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The Shape of Data: Distributions: Crash Course Statistics #7
 
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When collecting data to make observations about the world it usually just isn't possible to collect ALL THE DATA. So instead of asking every single person about student loan debt for instance we take a sample of the population, and then use the shape of our samples to make inferences about the true underlying distribution our data. It turns out we can learn a lot about how something occurs, even if we don't know the underlying process that causes it. Today, we’ll also introduce the normal (or bell) curve and talk about how we can learn some really useful things from a sample's shape - like if an exam was particularly difficult, how often old faithful erupts, or if there are two types of runners that participate in marathons! 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, Justin Zingsheim, 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, 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/YouTubeCrashCourse 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: 164242 CrashCourse
Describing Distributions in Statistics
 
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The four key points are discussed when describing distributions in statistics...Shape, Center, Spread, and Outliers. Please forgive the misspelling of DESCRIBED in the video. TIP to identify Left & Right Skewness: (Thanks LeBadman:) Left: Mean is less than Median is less than Mode Symmetrical: Mean, Median and Mode are approximately equal Right: Mean is greater than Median is greater than Mode You just take: Mean, Median, Mode If it's left skewed, you will see the inequalities pointing to the left. If it's right skewed, you will see the inequalities pointing to the right. Check out http://www.ProfRobBob.com, there you will find my lessons organized by class/subject and then by topics within each class. Find free review test, useful notes and more at http://www.mathplane.com
Views: 98883 ProfRobBob
Examining Distributions
 
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Unit 1, Part 1 Quantitative Data & Categorical Data Descritptive Statistical Methods
Views: 3369 Robert Emrich
Examining a Distribution
 
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Views: 278 Liz Minton
Describing the Shape, Center, and Spread of a Distribution
 
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This statistics lesson shows you how to describe the shape, center, and spread of the distribution by just examining the graph of the data given by a histogram or a dotplot. By inspecting the graph of a distribution, you could identify important statistic and behavior of your data by how the density curve forms it shape.
Views: 3973 Numberbender
Cleaning Data in R Course - Examining Distributions
 
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This session deals with Examining Distributions. When you are looking to optimize your features and variables you would want to examine the distributions of data in r. It is very easy to view and test the distribution for non-categorical data in R. For instance, you can describe the distribution with descdist or you can plot your data against a known distribution. Data Wrangling in R Course on Experfy.com -- R is an extraordinarily powerful language with a vast community of great resources, but where should you start when all you want to do is get your data into a usable format? How do you know your data might be ready? What are the pitfalls you should watch for so that you don’t perform an analysis on bad data? This course will teach you from start to finish how to get your data into R efficiently and polish it up so that it is as good as it can be. This will let you or your team focus after this step on the statistical modeling, visualization, reporting, sharing, or any other post-processing task you wish to perform. Confidence, reliability, and reproducibility in your data acquisition and preparation are the kingpins to being able to maximize your data’s value. Follow us on: https://www.facebook.com/experfy https://twitter.com/experfy https://experfy.com
Views: 392 Experfy
Central limit theorem | Inferential statistics | Probability and Statistics | Khan Academy
 
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Introduction to the central limit theorem and the sampling distribution of the mean Watch the next lesson: https://www.khanacademy.org/math/probability/statistics-inferential/sampling_distribution/v/sampling-distribution-of-the-sample-mean?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/statistics-inferential/normal_distribution/v/ck12-org-more-empirical-rule-and-z-score-practice?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: 1335616 Khan Academy
Shape, Center, and Spread
 
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How to Describe Distributions of quantitative data. How to construct a box plot from the 5 number summary.
Views: 34461 Kent Wiginton
Examining and Screening Data for Multivariate Data Analysis with Unrouped Data - Part III
 
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We discuss how to deal with Data Accuracy, Missing Values, Outliers, Normality, Linearity and Homoscedasticity while performing Multiple Regression.
Views: 145 Vikas Agrawal
Examining and Screening Data for Multivariate Data Analysis with Grouped Data - Part II
 
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We discuss how to deal with Data Accuracy, Missing Values, Outliers, Normality, Linearity and Homoscedasticity while performing MANOVA.
Views: 302 Vikas Agrawal
Key concepts in modelling the spatial distribution of fish
 
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A presentation by Benjamin Planque, Institute of marine research in Tromsö, on the PhD course: Modeling to study the Baltic Sea ecosystem - possibilities and challenges Askö Laboratory in March 2013 To BEAMs homepage: http://www.smf.su.se/beam
Views: 640 SUBalticSeaCentre
Statistics | 1.3 Examining Graphs
 
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This video will help you understand how to analyze graphs in statistics, Key Concepts: Graph, Center, Unusual Values, Spread, Shape, Uniform, Symmetric, Skewed Thank you for watching our educational video.
Views: 575 Club Academia
Examining the Future of Field and Inside Sales in Distribution
 
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Distribution as a whole is rapidly changing with the rise of digital platforms. In general, we are moving toward more efficient shopping and buying mechanisms. In the report, this efficiency manifests as a move toward digital and inside sales and away from field sales. To learn more, visit http://www.WayPointAnalytics.com
Views: 43 WayPoint Analytics
Examining the Bell Curve: A Data Science Perspective
 
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Table of Contents: 00:15 - Topics 00:32 - Quick Facts 01:08 - Why Study TBC? 01:16 - 01:35 - 01:58 - 02:11 - Comment 02:16 - 02:35 - 03:25 - Principal Theses 03:28 - 04:04 - 04:35 - 04:53 - 05:18 - 05:42 - 05:54 - 06:19 - 07:25 - My Approach 07:27 - 07:33 - 07:59 - 08:38 - STEPS
Views: 205 Alfred Essa
3.2 Examining Distributions
 
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made with ezvid, free download at http://ezvid.com
Views: 110 Alex Brazill
Exploratory Analysis of TCGA-BLCA RNA Seq data
 
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00:10 - The memory setting to handle large data sets. 00:40 - Importing samples from GDC data center. 01:30 - Creating a series, and set GDC sample annotations as parameters. 03:50 - Setting a normalization as viewing data distribution patterns. 06:20 - Filtering. 08:20 - PCA, and marking samples in a cluster. 08:50 - Visualizing parameters to help interpreting the result. 13:10 - Examining data distribution patterns of artificial effects. 18:20 - Excluding a part of samples from the analysis. 19:00 - Defining subgroups of tumor samples. 21:10 - Extracting differentially expressed genes between the subgroups. 22:00 - Creating a new series of Normal-Tumor paired samples. 24:30 - Making tumor/normal ratios to cancel individual differences. 27:00 - Examining "tumorization" effect on the expression profile. 27:30 - Defining 2 types of "tumorization" from a result of PCA. 29:10 - Extracting differentially expressed genes between the "tumorization" types. 30:00 - Comparing results for further analysis.
Views: 783 subiosupport
02 - Normal Distribution
 
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Materials Looking at Data - Distributions Slides: Looking at Data Lecture Normal Distributions Lecture Looking at Data - Relationships Slides: Looking at Data - Relationships Lecture Producing Data Slides: Producing Data Lecture Objectives Examine distributions. Summarize and describe the distribution of a categorical variable in context. Generate and interpret several different graphical displays of the distribution of a quantitative variable (histogram, stemplot, boxplot). Summarize and describe the distribution of a quantitative variable in context: a) describe the overall pattern, b) describe striking deviations from the pattern. Relate measures of center and spread to the shape of the distribution, and choose the appropriate measures in different contexts. Apply the standard deviation rule to the special case of distributions having the "normal" shape. Explore relationships between variables using graphical and numerical measures. Classify a data analysis situation (involving two variables) according to the "role-type classification," and state the appropriate display and/or numerical measures that should be used in order to summarize the data. Compare and contrast distributions (of quantitative data) from two or more groups, and produce a brief summary, interpreting your findings in context. Graphically display the relationship between two quantitative variables and describe: a) the overall pattern, and b) striking deviations from the pattern. Interpret the value of the correlation coefficient, and be aware of its limitations as a numerical measure of the association between two quantitative variables. In the special case of linear relationship, use the least squares regression line as a summary of the overall pattern, and use it to make predictions. Recognize the distinction between association and causation, and identify potential lurking variables for explaining an observed relationship. Recognize and explain the phenomenon of Simpson's Paradox as it relates to interpreting the relationship between two variables. Sampling. Examine methods of drawing samples from populations Identify the sampling method used in a study and discuss its implications and potential limitations. Designing Studies. Distinguish between multiple studies, and learn details about each study design. Identify the design of a study (controlled experiment vs. observational study) and other features of the study design (randomized, blind etc.). Explain how the study design impacts the types of conclusions that can be drawn.
Views: 1812 Lollynonymous
Mean, Median, and Mode: Examining U.S. Earthquake Data (2000-2011)
 
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I examine how to find the mean, median, and mode (all TYPES of averages) by looking at actual U.S. earthquake data this millennium. Check out more videos in the statistics series or other math, economics, and miscellany on www.radicaltutor.com.
Views: 366 Michael Pandolfini
Math Antics - Mean, Median and Mode
 
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Learn More at mathantics.com Visit http://www.mathantics.com for more Free math videos and additional subscription based content!
Views: 1202831 mathantics
Interpreting box plots | Data and statistics | 6th grade | Khan Academy
 
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Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/cc-6th-box-whisker-plots/e/interpreting-quartiles-on-box-plots?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/cc-6th/v/calculating-interquartile-range-iqr?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/cc-6th-box-whisker-plots/v/another-example-constructing-box-plot?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 Academy‰Ûªs 6th grade channel: https://www.youtube.com/channel/UCnif494Ay2S-PuYlDVrOwYQ?sub_confirmation=1 Subscribe to Khan Academy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 380566 Khan Academy
Examining A Dot Plot
 
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This video shows how to find the median, mean, IQR and the number of observations of a dot plot.
Views: 3969 mrmaisonet
AP Statistics: Exploring Data (ED) Video 1 - Data
 
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This video goes over data, variables, statistics, and the who, what, where, when, why, and how of data.
Views: 19023 Michael Porinchak
2 Non-Parametric - Examining Skewness of Data
 
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The Non-Parametric Analyses video series is available for FREE as an iTune book for download on the iPad. The ISBN number is 978-1-62407-809-5. The title is "Non-Parametric Analyses." Waller and Lumadue are the authors. The iTune text provides accompanying narrative and the SPSS readouts used in the video series. The textbook can be obtained from: https://itunes.apple.com/us/book/non-parametric-analyses/id657196105?ls=1 This video guides the viewer through the process of using SPSS to examine the skewness and kurtosis of a data set. Time is also spent examining the SPSS readout to provide insight into the interpretation of the results.
Views: 5732 Lee Rusty Waller
The Normal Distribution and the 68-95-99.7 Rule
 
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Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! The Normal Distribution and the 68-95-99.7 Rule. In this video, I talk about the normal distribution and what percentage of observed values fall within either 1, 2, or 3 standard deviations from the mean. One specific example is discussed. For more free math video, visit http://PatrickJMT.com
Views: 704808 patrickJMT
How to Analyze Satisfaction Survey Data in Excel with Countif
 
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Purchase the spreadsheet (formulas included!) that's used in this tutorial for $5: https://gum.co/satisfactionsurvey ----- Soar beyond the dusty shelf report with my free 7-day course: https://depictdatastudio.teachable.com/p/soar-beyond-the-dusty-shelf-report-in-7-days/ Most "professional" reports are too long, dense, and jargony. Transform your reports with my course. You'll never look at reports the same way again.
Views: 392374 Ann K. Emery
AP Statistics: Binomial and Geometric Models
 
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This video explains the basics of the geometric and binomial models with a few basic examples. If you are interested in practice AP questions to help prepare you for the AP test in May please utilize Barron’s AP Statistics Question Bank. Access via the web or by downloading the app in iTunes or the Google Play Store. Links are below: Web: https://www.examiam.com/ap iTunes: https://itunes.apple.com/us/app/barrons-ap-statistics/id1438469502?mt=8 Google Play Store: https://play.google.com/store/apps/details?id=com.examiam.apstatistics
Views: 15388 Michael Porinchak
How to calculate interquartile range IQR | Data and statistics | 6th grade | Khan Academy
 
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Learn how to calculate the interquartile range, which is a measure of the spread of data in a data set. Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/cc-6th/e/calculating-the-interquartile-range--iqr-?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/cc-6-mad/v/mean-absolute-deviation?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/cc-6th-box-whisker-plots/v/interpreting-box-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 Academy‰Ûªs 6th grade channel: https://www.youtube.com/channel/UCnif494Ay2S-PuYlDVrOwYQ?sub_confirmation=1 Subscribe to Khan Academy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 427417 Khan Academy
Analysing residuals (Minitab)
 
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Currell: Scientific Data Analysis. Analysis for Fig 5.14 data. See also 6.4. http://ukcatalogue.oup.com/product/9780198712541.do © Oxford University Press
Examining First Marriages In The US - National Health Statistics Report (Data From 2006-2010)
 
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Here is the most in-depth data I could find from a representative sample of Americans aged 15-44. This is data from the NSFG (National Survey of Family Growth). There is data on cohabitation trends, marriage trends, as well as a more in-depth breakdown of age trends and marriage/divorce by race. It also compares 2006-2010 with data from 1982, 1995, and 2002. Hope you guys enjoy some of the interesting correlational data presented in this report. Read it here for more data and numbers if you want: https://www.cdc.gov/nchs/data/nhsr/nhsr049.pdf BIG SHOUTOUT TO NEW Patreon Patrons: MikeTO, Walter, and Symp09 Also, shoutout to other patrons: Liam and Brian My Patreon: https://www.patreon.com/jerryliu/ Please go to my Amazon store and check out the stuff featured in this video: https://www.amazon.com/shop/influencer-bbbbd7c6 If you haven't checked out my Amazon store, here's some of my key video recording equipment Here's my Zoom H4n recorder: http://amzn.to/2BVdMg4 Here's the new webcam I use to record: http://amzn.to/2kbOZfk If you want to check out the camera I use to film: http://amzn.to/2lqGufi Here's the mic I bought that I use to record from my phone: http://amzn.to/2j9Ns8Q Here's the condenser mic I use to record from the screen: http://amzn.to/2hgDjqs Here's the wireless mic I use: http://amzn.to/2lqLKQ2 Shoutout to Patreon sponsors, whether past or present.
Views: 1935 Jerry Liu
Exploring Categorical Data
 
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This video was created by OpenIntro (openintro.org) and provides an overview of the content in Section 1.7 of OpenIntro Statistics, which is a free statistics textbook with a $10 paperback option on Amazon. In this section we will be introduced a couple of techniques for exploring and summarizing categorical variables.
Views: 19941 OpenIntroOrg
Describing the shape of a graph
 
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Shape center spread and outliers are used to describe the shape of a dot plot
Views: 10789 Andrew Farrell
Testing Distributions for Normality - SPSS (part 1)
 
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I demonstrate how to evaluate a distribution for normality using both visual and statistical methods using SPSS.
Views: 417248 how2stats
Examining and Screening Data for Univariate Data Analysis with Grouped Data - Part I
 
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We discuss how to deal with Data Accuracy, Missing Values, Outliers, Normality, Linearity and Homoscedasticity while performing ANOVA. Correction: Levene's test should be performed using "rincom4" variable and not "rincom3" variable as shown in the video. However , we still get the same results.
Views: 254 Vikas Agrawal
Distinguishing Distributions
 
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Statistics: looking at the shape, center, and spread of various distributions.
Views: 605 aconley5
Likert Scales and Coding Groups (Copying Value Labels) - Part 1
 
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Learn about Likert Scales in SPSS and how to copy labels from one variable to another in this video. Entering codes for Likert Scales into SPSS is also covered. Check out our next text, 'SPSS Cheat Sheet,' here: http://goo.gl/b8sRHa. Prime and 'Unlimited' members, get our text for free! (Only $4.99 otherwise, but will likely increase soon.) Lots more Likert & SPSS Videos here: https://www.udemy.com/survey-data/?couponCode=SurveyLikertVideosYT Likert scale SPSS video. YouTube Channel: https://www.youtube.com/user/statisticsinstructor Channel Description: For step by step help with statistics and SPSS. Both descriptive and inferential statistics covered. Subscribe today! Video Transcript: In this video we'll take a look at how to enter value labels for a variable which will be review since we've done that before. But then I also want to show you how to apply value labels that were entered for one variable to a number of different variables which can be really useful as it's a great time saver. Here in this data set notice that I have 10 people and I have the variables gender, item 1, 2, 3, 4, and 5. And they answered on what's known as a Likert scale. Now you very well may have heard of a Likert scale before and the first thing is you may have heard of it called LIKE-ERT scale which is very common to call it that but it's actually Likert, so it's pronounced LICK-ERT instead of LIKE-ERT and it was developed by Rensis Likert in the early to middle 1900s he developed the scale. And it's used so commonly, it's used in this 5-point option as you see here, 5 to 1, and we'll talk about that in just a moment. You'll also see it in a 7-point option, it's very commonly used that way. And less commonly so but you'll see it in other ways like 9-point scale and so forth. And it's used with many different kinds of descriptions like definitely true, somewhat true, and so forth; not just agree as you see here. So, in the most traditional use of this scale, which is what we see right here, we have a 5=strongly agree, a 4=agree, 3 is neither agree nor disagree - this is sometimes called neutral - 2 is disagree and then 1 is strongly disagree. On item 1 they would read the following statement: I can turn to others for support when needed. And then what they do is they read that item, they look at these 5 options, and if it's someone who has a lot of support in their network or friendships or what have you, they might answer 5, strongly agree, or 4, agree. And if it's someone who doesn't experience a lot of social support, they might answer a 1 for strongly disagree or a 2 for disagree and so on. So, the first person here in row 1, notice for item 1 they answered a 4, so they answered agree. Item 2 they answered a 5 for strongly agree and so on. If we look down item 1, did anyone answer strongly disagree - let's take a look at that. We're looking for a 1 here, and notice that participant number 9, they answered a 1 on item 1, so they answered strongly disagree, and so on. So what I want to do here is go ahead and enter the value labels for item 1 so we're going to enter these into SPSS that you see here. And then I want to show you how to apply those to the remaining items in a very quick way. First of all, notice that we have gender, if I click on my value labels button here as a review, gender is already coded, I already entered those. But what I don't have entered is item 1, item 2, 3, 4, and 5. And I'd like to go ahead and enter those to have them in the dataset, so if I go back and look at this file at a later time, I'll remember that a 5 corresponded to strongly agree and a 1 corresponded to strongly disagree, so in other words I'll know which direction this scale is scored, and what I mean by that is higher scores indicate greater social support because people strongly agreed with a given item. Whereas lower scores indicated less social support. Since we're looking at entering value labels, let's begin with item 1. So I could either double-click on item 1 or I could go to the variable view tab. Let's go ahead and double-click on item 1 right at the column heading here that's "name". So I double-click on that and notice it takes me to the variable view window. So that's a quick way to get there if you want to access the variable view window. And then we'll go to the "values" column here, click on the "None" cell and then notice the 3 dots appear. So I click on that and then here let's start with Lifetime access to SPSS videos: http://tinyurl.com/m2532td Video on adding Likert items together to create a total score: http://youtu.be/7jxpSLZCBsw Likert Scales Likert Strongly Agree to Strongly Disagree Likert in SPSS
Views: 189933 Quantitative Specialists
AP Statistics: Scatterplots, Association, Correlation - Part 1
 
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This video covers the basis of examining the relationship between two quantitative variables. If you are interested in practice AP questions to help prepare you for the AP test in May please utilize Barron’s AP Statistics Question Bank. Access via the web or by downloading the app in iTunes or the Google Play Store. Links are below: Web: https://www.examiam.com/ap iTunes: https://itunes.apple.com/us/app/barrons-ap-statistics/id1438469502?mt=8 Google Play Store: https://play.google.com/store/apps/details?id=com.examiam.apstatistics
Views: 34095 Michael Porinchak
Pretest and Posttest Analysis Using SPSS
 
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This video demonstrates a few ways to analyze pretest/posttest data using SPSS.
Views: 113263 Dr. Todd Grande
Median Polish - Exploratory Data Analysis
 
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[NOTE: Good CC/Subtitles Added] Median Polish is an Exploratory Data Analysis technique for analyzing two-way tables. This video shows a step-by-step example of working the Median Polish on a simple 3x3 two-way table: -15 4 1 6 16 30 -5 4 -12 Here is a simple R program that will create 3x3 two-way tables for you to practice with, and the median polish results generated by R: tbl = matrix(data=as.integer(runif(9) * 10), nrow=3, ncol=3) tbl medpolish(tbl)
Views: 4949 Timothy Chen Allen
Hierarchical Network Design
 
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A brief introduction to the hierarchical network design, Enterprise Architecture model with enterprise campus and enterprise edge. Also solving tending IT challenges with the Borderless Network Architecture, Collaboration Architecture and Data Center/Virtualization Architecture.,
Views: 24244 ciscoKim
Felix Chan. Modelling Body Mass Index Distribution using Maximum Entropy Density
 
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Presenter: Felix Chan, Curtin University Title:Modelling Body Mass Index Distribution using Maximum Entropy Density Abstract: : The objective of this paper is to model the conditional distribution of Body Mass Index (BMI) by examining the relations between a set of covariates and the moments of the BMI distribution. While BMI is often seen as a leading indicators of health, most studies on the distribution of BMI did not model beyond the second order moments. This makes it difficult to examine the determinants of obesity as the mean and variance do not contain sufficient information about the tail of the distribution. This paper applies the Maximum Entropy Density framework to examine the relations between a set of covariates and the higher order moments of the BMI distribution. The aim is to provide a more accurate description on the relations between a set of determinant and the shape of the BMI distribution. Theoretically, the paper derives the asymptotic properties of the maximum likelihood estimator of the proposed density, including consistency and asymptotic normality. Empirically, this paper applies the proposed framework to an Australian dataset. The results demonstrate how different covariates affect different moments of the BMI distribution.
Views: 64 AARES/ARE-UWA
Sample variance | Descriptive statistics | Probability and Statistics | Khan Academy
 
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Thinking about how we can estimate the variance of a population by looking at the data in a sample. Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/e/variance?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Watch the next lesson: https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/v/review-and-intuition-why-we-divide-by-n-1-for-the-unbiased-sample-variance?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/v/variance-of-a-population?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics 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: 328891 Khan Academy
Using Excel to illustrate a uniform probability distribution
 
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This is for Data Management courses where we study uniform PDs as one kind of many probability distributions. We are using an Excel simulation to show that dice rolls give a uniform probability distributions by examining their relative frequencies ... ( or *are* they uniform...?)
Views: 18774 Paul King
The Soft Drink Excitation: minitab 5, analysing data 3
 
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See the overview of the project and analysis (Part 1) here: http://youtu.be/KzQI_hcfBFo This goes with Part 2 here: http://youtu.be/G06UrSnxZRc which has some visualisations of how anova works, why equal variances and normal residuals matter, and problems often associated with residuals like skewness (left or right) and kurtosis (platykutic, mesokurtic, leptokurtic). This video looks at examining residuals in more detail, particularly skewness and kurtosis. If you are only doing a basic introductory course in data analysis this may be more advanced than your course requires. Please leave me a question if you don't understand something. Formulas used are: "Values of 2 standard errors of skewness (ses) or more (regardless of sign) are probably skewed to a significant degree. The ses can be estimated roughly using the following formula (after Tabachnick & Fidell, 1996): The square root of 6 over N." "Values of 2 standard errors of kurtosis (sek) or more (regardless of sign) probably differ from mesokurtic to a significant degree. The sek can be estimated roughly using the following formula (after Tabachnick & Fidell, 1996): the square root of 24 over N" at http://jalt.org/test/bro_1.htm or look up the text referenced. You don't necessarily need a formula to work out if a distribution is skewed or kurtotic - it is usually pretty self evident from a histogram.
Views: 587 st8tistics
Exploring GIS: Why spatial is special?
 
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An overview of the spatial thinking process in geographic information systems and science. The presentation includes the spatial thinking questions that a GIS can answer.
Views: 2815 GIS VideosTV
How to detect outliers in SPSS
 
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I describe and discuss the available procedure in SPSS to detect outliers. The procedure is based on an examination of a boxplot. SPSS can identify two different types of outliers, based on two different inter-quartile range rule multipliers. Neither multiplier (1.5 and 3.0) is ideal, however, with a bit of extra work, you can calculate an outlier based on the 2.2 multiplier. I demonstrate how to do so here: https://www.youtube.com/watch?v=WSflSmcNRFI
Views: 126677 how2stats
Dot Plots - Mean, Median, Mode and Range
 
07:57
In this video we will learn how to calculate the mean, median, mode and range of data from dot plots.
Views: 24539 Travis Nelson
Center, spread, and shape of distributions — Harder example | Math | New SAT | Khan Academy
 
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Watch Sal work through a harder Center, spread, and shape of distributions problem. Watch the next lesson: https://www.khanacademy.org/test-prep/new-sat/new-sat-math/new-sat-problem-solving-data-analysis/v/sat-math-q10-easier?utm_source=YT&utm_medium=Desc&utm_campaign=NewSAT Missed the previous lesson? https://www.khanacademy.org/test-prep/new-sat/new-sat-math/new-sat-problem-solving-data-analysis/v/sat-math-q9-easier?utm_source=YT&utm_medium=Desc&utm_campaign=NewSAT New SAT (starting March 2016) on Khan Academy: Practice all of the skills you’ll need for the new SAT. We also have four official practice exams from College Board. The October 2015 PSAT is in the style of the new SAT. 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 New SAT channel: https://www.youtube.com/channel/UCb6Pzsn8oIFv1N8eGem570A?sub_confirmation=1 Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 100796 Khan Academy
R Statistics tutorial: Creating bar charts for categorical variables | lynda.com
 
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This tutorial walks you through the process, step-by-step, for creating bar charts for a single categorical variable with R Statistics. Watch more at http://www.lynda.com/R-tutorials/R-Statistics-Essential-Training/142447-2.html?utm_campaign=ka3mDnOMR3k&utm_medium=viral&utm_source=youtube. This tutorial is a single movie from the R Statistics Essential Training course presented by lynda.com author Barton Poulson. The complete course is 5 hours and 59 minutes and shows how to model statistical relationships using graphs, calculations, tests, and other analysis tools in R Statistics. Introduction 1. Getting Started 2. Charts for One Variable 3. Statistics for One Variable 4. Modifying Data 5. Working with the Data File 6. Charts for Associations 7. Statistics for Associations 8. Charts for Three or More Variables 9. Statistics for Three or More Variables Conclusion
Views: 16219 LinkedIn Learning
Analyzing the Cloudera Hortonworks Merger
 
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Breaking Big Data News last was about the Cloudera Hortonworks merger. What does that mean for the Hadoop Ecosystem? In this episode of the Big Data Beard YouTube show Brett Roberts and Thomas Henson will analyze the merger of the two premier Hadoop Ecosystem distributors. Find out our predictions for the future of Cloudera-Hortonworks and the Hadoop Community as a whole. Be sure to leave comments on your prediction from the Cloudera Hortonworks merger. ► GROW YOUR BIG DATA BEARD - Site devoted to "Exploring all aspects of Big Data & Analytics" ◄ https://bigdatabeard.com/ ► BIG DATA BEARD PODCAST - Subscribe to learn what's going on in the Big Data Community ◄ https://bigdatabeard.com/subscribe-to-podcast/ ► CONNECT ON TWITTER ◄ https://twitter.com/bigdatabeard
Views: 723 Big Data Beard