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*** Check-out the improved version of this video here: https://youtu.be/tDLcBrLzBos I describe the standard normal distribution and its properties with respect to the percentage of observations within each standard deviation. I also make reference to two key statistical demarcation points (i.e., 1.96 and 2.58) and their relationship to the normal distribution. Finally, I mention two tests that can be used to test normal distributions for statistical significance. normal distribution, normal probability distribution, standard normal distribution, normal distribution curve, bell shaped curve
Views: 1050974 how2stats

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Quantile-Quantile (QQ) plots are used to determine if data can be approximated by a statistical distribution. For example, you might collect some data and wonder if it is normally distributed. A QQ plot will help you answer that question. You can also use QQ plots to compare to different datasets that you collected to determine if their distributions are comparable. This video shows you how to do both things. For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/

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See how to calculate and interpret Mean Median Mode Standard Deviation in Excel. Create a Frequency Distribution and then a Histogram. Basic Statistics. Mean Median Mode, and Standard Deviation Mean Median and Mode are all Averages The reason we have averages is because we need "ONE" value that will represent all the values so we can talk about the "typical score". All the data is so spread out that is hard to talk about 'all" the data unless we calculate a typical value. Here are three ways to calculate a typical value: Mean, Median Mode. MEAN is the arithmetic mean (add all the scores and divide by the count). In Excel we use the AVERAGE function MEDIAN is the one in the middle (position) after we have sorted (this is good when we have extreme values like in real estate (most of the houses are around \$200,000, but a few are \$1,000,000)). In Excel we use the MEDIAN function MODE is the one that occurs most often. This is good when we have "word" categories such as preference for "cola". In Excel we use the MODE function (It will not tell you when there are more than 1 mode). The Standard Deviation tells you: 1) how spread out the data is; 2) what the mean deviation is; 3) does the average represent its data points fairly. In Excel we use the STDEV function for a sample and the STDEVP function for a population (population is all possible values; sample is some of the values but not all). Histogram. SUMPRODUCT COUNTIF function formula. Column Chart Ampersand Concatenate all these functions ignore blanks or dashes. If you really want to include them you must put a zero instead of a dash or blank.
Views: 136509 ExcelIsFun

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Construct Frequency Distribution with EXCEL
Views: 1893 Wei Ching Quek

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You have surely seen a normal distribution before as it is the most common one. The statistical term for it is Gaussian distribution, but many people call it the Bell Curve as it is shaped like a bell. It is symmetrical and its mean, median and mode are equal. If you remember the lesson about skewness, you would recognize it has no skew! It is perfectly centered around its mean. Alright. So, it is denoted in this way. N stands for normal, the tilde sign denotes it is a distribution and in brackets we have the mean and the variance of the distribution. On the plane, you can notice that the highest point is located at the mean, because it coincides with the mode. The spread of the graph is determined by the standard deviation. Now, let’s try to understand the normal distribution a little bit better. Website: https://365datascience.com Facebook: https://www.facebook.com/365datascience Twitter: https://twitter.com/365datascience LinkedIn: https://www.linkedin.com/company-beta/18061054/ Google+: https://plus.google.com/114636546494634370189/
Views: 469 365 Data Science

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Subject:Human Resource Management Paper: Performance and Compensation Management
Views: 23150 Vidya-mitra

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I use STATISTICA Data Miner to create a predictive quality control method with some manufacturing data I was able to acquire.

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Normalizing Data
Views: 1412 KevinAtStout

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Views: 131133 Don't Memorise

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Tutorial on calculating the standard deviation and variance for statistics class. The tutorial provides a step by step guide. Like us on: http://www.facebook.com/PartyMoreStudyLess Related Videos: How to Calculate Mean and Standard Deviation Using Excel http://www.youtube.com/watch?v=efdRmGqCYBk Why are degrees of freedom (n-1) used in Variance and Standard Deviation http://www.youtube.com/watch?v=92s7IVS6A34 Playlist of z scores http://www.youtube.com/course?list=EC6157D8E20C151497 David Longstreet Professor of the Universe Like us on: http://www.facebook.com/PartyMoreStudyLess Professor of the Universe: David Longstreet http://www.linkedin.com/in/davidlongstreet/ MyBookSucks.Com
Views: 1571070 statisticsfun

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Tutorial on finding the mean, z score when you know the area (or probability). Playlist on Z scores http://www.youtube.com/course?list=EC6157D8E20C151497 Like MyBookSucks: http://www.facebook.com/PartyMoreStudyLess Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 32137 statisticsfun

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In this video, you learn how to use the Distribution Analysis task in SAS Studio. You learn how to request histograms with overlaid density curves and inset statistics, as well as a normal probability plot and fit statistics for assessing normality.
Views: 4234 SAS Software

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Medical Statistics: Measures of Data Dispersion. In this video I take a look at variance and standard deviation.
Views: 35 Juan Klopper

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This video demonstrates how to create and interpret a scatterplot matrix using in SPSS. A scatterplot matrix is useful for analyzing relationships between multiple variables at the same time.
Views: 40675 Dr. Todd Grande

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Anomaly detection is important for data cleaning, cybersecurity, and robust AI systems. This talk will review recent work in our group on (a) benchmarking existing algorithms, (b) developing a theoretical understanding of their behavior, (c) explaining anomaly "alarms" to a data analyst, and (d) interactively re-ranking candidate anomalies in response to analyst feedback. Then the talk will describe two applications: (a) detecting and diagnosing sensor failures in weather networks and (b) open category detection in supervised learning. See more at https://www.microsoft.com/en-us/research/video/anomaly-detection-algorithms-explanations-applications/
Views: 12712 Microsoft Research

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I use data representing the amount of natural gas used in my home on a daily basis for 30 consecutive days to demonstrate the creation of a random process fitted line plot. I also show calculation of the statistic RMSE (Root Mean Square Error) and use it to represent the quality of fit. The random process model assumes the data fluctuates randomly around a constant level - which we estimate with the mean of the data we've collected.
Views: 1973 ProfTDub

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A common task in data science is to analyze data from an external source that may be in a text or comma separated value (CSV) format. 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. This demonstrates how to import data, perform a basic analysis such as average values, trend the results, save the figure, and export the results to another text file.
Views: 38128 APMonitor.com

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The video describes how to analyze data from a recognition memory experiment to create a Receiver Operating Characteristic (ROC) curve, which indicates how well the person is able to distinguish things they studied from things they didn't study. We don't get too far into the theory here, this really will just let you see how to do the simple calculations that let you create the ROC curve! (this is part I where we set up the problem, in part II we actually plot the ROC)
Views: 56828 Sean Polyn

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This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 8611 Udacity

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We will create a Histogram in Excel using the Histogram tool in the Data Analysis ToolPak, and we will let Excel choose the number of classes/bins to use.
Views: 14084 Vickie Dominguez

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Created with TechSmith Snagit for Google Chrome™ http://goo.gl/ySDBPJ
Views: 61 rberman217

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LDA is surprisingly simple and anyone can understand it. Here I avoid the complex linear algebra and use illustrations to show you what it does so you will know when to use it and how to interpret the results. Sample code for R is at the StatQuest website: https://statquest.org/2016/07/10/statquest-linear-discriminant-analysis-lda-clearly-explained/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider a StatQuest t-shirt or sweatshirt... https://teespring.com/stores/statquest ...or buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/

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Learn how to use formulas in Excel to find out how many of the data points fall within 1, 2, or 3 standard deviations of the mean. For more help, visit my website: http://mathandstatshelp.com
Views: 437 Math and Stats Help

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Checking for a Normal Distribution on SPSS
Views: 15658 LoucollSport

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This brief tutorial provides a quick overview of descriptive statistics, specifically measures of: 1) Central tendency 2) Statistical dispersion 3) Distribution
Views: 690 leuschf

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processing raw data
Views: 3421 Derek Druce

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Views: 3742805 3Blue1Brown

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Here I am describing how to bin data within XLMiner.
Views: 1468 Michael Rechenthin

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Views: 50 Damn! I Love Data

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Views: 2428610 3Blue1Brown

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Creating a confusion matrix using pivot tables for a binary classifier for the loans dataset.
Views: 2372 Vishal Gupta

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This video examines how to calculate a correlation in Google Sheets using multiple variables. All bi-variate (two at a time) correlations are produced.

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Views: 97 Shaun Scott

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Views: 17171 edureka!

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Learn measures of dispersion using Excel For Training & Study packs on Analytics/Data Science/Big Data, Contact us at [email protected] Find all the study packs available with us here: http://analyticsuniversityblog.blogspot.in/ SUBSCRIBE TO THIS CHANNEL for free tutorials on Analytics/Data Science/Big Data/SAS/R/Hadoop

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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2Gi1Gzx]. Kernel density estimate techniques help find the underlying probability distribution. It helps find the probability density function for the given sample of data. Using KDE, we will find the distribution for positively oriented text and negatively oriented text. • Generate histogram for KDE For the latest Big Data and Business Intelligence tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 1483 Packt Video

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All course materials can be found online: https://drive.google.com/drive/folders/11jVCEej9cSN9bzIwgBW0jGAdvBdcnQA7?usp=sharing Information about the tutorial: 3 new workflows in Perseus: 1. Hawaii (multi-volcano) plot: Analyze your pull-down screens in one go. The Hawaii plots offers the same interactivity as the regular volcano plot while providing global control over parameters and making it easier to compare different conditions. Visualize the resulting interaction network directly within Perseus. 2. Phosphoproteomics + PPI: Analyze your PTM data in the context of a PPI network such as STRING. Derive signaling functionality scores that allow you to identify which proteins significantly drive/suppress phosphorylation in your sample. 3.Co-expression analysis + phenotype/clinical: Cluster your data based on a co-expression network. Understand which clusters drive your phenotype by correlating it with proteins representative for each cluster. MaxQuant Summer school 2018 in Barcelona: website: http://summerschool.maxquant.de/summerschool2018/welcome.html program: http://summerschool.maxquant.de/summerschool2018/program.html All the MaxQuant Summer School presentations are going to be live streamed.
Views: 1104 Max Quant

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Learn how to carry out tests for correlations in data using Microsoft Excel, including the Spearman’s rank correlation, and Pearson’s product moment correlation. https://global.oup.com/academic/product/research-methods-for-the-biosciences-9780198728498 This video relates to section 9.5 in the book Research Methods for the Biosciences third edition by Debbie Holmes, Peter Moody, Diana Dine, and Laurence Trueman. The video is narrated by Laurence Trueman. © Oxford University Press

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Tutorial on plotting data in Excel, and getting it to look half-way decent.
Views: 292 Brian Blais

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In these videos I show how you can normalise/denormalise numerical values to a certain range. I also show PHP implementation. My web page: www.imperial.ac.uk/people/n.sadawi

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See more: http://www.ehow.com/tech/
Views: 57539 eHowTech

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A few simple rules for choosing bin sizes for histograms.
Views: 84223 Stephanie Glen

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Views: 4325 Anton Petrov

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This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 4112 Udacity

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