmap Preparation to Upgrade to 2013 or 2010) - Including Custom Code & Solution Review * Enterprise Content Management Systems based on Microsoft SharePoint * Enterprise Metadata Design, Taxonomy | Retention Schedule Development | Disposition Workflow, and Records Management Implementations * Roadmap, Requirements Gathering, Planning, Designing, and Performing the Actual Implementation * Best Practices Consulting on SharePoint 2013, 2010, 2007 | EPC Group has completed over 725+ initiatives * Intranet, Knowledge Management, Internet and Extranet-Facing as Well as Mobility (BYOD Roadmap), Cloud, Hybrid, and Cross-Browser | Cross-Platform Solutions for SharePoint 2013 / 2010 with Proven Past-performance *Upgrades or Migrations of Existing Deployments or Other LOB Systems (Documentum, LiveLink, FileNet, SAP, etc.) using EPC Group's Proven Methodologies (On-Premises, Hybrid, Virtualized, or Cloud-Based Infrastructure Design) * Custom Application, Feature, Master Pages, Web Parts, Security Model, Usability (UI), and Workflow Development (i.e. Visual Studio 2012) * Migration Initiatives to SharePoint 2013 / SharePoint 2010 * Key Performance Indicators, Dashboard & Business Intelligence Reporting Solutions (PerformancePoint 2013, SQL Server 2012, BI, KPIs, PowerPivot, Scorecards, Big Data Experts) * Experts in Global \ Enterprise Infrastructure, Security, Hardware Configuration & Disaster Recovery (Global performance considerations, multilingual, 1mm+ user environment experience) * Tailored SharePoint "in the trenches" Training on SharePoint 2013, 2010, 2007 as well as Project Server and Custom Development Best Practices * Support Contracts (Ongoing Support your Organization's 2013, 2010, or 2007 Implementations) * .NET Development, Custom applications, BizTalk Server experts * Project Server 2013, 2010, and 2007 Implementations and Consulting * SharePoint Roadmap & Governance Development: 6, 12, 18, 24 and 36 months (Steering Committee & Code Review Board Development) * Corporate Change Management & End User Empowerment Strategies * EPC Group's WebpartGallery.com - Customized Web Parts Based off of "in the trenches" Client Needs With over 14 years of experience, EPC Group delivers time tested SharePoint methodologies that ensure success within your organization. Engagement with EPC Group carries unique offerings and knowledge. Currently having implemented over 725+ SharePoint engagements and 75+ Microsoft Project Server implementations, we are the nation's leading SharePoint and Microsoft platform related consulting firm. EPC Group will be releasing our 3rd SharePoint book in August of 2013 by Sams Publishing titled, "SharePoint 2013 Field Guide: Advice from the Consulting Trenches" which will be like having a team of Senior SharePoint 2013 consultants by your side at each turn as you implement this new powerful and game changing software platform within your organization. SharePoint 2013 Field Guide: Advice from the Consulting Trenches will guide you through all areas of a SharePoint initiative from the initial whiteboarding of the overall solutions to accounting for what your organization currently has deployed. It will assist you in developing a roadmap and detailed step-by-step implementation plan and will also cover implementation best practices, content management and records management methodologies, initial SharePoint 2013 development best practices, as well as mobility planning. SharePoint 2013, Microsoft SharePoint 2013, SharePoint Consulting, Microsoft SharePoint consulting, SharePoint Consulting Firm, Top SharePoint Firm, SharePoint 2013 Consulting,SharePoint 2010 Consulting, SharePoint ECM Consulting, SharePoint branding firm, SharePoint, SharePoint branding experts, ECM experts SharePoint, Errin O'Connor, EPC Group, EPC Group.net, BizTalk Consulting, Project Server Consulting, BYOD, SharePoint 2013 book, SharePoint 2013 advice from the trenches
Views: 200 EPC Group.net
In this video I explain how SVM (Support Vector Machine) algorithm works to classify a linearly separable binary data set. The original presentation is available at http://prezi.com/jdtqiauncqww/?utm_campaign=share&utm_medium=copy&rc=ex0share
Views: 543261 Thales Sehn Körting
Welcome to AMP Conf 2019! The AMP team and community are excited to bring you the latest updates and announcements. Hear about the roadmap for 2019 and beyond, live from Tokyo, Japan! Subscribe to the AMP ⚡ YouTube channel → http://bit.ly/AMPsubscribe AMP Conf '19 all sessions playlist → http://bit.ly/AmpConf2019 Get started → https://amp.dev/ Learn web development with AMP! Beginner, intermediate, & advanced courses offered → http://bit.ly/AMPcourses Event photo album → http://bit.ly/AMPconf19photos Speaker(s): Malte Ubl, Google
Views: 4007 The AMP Channel
Семинар сегодня будет состоять из двух тем (больше вес у второй темы): 1. Стандартный анализ одномерных временных рядов в R. Основной материал: A Little Book of R for TS, ; Подвохи при работе с временными рядами: R_TS_issues. 2. Оценка VAR и SVAR моделей (рассмотрим только стационарные VAR). Основной материал: vars package.
Views: 1477 Nikolay Arefiev
SAS Education offers you to join the Master Class " From Data to Data Visualization" to learn how to: - Detect new phenomenas - Go beyond of what you can do with your datas - Broadcast your guidance through relevant and impactful visuals Hosted by Bernard Lebelle Graduated of EDHEC Business School and founder of Bleu Cobalt, limited to 8 people groups, get the benefit of rich and interactive discussions. We look forward to meeting you soon, If you need any further information, feel free to contact us : http://www.sas.com/fr_fr/events/14/MASTERCLASS-SAS-DATA-VISUALISATION/presentation.html
Views: 152 SAS France
DEZL Digital Marketing Solutions Deborah Petersen Enrico Suarez Zack Tysiak Logan Watson-Page OBJECTIVE: Increase exposure, awareness, and sales to executives in India and the Greater Toronto Area who are interested in a fishing & dining adventure. 0:48 Solution 1: Weekly Videos Details: Each week, a representative of the business will upload videos to YouTube and link them on their social media pages. The videos will provide tips, advice, and answers to potential questions for those who are interested in cottage-life. Some examples would be Q and A’s (addressing any questions received via social media, e-mail, their webpage, etc.), tips on packing for a vacation, advice on fishing gear/lures, virtual tours of the cottages, etc. This type of content will help the business to build a relationship with potential consumers and give them an idea of the types of things they would be able to enjoy if they book a package. Why: Virtual reality is becoming increasingly popular as a marketing tool, so incorporating some virtual tours into video content may set these videos apart from others on the market. Videos are popular on social media and may have a more positive effect and likelihood of being viewed by consumers than just photos or text. Another aspect worth mentioning is the popularity of YouTube videos among Gen X’ers, whose top 3 interests for video content is nostalgic/past events, current events, and learning/how-to videos (McGee, 2017). When it comes to millennials, building an experience is crucial to gaining their attention, whereas Gen X is all about the practicality of their purchase, which are both something that these videos offer (Richardson, 2018). The number of likes, shares, and comments will indicate the effectiveness of the videos and provide a means of measurability. 1:48 Solution 2: Spin to Win Giveaway Details: When a consumer clicks the link, they will be brought to a sub-page on the company’s website with a Spin to Win Giveaway. The consumer clicks a wheel which spins and randomly selects a giveaway option. Each wedge has a different value, like 5, 10, or 15% off their booking with one of the twelve being a 25% off wedge. Codes for each value will be unique and be provided after the consumer inputs their e-mail. The codes may be used via the website or in-person when booking. We will be able to measure its effectiveness by how many discount codes are actually used by customers. Why: This type of interactive content will help increase web traffic to the business’ page which will increase awareness. Consumers enjoy interactive content, and by including a discount code, it will also help promote sales. Whether it is through an e-mail, social media post, or a giveaway, offering a discount is a great incentive for customers to choose this business over a competitor’s, and if their experience is as good as advertised, they may even become repeat customers (Tanase, 2018). 2:58 Solution 3: Email Blasts Details: Encourage consumers to register for e-mail subscriptions through social media platforms such as Linkedin and Facebook. Our target market is for executives and high-end customers, which typically includes older generations as they are likely to hold executive positions with higher income levels. There are high percentages of executives using Linkedin (Andreou, 2018, p. 26), and according to Statistica, 15% of Indians use Linkedin and 30% use Facebook. (Statista, 2018). Another important consideration is that e-mail is the most widely used means of communication on the internet for older people with “93% of baby boomers (1946-1964) actively using email, and 61% of them [using] it on a daily basis” (Andreou, 2018, p.79). Why: By combining social media as a means of advertising we can measure outcoming links by having post that links to our main page that consumers can use to register for weekly news flyers and potential deals (discounts, free stay, etc.). On the website’s main page, it could also be altered so that consumers can buy packages online as “75% of baby boomers buy products online” (Andreou, 2018, p.80). Using Google Analytics to see who registers and compare bounces would provide a means of measurability (Andreou, 2018, p. 31 and p.86).
Views: 32 Enrico Suarez
Abba Elijah also known as elijagod (elija_god) http://www.elijagod.com/ http://abbaelijah.hubpages.com/ http://facebook.com/abba.elijah/
Views: 104 Abba Elijah
Minecraft Tutorial Playlist ► http://www.youtube.com/playlist?list=PLEB388783144C45A8 This video will show you how to display your health in the tab screen and other places. Minecraft: Red Sand Converter Tutorial (Minecraft 1.8) https://www.youtube.com/watch?v=wtBS62Xyoa4&list=PLEB388783144C45A8&index=11 Minecraft: Supercharged Cake Trap Tutorial https://www.youtube.com/watch?v=5_bJ78lC0VM&list=PLEB388783144C45A8&index=18 Links! ● Second Channel http://bit.ly/xisumatwo ● Livestreams http://www.twitch.tv/xisuma ● Twitter http://bit.ly/xisuma_twitter ● Facebook http://on.fb.me/xisuma_facebook ● Website http://www.xisumavoid.com ● Donate / Support http://www.xisumavoid.com/support Last of stat's that can be used ie stat.animalsBred "animalsBred", "armorCleaned", "bannerCleaned", "beaconInteraction", "boatOneCm", "brewingstandInteraction", "cakeSlicesEaten", "cauldronFilled", "cauldronUsed", "chestOpened", "climbOneCm", "craftingTableInteraction", "crouchOneCm", "damageDealt", "damageTaken", "deaths", "dispenserInspected", "diveOneCm", "drop", "dropperInspected", "enderchestOpened", "fallOneCm", "fishCaught", "flowerPotted", "flyOneCm", "furnaceInteraction", "hopperInspected", "horseOneCm", "itemEnchanted", "jump", "junkFished", "leaveGame", "minecartOneCm", "mobKills", "noteblockPlayed", "noteblockTuned", "pigOneCm", "playerKills", "playOneMinute", "recordPlayed", "sprintOneCm", "swimOneCm", "talkedToVillager", "timeSinceDeath", "tradedWithVillager", "trappedChestTriggered", "treasureFished" , "walkOneCm" and in 1.9 "sneakTime"
Views: 258519 xisumavoid
Lecture video for “Data Sense: An Introduction to Statistics for the Behavioral Sciences” by Barton Poulson. This video covers Chapter 01: Introduction, Section 01: Storytelling. It explains how data analysis is a form of storytelling and how the principles of good storytelling can be applied to data. The book and complete set of videos may be purchased at http://kendallhunt.com/poulson/.
Views: 1753 Barton Poulson
For numerical data with one or more variables, descriptive statistics are used to summarize the empirical distribution of each variable. Windows Excel can calculate descriptive statistics using the Data Analysis Toolpak, which you should already have enabled as an add-in for Excel. First, start Excel and open your data set. I will assume that your data is arranged with the variables as columns and that your data also includes column headings. Next, click the Data tab and choose Data Analysis. If you do not see the Data Analysis option here, then you have not enabled the Data Analysis Toolpak correctly. In the next box, select Descriptive Statistics and click OK. You will then be presented with a dialog box requiring several inputs. For the Input Range, select the rectangular array of cells around the numerical columns that you would like to analyze. Click that labels are in the first row, and be sure to click the option for Summary Statistics. Other options can safely be left at their defaults. Then click OK. After a moment, Excel will produce a new tab with the desired descriptive statistics.
Views: 52532 Sam Burer
Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/probability/probability-and-combinatorics-topic/permutations/e/permutations_1?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Watch the next lesson: https://www.khanacademy.org/math/probability/probability-and-combinatorics-topic/permutations/v/zero-factorial-or-0?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/probability-and-combinatorics-topic/permutations/v/permutation-formula?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: 271911 Khan Academy
Enter and define variables from a questionnaire in SPSS. This example looks at a multiple response question in which a participant can 'tick all that apply'. ASK SPSS Tutorial Series
Views: 81246 BrunelASK
Here we give you a set of numbers and then ask you to find the mean, median, and mode. It's your first opportunity to practice with us! Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/probability/descriptive-statistics/central_tendency/e/mean_median_and_mode?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Watch the next lesson: https://www.khanacademy.org/math/probability/descriptive-statistics/central_tendency/v/exploring-mean-and-median-module?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/descriptive-statistics/central_tendency/v/statistics-intro-mean-median-and-mode?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: 2086372 Khan Academy
Check out my Blog: http://exceltraining101.blogspot.com This video show how to create a win-loss chart. A common use case is that this chart will help to visually show how a team is doing over time; how times they are winning or losing. There are 2 examples on how to create this: one using the sparkline win/loss feature and the other using the chart engine. P.S. Feel free to provide a comment or share it with a friend! #exceltips #exceltipsandtricks #exceltutorial #doughexcel --------------------- Excel Training: https://www.exceltraining101.com/p/training.html Excel Books: https://www.amazon.com/shop/dough
Views: 15942 Doug H
Data mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), an interdisciplinary subfield of computer science, is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The term is a misnomer, because the goal is the extraction of patterns and knowledge from large amount of data, not the extraction of data itself. It also is a buzzword, and is frequently also applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support system, including artificial intelligence, machine learning, and business intelligence. The popular book "Data mining: Practical machine learning tools and techniques with Java" (which covers mostly machine learning material) was originally to be named just "Practical machine learning", and the term "data mining" was only added for marketing reasons. Often the more general terms "(large scale) data analysis", or "analytics" -- or when referring to actual methods, artificial intelligence and machine learning -- are more appropriate. This video is targeted to blind users. Attribution: Article text available under CC-BY-SA Creative Commons image source in video
Views: 1712 Audiopedia
https://www.albertoolla.it/cose-machine-learning-reti-neurali/ Cos'è il Machine Learning? In questo tutorial in italiano ti spiego i 3 metodi di apprendimento per far imparare un computer, come funzionano le Reti Neurali e da quali strumenti e risorse (gratuite e non) puoi iniziare per scrivere programmi di ML. ►Iscriviti per più video https://goo.gl/ZAr8yW Vuoi ricevere la mia NEWSLETTER? ►https://www.albertoolla.it/ Seguimi sulla Mia Pagina Facebook ► https://www.facebook.com/albertoolla.it Decidi l'argomento del prossimo SPIEGONE DEL MESE, vieni nel gruppo chiuso e partecipa al sondaggio! ► https://www.facebook.com/groups/albertoolla/
Views: 6752 Alberto Olla
Get a look into the mind of Neil Patel as he breaks down his personal content marketing process. ►Subscribe: https://goo.gl/ScRTwc to learn more secret SEO tips. Find me on Facebook: https://www.facebook.com/neilkpatel/ Read more on my blog: https://neilpatel.com/blog We're here to kick off the Advanced Content Marketing Summit. In this session, Neil will show the audience everything he does on his own sites, analytics, driving traffic, a bunch more. So, let's get that screen sharing up. Give us just a few seconds. Let's first get started in my analytics. I think it's already loaded. So, audience overview. You guys can see my traffic stats. There's not really much to hide. So last seven days, I was at 214,000 unique visitors. That's not too shabby, considering I don't do paid advertising. There was like, two jumps. So this is August. Let's look at August of last year, 2016. Keep in mind, I was also doing paid ads then. I was at 454. Now I'm at 200-something thousand in seven days, right? You guys see the difference? Like, you know, this is August 2016. This is, I don't know, we can do a whole month like July. So, 454. I look at users, 'cause users is unique. So 454 to 695. So my traffic is still growing, and here's one strategy that I did. It's hard to see when I look at these months, but if you look at last year, so we can pick any day. Like, we can pick October 2016, and let's go into some of my blog posts. The site content, all pages. So you see this? 13 secrets that'll boost your Facebook organic reach. This post has 13,404 visits. So we would take these keywords. I would sort 'em by impressions and click the rate. So, I can see which keywords have the highest impression count. Like, Facebook marketing strategy gets a ton of impressions for being on the eighth page. 80 position, 80.8, is usually eighth or ninth page, right, however you wanna look at it. So when I would look at all of this, I would sort by impressions, and then I would take all of these keywords, and I would integrate 'em within my blog post. So, let's go to my post. And this post is now changed. It's not 13. Facebook organic reach, search post. My editor is in there; Grant is currently editing. Okay, you see it's now called 20 Secrets That'll Boost Your Facebook Organic Reach, versus the old one of 13 secrets. In other words, what I did is I took this post and I made it super detailed, and I added in all the keywords. It works really well each and every single time. So, the page is loading, and I'll show you other examples that I did this way. Right, like, as you can see, and then I create a table with the list, where you can just click, and you can go down to the section, right, and I'm integrating the keywords within the content. The page is super long. If you look at how many keywords now, this post has 9,858 keywords, or technically words. Some of 'em are a keyword rank, some of 'em aren't, and that's how I rank better, is by modifying the articles and adding in all the keywords that do well, or that I'm at least getting impressions for. Then that way, I know what Google's already ranking me for. If I discuss those topics within my content, I'm much more likely to get ranking. And I do this for a lot of my content pieces. I go through Google Search Console. Every single week, we go and we figure out, all right, what are the most popular posts that we're ranking for, and we just continually rewrite those articles. That's what is helping increase our traffic and our rankings more than anything else. So, if I go month over month, keep in mind, August isn't over yet. So I go to like, April. I know we weren't doing it all the way back in April, and I go to today. August, of course, is gonna be lower than July, because August isn't over yet, but as you can see, it's pretty much growing, right? April, 15, then 12. June is when we rewrote the article, some time in June. July was our first full month, and like, look, it's just going up. July, already, July first through 31st, 22,000 visits. July first to August 23rd, 21,000 visits. That shows, so 21,498. 21,498 divided by, let's say 23rd, Clayton? That puts us on track or 28,000 visitors this month. That's not too shabby, right, all because we rewrite the post and just put in more keywords.
Views: 22954 Neil Patel
Power BI nos brinda la opción de conectaros a terceros, entre ellos Facebok. De tal manera podemos tener acceso a estadisticas de uso y sacar provecho a maximo de ambas herramientas. Saca tus propias Facebook Analytics. Power BI Facebook Insights. Conectar Facebook con Power BI. Facebook Power BI. Estadísticas Facebook con Power BI. =====Suscribete===== ►Contenido todas las semanas http://www.youtube.com/subscription_center?add_user=bilatam =====Contenido Relacionado===== ►Opinión: https://www.youtube.com/watch?v=mYrlUIT0c5U&list=PLRiwUUBPYwFjfGM4Cfm9Vc_LoQms1yBiq ►Comparación Business Intelligence Tools: https://www.youtube.com/watch?v=mYrlUIT0c5U ►Arquitectura Business Intelligence / Data Warehouse: https://www.youtube.com/watch?v=4fJojpYHNKg ►Data Warehouse - Desnormalización: https://www.youtube.com/watch?v=iEAIAmmJc_0 =====Comunidad en Linea===== ■Facebook: https://www.fb.com/BusinessIntelligenceLATAM/
Views: 6698 Business Intelligence LATAM