Statistics and Statistics with R Tutorials (All Videos) | MarinStatsLectures - Samples from a Normal Distribution | Statistics Tutorial #4 | MarinStatsLectures

Samples From a Normal Distribution: What does normal in statistics look like? How do samples in statistics vary from population? (with examples and web simulations) Web simulation tool for Sampling (https://bit.ly/2FhJ3xn) "Understanding Normal Sample" R-Script: (https://bit.ly/2rOfgEJ) 👍🏼Best Statistics & R Programming Language Tutorials: ( https://goo.gl/4vDQzT ) ►► Like to support us? You can Donate (https://bit.ly/2CWxnP2), Share our Videos, Leave us a Comment and Give us a Like! Either way We Thank You! In this video we learn about how samples behave. First, we will use R programming language to run simulations by drawing a sample from a normal distribution and create histograms, and calculate mean and standard deviations for it. We will also use a very cool web visualization tool to draw various samples of different sizes from a normal distribution, create histograms, and calculate mean and standard deviations for it. Often, a sample which we might think as "skewed" or "not normal" actually IS normal at the population level We will take samples from a Normally distributed population, and look at the shapes of the histograms that we will end up with. This will help us to see that "normal data doesn't always look so normal" This is important, because many statistical methods rely on an assumption of normality, and so we need to have a better understanding of "how samples behave", and not be so quick to label data as skewed/non-normal. This will lead us into a discussion of a Sampling Distribution: the theoretical set of "all possible" sample means we may end up with when taking a sample. First we must learn to understand how samples behave, and what sorts of estimates may show up in data. Once we understand this, we can then do "statistical inference", and use our sample to make statements or generalizations back to the population. This video is the step in understanding how samples vary from the true or population value. ◼︎ Table of Content 0:00:49 Using R Programming Software to run simulations by drawing a sample from a normal distribution create histograms, and calculate mean and standard deviations 0:04:01 Using a web visualization tool to draw various samples of different sizes from a normal distribution, create histograms, and calculate mean and standard deviations ►► Watch More: ►Normal Distribution Concept: https://youtu.be/zUnC1CV4FAc ►Normal Distribution in R: https://youtu.be/peEsXbdMY_4 ►Intro to Statistics Course (complete series): https://bit.ly/2SQOxDH ►Data Science with R course (complete series): https://bit.ly/1A1Pixc ►Getting Started with R (Series 1): https://bit.ly/2PkTneg ►Graphs and Descriptive Statistics in R (Series 2): ►Probability distributions in R (Series 3): https://bit.ly/2AT3wpI ►Bivariate analysis in R (Series 4): https://bit.ly/2SXvcRi ►Linear Regression in R (Series 5): https://bit.ly/1iytAtm ►ANOVA course https://bit.ly/2zBwjgL ►Linear Regression Concept and with R course https://bit.ly/2z8fXg1 ►Puppet Master of Statistics: https://bit.ly/2RDAAv4 ►Hypothesis Testing course https://bit.ly/2Ff3J9e Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support some statistics and R programming language courses at The University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!