Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together videos about Helen, her brother, Luke and the choconutties. There is a sequel to give more practice choosing and illustrations of the different types of test with hypotheses.
Views: 715353 Dr Nic's Maths and Stats
This clip explains how to produce some basic descrptive statistics in R(Studio). Details on http://eclr.humanities.manchester.ac.uk/index.php/R_Analysis. You may also be interested in how to use tidyverse functionality for basic data analysis: https://youtu.be/xngavnPBDO4
Views: 123828 Ralf Becker
This tutorial provides an overview of statistical analyses in the social sciences. It distinguishes between descriptive and inferential statistics, discusses factors for choosing an analysis procedure, and identifies the difference between parametric and nonparametric procedures.
Views: 222996 The Doctoral Journey
The kind of graph and analysis we can do with specific data is related to the type of data it is. In this video we explain the different levels of data, with examples. Subtitles in English and Spanish.
Views: 820717 Dr Nic's Maths and Stats
This statistical analysis overview explains descriptive and inferential statistics. Watch more at http://www.lynda.com/Excel-2007-tutorials/business-statistics/71213-2.html?utm_medium=viral&utm_source=youtube&utm_campaign=videoupload-71213-0101 This specific tutorial is just a single movie from chapter one of the Excel 2007: Business Statistics course presented by lynda.com author Curt Frye. The complete Excel 2007: Business Statistics course has a total duration of 4 hours and 19 minutes and covers formulas and functions for calculating averages and standard deviations, charts and graphs for summarizing data, and the Analysis ToolPak add-in for even greater insights into data Excel 2007: Business Statistics table of contents: Introduction 1. Introducing Statistics 2. Learning Useful Excel Techniques 3. Summarizing Data Using Tables and Graphics 4. Describing Data Using Numerical Methods 5. Using Probability Distributions 6. Sampling Values from a Population 7. Testing Hypotheses 8. Using Linear and Multiple Regression Conclusion
Views: 106752 LinkedIn Learning
Watch Sample Class recording: http://www.edureka.co/statistics-essentials-for-analytics?utm_source=youtube&utm_medium=referral&utm_campaign=statistics-tut-1 Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data.In applying statistics to, e.g., a scientific, industrial, or societal problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Populations can be diverse topics such as "all persons living in a country" or "every atom composing a crystal". Statistics deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments. The video covers following topics: 1.Exploratory Analysis 2.Few termenologie son Statstics 3.Variance 4.Standard Deviation 5.Inquartile Range Edureka is a New Age e-learning platform that provides Instructor-Led Live, Online classes for learners who would prefer a hassle free and self paced learning environment, accessible from any part of the world. The topics related to Statistics & Probability have extensively been covered in our course 'Statistics Essentials for Analytics’. For more information, please write back to us at [email protected] Call us at US: 1800 275 9730 (toll free) or India: +91-8880862004
Views: 80912 edureka!
Please watch: "logistic regression case study" https://www.youtube.com/watch?v=M9Reulcqb2g --~-- Learn Basic statistics for Business Analytics Business Analytics and Data Science is almost same concept. For both we need to learn Statistics. In this video I tried to create value on most used statistical methods for Data Science or Business Analytics for Statistical model Building. Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data. In applying statistics any can handle a scientific, industrial, or societal problem. I value your time and effort that is why I have capture almost 20 statically concept in this video. Learn Basic statistics for Business Analytics Here I have capture how to learn Mean, how to learn Mode, How to learn median, Concept of Sleekness, Concept of Kurtosis, learn Variables, concept of Standard deviation, Concept of Covariance, Concept of correlation, Concept of regression, How to read regression formula, how to read regression graph, Concept of Intercept, Concept of slope coefficient, Concept of Random Error, Different types of regression Analysis, Concept ANOVA (Analysis of Variance), How to read ANOVA table, How to learn R square (Interpreted R square), Concept of Adjusted R Square, Concept of F test, Concept of Information Value, Concept of WOE, Concept of Variable inflation Factors. Learn Basic statistics for Business Analytics By this video you can Start Learn statistics for Data Science and Business analytics easily and effectively. These statistics are useful when at the time of running linear regression, Logistic regression statistics models. For Statistical Data Exploration you may need to see Meager of central tendency and Data Spread in Statistics. By Understanding Mean, Mode, Median, Sleekness, Kurtosis, Variance, Standard deviation. Learn Basic statistics for Business Analytics To understand statistical relationship between variables you can use Covariance, Correlation coefficient, Regression , ANOVA (Analysis of Variance) . Learn Basic statistics for Business Analytics To understand Strength of stastical relationship between variables you can use R square, Adjusted R square, F test. If you want to understand variable importance in your stastical model you can use Information value (IV) and Weight of evidence (WOE) Concept. Information value and Weight of evidence mostly used in Logistic Regression Analysis. Learn Basic statistics for Business Analytics Variable inflation factors (VIF) is used for understanding, It is the stastical method to understand variable importance. What is the importance of this variable statically in the Regression model? By VIF we check Correlation between variable. Learn Basic statistics for Business Analytics At last I have explained when to use ANOVA, When to Use Linear regression and when to use Logistic regression. Learn Basic statistics for Business Analytics Thank you So much for watching this video, Hope I can add some value in your Journey as a Statistician, Business Analytics professional and Data Scientist professional. Blogger : http://koustav.analyticsanalysis.busi... google plus: https://plus.google.com/u/0/115750715 facebook link: https://www.facebook.com/koustav.biswas.31945?ref=bookmarks website: https://www.analyticsanalysisbusiness.com
Views: 59974 Analytics Analysis Business
Here are a few of the many ways to look at data. Which is your favorite? Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/dot-plot/e/intro-to-simple-data?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/dot-plot/v/frequency-tables-and-dot-plots?utm_source=YT&utm_medium=Desc&utm_campaign=6thgrade Missed the previous lesson? https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-geometry-topic/cc-6th-polygons-in-the-coordinate-plane/v/constructing-polygon-on-coordinate-plane-example?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 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 Khan AcademyÂÃÂªs 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: 417230 Khan Academy
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 AcademyÂÃÂªs 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: 1871821 Khan Academy
Statistical Analysis of Data Video Lecture of Principles of Measurement Chapter in Subject Electronic Instrumentation and Measurement for Electrical, Electronics, EXTC & Instrumentation Engineering Students. Watch Previous Videos of Chapter Principles of Measurements:- 1) Sources of Errors in Measurement - Electronic Instrumentation and Measurement - https://www.youtube.com/watch?v=mXlYEplJfM4 2) Methods of Minimizing Errors - Principles of Measurement - Electronic Instrumentation & Measurement - https://www.youtube.com/watch?v=WCI6sBNi_ow Watch Next Videos of Chapter Principles of Measurements:- 1) Types of Errors in Measurement System - Problem 1 - Principles of Measurement - Electronic Instrumentation and Measurement - https://www.youtube.com/watch?v=irlFIPfC9qs 2) Types of Errors in Measurement System - Problem 2 - Principles of Measurement - Electronic Instrumentation and Measurement - https://www.youtube.com/watch?v=aq7QFhFoaBY Access the Complete Playlist of Subject Electronic Instrumentation and Measurement:- http://gg.gg/Electronic-Instrumentation-and-Measurement Access the Complete Playlist of Chapter Principles of Measurements:- http://gg.gg/Principles-of-Measurement Subscribe to Ekeeda Channel to access more videos:- http://gg.gg/Subscribe-Now #ElectronicInstrumentationandMeasurement #ElectronicInstrumentation #ElectronicMeasurement #ElectronicInstrumentsandMeasurement #ElectronicMeasurementVideoTutorials #ElectronicMeasurementTutorials #ElectronicInstrumentationVideoLectures #ElectronicInstrumentationOnlineLectures #ElectronicInstrumentationandMeasurementlectures Thanks For Watching. You can follow and Like us in following social media. Website - http://ekeeda.com Parent Channel - https://www.youtube.com/c/ekeeda Facebook - https://www.facebook.com/ekeeda Twitter - https://twitter.com/Ekeeda_Video LinkedIn- https://www.linkedin.com/company-beta/13222723/ Instgram - https://www.instagram.com/ekeeda_/ Pinterest - https://in.pinterest.com/ekeedavideo You can reach us at [email protected] Happy Learning : )
Views: 851 Ekeeda
Copyright Broad Institute, 2013. All rights reserved. The presentation above was filmed during the 2012 Proteomics Workshop, part of the BroadE Workshop series. The Proteomics Workshop provides a working knowledge of what proteomics is and how it can accelerate biologists' and clinicians' research. The focus of the workshop is on the most important technologies and experimental approaches used in modern mass spectrometry (MS)-based proteomics.
Views: 6989 Broad Institute
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: 908731 David Langer
Download files: http://people.highline.edu/mgirvin/excelisfun.htm Topics in this video: 1. (00:43) Categorical Data vs. Quantitative Data 2. (02:00) Scales of Measurement (Levels of Measurement): Nominal, Ordinal, Interval, Ratio 3. (14:42) Cross Sectional Data vs. Time Series Data 4. (15:48) Graphical Display of types of Data 5. (16:22) How to Enter Data into the spreadsheet and use the Auto Complete (Auto Text) to your benefit 6. (18:50) How to create a new Excel Workbook to do your Homework from the Textbook
Views: 33665 ExcelIsFun
In common health care research, some hypothesis tests are more common than others. How do you decide, between the common tests, which one is the right one for your research? Thank you to the Statistical Learning Center for their excellent video on the same topic. https://www.youtube.com/rulIUAN0U3w
Views: 348633 Erich Goldstein
There is a growing interest from the Oil and Gas industry in the application of statistical analysis methods in the integrity management of assets. A major area of application is statistical analysis in the planning and evaluation of inspections carried on out equipment where there is potential for in-service degradation. This area is of growing relevance as operators seek to more effectively manage the risks associated with in-service degradation and developments in inspection technology make available more quantitative information. Statistical analysis allows an improved understanding of asset condition, taking into consideration the capability and limitations of the inspection methods, and this leads to improved decision making. There are substantial benefits to operators with respect to risk management and business performance. A major area of application of statistical analysis is in the planning and evaluation of sampling inspections where coverage is less than 100%. The aim of sampling inspections is to obtain sufficient information to allow reliable estimates for the regions not inspected. Statistical analysis underpins sampling approaches, in providing the basis for estimates for the uninspected area and also in assessing the reliability of the estimates. Statistical analysis in support of sampling inspection is now widely applied in practice - it is for example a fundamental requirement of NII of pressure vessels where a Type B strategy per the HOIS Recommended Practice for NII (DNV-RP-G103) applies. This free webinar will give attendees an overview of statistical analysis as applied to planning and evaluations of inspections in support of integrity management of process equipment. The webinar covers the following topics. -Introduction to application of statistical methods in integrity management -Statistical characteristics of in-service corrosion Basic theory covering extreme value analysis (EVA) and use of wall thickness distributions -Planning for effective sample inspections -Key inspection parameters, including coverage, accuracy and probability of detection -Use of statistical analysis for Type B NII cases -Example applications and case studies Your presenter: Mark Stone Bsc Eng (Mech), PhD Mark is responsible for Sonomatic?s integrity support area and leads a team delivering integrity-related services to clients. He is a Mechanical Engineer with over 25 years experience of working closely with NDT inspection colleagues to ensure better integration of inspection as part of more effective integrity management approaches. His experience covers planning for reliable inspection approaches and assessment of inspection results from an integrity perspective. A major part of his role covers development of methods to ensure best use is made of inspection data as input to integrity management decision making. This addresses a wide range of applications where statistical analysis is used for planning and evaluation of limited coverage inspections. Examples include development of strategies for non-intrusive inspection of pressure vessels, storage tanks, processing piping and unpiggable pipelines. He is primary author of the HOIS Recommended Practices for Non-intrusive inspection (NII) and Statistical Analysis of Inspection Data. http://www.sonomatic.com/index.php?page=webinars&objectid=674
Views: 509 Sonomatic
Python data analysis / data science tutorial. Let’s go! For more videos like this, I’d recommend my course here: https://www.csdojo.io/moredata Sample data and sample code: https://www.csdojo.io/data My explanation about Jupyter Notebook and Anaconda: https://bit.ly/2JAtjF8 Also, keep in touch on Twitter: https://twitter.com/ykdojo And Facebook: https://www.facebook.com/entercsdojo Outline - check the comment section for a clickable version: 0:37: Why data visualization? 1:05: Why Python? 1:39: Why Matplotlib? 2:23: Installing Jupyter through Anaconda 3:20: Launching Jupyter 3:41: DEMO begins: create a folder and download data 4:27: Create a new Jupyter Notebook file 5:09: Importing libraries 6:04: Simple examples of how to use Matplotlib / Pyplot 7:21: Plotting multiple lines 8:46: Importing data from a CSV file 10:46: Plotting data you’ve imported 13:19: Using a third argument in the plot() function 13:42: A real analysis with a real data set - loading data 14:49: Isolating the data for the U.S. and China 16:29: Plotting US and China’s population growth 18:22: Comparing relative growths instead of the absolute amount 21:21: About how to get more videos like this - it’s at https://www.csdojo.io/moredata
Views: 175716 CS Dojo
Download files: http://people.highline.edu/mgirvin/excelisfun.htm Topics in this video: 1. (00:21) What Is / Are Statistics? Define Statistics 2. (02:42) Descriptive Statistics and Inferential Statistics 3. (05:00) Collect, analyze and present raw data on Yahoo Stock Price: Search the internet, download, create formulas and crate a Chart and present the information in a useful way. 4. (06:05) Get Data from http://finance.yahoo.com/ 5. (06:43) Copy and paste data from internet into an Excel spreadsheet. Learn about Paste Special, Text 6. (07:28) Download a “.csv” file. “.csv” and “.txt” file types (file extensions) are text files. When you open them, they look like Excel, but it is not. We can copy and paste into a real Excel file. Text files are common files types that allow raw data to be transferred from one system to another. Text files are intermediate steps between the original Database and your Excel Spreadhseet. 7. (07:46) Control Panel, Folder Options, View Tab, Uncheck “Hide extensions for known file types” 8. (08:47) Highlight whole table keyboard is Ctrl + * 9. (09:50) Calculate maximum stock price with MAX function, minimum stock price with MIN and Mean using the AVERAGE function. 10. (11:30) Keyboard shortcuts for highlighting ranges that are not next to each other (noncontiguous ranges): Ctrl + Mouse Click 11. (12:15) Create Line Chart from Historical Data 12. (13:58) Page Setup 13. (17:52) Example of Inferential Statistics
Views: 37829 ExcelIsFun
Statistical Analysis of Data by Dr.Shahid,PhD - Research and Thesis Subscribe this channel and follow all the video in the playlist.If you are currently doing any research or writing a thesis please follow step by step guidelines provided in these videos hope you will get a good supervision of your quality research. quantitative research, quantitative research methods, quantitative research designs, quantitative research in urdu, quantitative research in nursing, quantitative research presentation, quantitative research example, quantitative research designs descriptive non-experimental, quantitative research vs qualitative, quantitative research questions, fundamental research, fundamental reggae jimmy cliff, fundamental review of the trading book, fundamental reggae, fundamental research in hindi, fundamental results, reading fundamental, fundamental and realized niche, fundamental rights (review i), fundamental 5 recognize and reinforce, how to write a good research paper, how to write a good resume, how to write a good research proposal, how to write a good resignation letter, how to write a good research question, how to write a good resume with no job experience, how to write a good resume and cover letter, how to write a good research essay, how to write a good resume 2016, how to write a good research, how to write a good proposal, how to write a good problem statement, how to write a good project, how to write a good profile, how to write a good protagonist, how to write a good program, how to write a good product review, how to write a good research proposal, how to write a good dating profile, how to write a good business proposal, how to write research paper, how to write research proposal, how to write research paper in urdu, how to write research article, how to write research methodology, how to write research paper in computer science, I how to write research thesis, a how to write research report, how to write research paper in latex, how to write research objectives,
Views: 346 Research and Thesis
R programming for beginners - This video is an introduction to R programming in which I provide a tutorial on some statistical analysis (specifically using the t-test and linear regression). I also demonstrate how to use dplyr and ggplot to do data manipulation and data visualisation. Its R programming for beginners really and is filled with graphics, quantitative analysis and some explanations as to how statistics work. If you’re a statistician, into data science or perhaps someone learning bio-stats and thinking about learning to use R for quantitative analysis, then you’ll find this video useful. Importantly, R is free. If you learn R programming you’ll have it for life. This video was sponsored by the University of Edinburgh. Find out more about their programmes at http://edin.ac/2pTfis2 This channel focusses on global health and public health - so please consider subscribing if you’re someone wanting to make the world a better place – I’d love to you join this community. I have videos on epidemiology, study design, ethics and many more.
Views: 302574 Global Health with Greg Martin
Note: The file discussed in this video is available at http://professoreaston.com/ForYouTubeVideos/ChiSquaredExample.xlsx In this video I discuss two two statistical hypothesis tests that are commonly used for attribute data in Six Sigma. The two tests are the two sample test of proportions and the Pearson Chi-Square test. If you want to skip the two-sample test for proportions are go directly to the discussion of the Pearson Chi-Square test, that discussion begins at time 14:40.
Views: 3003 ProfessorEaston
Hypothesis Testing and P-values Practice this yourself on Khan Academy right now: https://www.khanacademy.org/e/hypothesis-testing-with-simulations?utm_source=YTdescription&utm_medium=YTdescription&utm_campaign=YTdescription Watch the next lesson: https://www.khanacademy.org/math/probability/statistics-inferential/hypothesis-testing/v/one-tailed-and-two-tailed-tests?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/statistics-inferential/margin-of-error/v/margin-of-error-2?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: 2086381 Khan Academy
This is just a few minutes of a complete course. Get full lessons & more subjects at: http://www.MathTutorDVD.com. In this lesson we will cover the difference between descriptive and inferential statistics.
Views: 83250 mathtutordvd
Presenter: Christopher Fonnesbeck Description This tutorial will introduce the use of Python for statistical data analysis, using data stored as Pandas DataFrame objects. Much of the work involved in analyzing data resides in importing, cleaning and transforming data in preparation for analysis. Therefore, the first half of the course is comprised of a 2-part overview of basic and intermediate Pandas usage that will show how to effectively manipulate datasets in memory. This includes tasks like indexing, alignment, join/merge methods, date/time types, and handling of missing data. Next, we will cover plotting and visualization using Pandas and Matplotlib, focusing on creating effective visual representations of your data, while avoiding common pitfalls. Finally, participants will be introduced to methods for statistical data modeling using some of the advanced functions in Numpy, Scipy and Pandas. This will include fitting your data to probability distributions, estimating relationships among variables using linear and non-linear models, and a brief introduction to Bayesian methods. Each section of the tutorial will involve hands-on manipulation and analysis of sample datasets, to be provided to attendees in advance. The target audience for the tutorial includes all new Python users, though we recommend that users also attend the NumPy and IPython session in the introductory track. Tutorial GitHub repo: https://github.com/fonnesbeck/statistical-analysis-python-tutorial Outline Introduction to Pandas (45 min) Importing data Series and DataFrame objects Indexing, data selection and subsetting Hierarchical indexing Reading and writing files Date/time types String conversion Missing data Data summarization Data Wrangling with Pandas (45 min) Indexing, selection and subsetting Reshaping DataFrame objects Pivoting Alignment Data aggregation and GroupBy operations Merging and joining DataFrame objects Plotting and Visualization (45 min) Time series plots Grouped plots Scatterplots Histograms Visualization pro tips Statistical Data Modeling (45 min) Fitting data to probability distributions Linear models Spline models Time series analysis Bayesian models Required Packages Python 2.7 or higher (including Python 3) pandas 0.11.1 or higher, and its dependencies NumPy 1.6.1 or higher matplotlib 1.0.0 or higher pytz IPython 0.12 or higher pyzmq tornado
Views: 72063 Enthought
Excel file: https://dl.dropboxusercontent.com/u/561402/TTEST.xls In this video Paul Andersen explains how to run the student's t-test on a set of data. He starts by explaining conceptually how a t-value can be used to determine the statistical difference between two samples. He then shows you how to use a t-test to test the null hypothesis. He finally gives you a separate data set that can be used to practice running the test. Do you speak another language? Help me translate my videos: http://www.bozemanscience.com/translations/ Music Attribution Intro Title: I4dsong_loop_main.wav Artist: CosmicD Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/ Creative Commons Atribution License Outro Title: String Theory Artist: Herman Jolly http://sunsetvalley.bandcamp.com/track/string-theory All of the images are licensed under creative commons and public domain licensing: 184.108.40.206.2. Critical Values of the Student’s-t Distribution. (n.d.). Retrieved April 12, 2016, from http://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm File:Hordeum-barley.jpg - Wikimedia Commons. (n.d.). Retrieved April 11, 2016, from https://commons.wikimedia.org/wiki/File:Hordeum-barley.jpg Keinänen, S. (2005). English: Guinness for strenght. Retrieved from https://commons.wikimedia.org/wiki/File:Guinness.jpg Kirton, L. (2007). English: Footpath through barley field. A well defined and well used footpath through the fields at Nuthall. Retrieved from https://commons.wikimedia.org/wiki/File:Footpath_through_barley_field_-_geograph.org.uk_-_451384.jpg pl.wikipedia, U. W. on. ([object HTMLTableCellElement]). English: William Sealy Gosset, known as “Student”, British statistician. Picture taken in 1908. Retrieved from https://commons.wikimedia.org/wiki/File:William_Sealy_Gosset.jpg The T-Test. (n.d.). Retrieved April 12, 2016, from http://www.socialresearchmethods.net/kb/stat_t.php
Views: 444182 Bozeman Science
Updated video 2018: SPSS for Beginners - Introduction https://youtu.be/_zFBUfZEBWQ This video provides an introduction to SPSS/PASW. It shows how to navigate between Data View and Variable View, and shows how to modify properties of variables.
Views: 1424922 Research By Design
a short tutorial to introduce students to some terms involved in experimental uncertainty
Views: 264 Nicole Carro
Basic introduction to correlation - how to interpret correlation coefficient, and how to chose the right type of correlation measure for your situation. 0:00 Introduction to bivariate correlation 2:20 Why does SPSS provide more than one measure for correlation? 3:26 Example 1: Pearson correlation 7:54 Example 2: Spearman (rhp), Kendall's tau-b 15:26 Example 3: correlation matrix I could make this video real quick and just show you Pearson's correlation coefficient, which is commonly taught in a introductory stats course. However, the Pearson's correlation IS NOT always applicable as it depends on whether your data satisfies certain conditions. So to do correlation analysis, it's better I bring together all the types of measures of correlation given in SPSS in one presentation. Watch correlation and regression: https://youtu.be/tDxeR6JT6nM ------------------------- Correlation of 2 rodinal variables, non monotonic This question has been asked a few times, so I will make a video on it. But to answer your question, monotonic means in one direction. I suggest you plot the 2 variables and you'll see whether or not there is a monotonic relationship there. If there is a little non-monotonic relationship then Spearman is still fine. Remember we are measuring the TENDENCY for the 2 variables to move up-up/down-down/up-down together. If you have strong non-monotonic shape in the plot ie. a curve then you could abandon correlation and do a chi-square test of association - this is the "correlation" for qualitative variables. And since your 2 variables are ordinal, they are qualitative. Good luck
Views: 503654 Phil Chan
Statistics and Data Series presentation by Dr. Catherine Corrigall-Brown, Jan 23, 2013 at Western University: "A Practical Introduction to Content Analysis." The presentation outlined what content analysis is, discussing how contents are coded, and illustrated types of analyses that can be done with the technique. Dr. Corrigall-Brown also presented a few examples of studies done with content analysis. Slides for this presentation are online at the RDC website. The Statistics and Data Series is a partnership between the Centre for Population, Aging and Health and the Research Data Centre. This interdisciplinary series promotes the enhancement of skills in statistical techniques and use of quantitative data for empirical and interdisciplinary research. More information at http://rdc.uwo.ca
Views: 52426 Western University
#AdvancedStatisticalTechniques | Learn more about our analytics programs: http://bit.ly/2EjCWZh This tutorial helps you understand the following advanced statistical techniques and its applications. - Analysis of Variance (ANOVA) - Linear Regression Analysis - Principal Component Analysis (PCA) - Factor Analysis #AdvancedStatiscs #Tutorial #GreatLearning #ANOVA #PCS #FactorAnalysis ----------------------------------------- Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Big Data and Analytics. PG Program in Business Analytics (PGP-BABI): 12-month program with classroom training on weekends + online learning covering analytics tools and techniques and their application in business. PG Program in Big Data Analytics (PGP-BDA): 12-month program with classroom training on weekends + online learning covering big data analytics tools and techniques, machine learning with hands-on exposure to big data tools such as Hadoop, Python, Spark, Pig etc. PGP-Data Science & Engineering: 6-month weekend and classroom program allowing participants enables participants in learning conceptual building of techniques and foundations required for analytics roles. PG Program in Cloud Computing: 6-month online program in Cloud Computing & Architecture for technology professionals who want their careers to be cloud-ready. Business Analytics Certificate Program (BACP): 6-month online data analytics certification enabling participants to gain in-depth and hands-on knowledge of analytical concepts. Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U Do you know what the three pillars of Data Science? Here explaining all about thepillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: Google Plus: https://plus.google.com/u/0/108438615307549697541 Facebook: https://www.facebook.com/GreatLearningOfficial/ LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube
Views: 13023 Great Learning
(April 2, 2014) Metodi Nikolov, Senior Quantitative Analyst at FinAnalytica, talks about the probability models that a given financial data series follows. The speaker gives information about the kinds of outcomes and answers that can be gotten from the data and how statistics and analysis are performed on it. This lecture was organized for Professor Dimitar Christozov's Data Mining class. More about this talk on our website: http://www.aubg.edu/talks/finanalytica-statistical-analysis-of-financial-data Find us elsewhere on the web: WEBSITE: http://www.aubg.edu/talks FACEBOOK: http://www.facebook.com/AUBGTalks TWITTER: http://twitter.com/AUBGTalks GOOGLE+: http://plus.google.com/113278525844733479649/ Find out more about our awesome university, the American University in Bulgaria: http://www.aubg.edu
Views: 2553 AUBGTalks
Science and Engineering Practice 3: Analyzing and Interpreting Data Paul Andersen explains how scientists analyze and interpret data. Data can be organized in a table and displayed using a graph. Students should learn how to present and evaluate data. Intro Music Atribution Title: I4dsong_loop_main.wav Artist: CosmicD Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/ Creative Commons Atribution License
Views: 60751 Bozeman Science
Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 688050 statisticsfun
In this video you will learn the different types of sampling techniques that you can use while building predictive models or data science models. You can use Probability Samples – Each member of the population has a non zero probability of getting selected in the sample Examples : Random Sampling, Systematic Sampling & Stratified sampling Non Probability Samples- Members are selected from the population in non random way Convenience sampling, Judgement sampling, Quota Sampling, & Snowball Sampling ANalytics Study Pack : https://analyticuniversity.com Analytics University on Twitter : https://twitter.com/AnalyticsUniver Analytics University on Facebook : https://www.facebook.com/AnalyticsUniversity Logistic Regression in R: https://goo.gl/S7DkRy Logistic Regression in SAS: https://goo.gl/S7DkRy Logistic Regression Theory: https://goo.gl/PbGv1h Time Series Theory : https://goo.gl/54vaDk Time ARIMA Model in R : https://goo.gl/UcPNWx Survival Model : https://goo.gl/nz5kgu Data Science Career : https://goo.gl/Ca9z6r Machine Learning : https://goo.gl/giqqmx Data Science Case Study : https://goo.gl/KzY5Iu Big Data & Hadoop & Spark: https://goo.gl/ZTmHOA
Views: 4158 Analytics University
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: 161717 APMonitor.com
Download files: http://people.highline.edu/mgirvin/excelisfun.htm Install Data Analysis Add-in For Amazing Excel Statistical Tools in Excel 2013.
Views: 36704 ExcelIsFun
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: 421793 Anywhere Math
This is a short practical guide to Qualitative Data Analysis
Views: 107948 James Woodall
What makes a question a "statistical question"? Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/cc-6-statistical-questions/e/statistical-questions?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/histograms/v/histograms-intro?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/dot-plot/v/frequency-tables-and-dot-plots?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 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 Khan AcademyÂÃÂªs 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: 431497 Khan Academy
Try my new interactive online course "Fundamentals of Bayesian Data Analysis in R" over at DataCamp: https://www.datacamp.com/courses/fundamentals-of-bayesian-data-analysis-in-r ---- This is part one of a three part introduction to Bayesian data analysis. This first part aims to explain *what* Bayesian data analysis is. See here for part 2: https://youtu.be/mAUwjSo5TJE Here are links to the exercises mentioned in the video: R - https://goo.gl/cxfnYK (if this link does not work for you try http://rpubs.com/rasmusab/257829) Python - https://goo.gl/ceShN5 More Bayesian stuff can be found on my blog: http://sumsar.net. :)
Views: 76114 rasmusab
Get the full course at: http://www.MathTutorDVD.com The student will learn the big picture of what a hypothesis test is in statistics. We will discuss terms such as the null hypothesis, the alternate hypothesis, statistical significance of a hypothesis test, and more. In this step-by-step statistics tutorial, the student will learn how to perform hypothesis testing in statistics by working examples and solved problems.
Views: 1222973 mathtutordvd