Statistics and Statistics with R Tutorials (All Videos) | MarinStatsLectures - Chi-Square Test, Fisher’s Exact Test, & Cross Tabulations in R | R Tutorial 4.10| MarinStatsLectures

Chi-Square Test, Fisher’s Exact Test, and Cross-Tabulations in R with Example: Learn how to conduct Pearson’s Chi-square test of independence and Fisher's exact test in R, and produce cross tabulations (contingency table/cross tabs) in R. 👉🏼Related: Chi-Square Test of Independence in statistics video (https://youtu.be/pfc9MUz03XA ) 📝 Find R practice dataset (BloodPressure) here: (https://statslectures.com/r-scripts-datasets ) 👍🏼Best Statistics & R Programming Language Tutorials: ( https://goo.gl/4vDQzT ) ►► Want to support us? You can Donate (https://bit.ly/2CWxnP2), Share Our Videos, Leave Comments or Give us a Like! In this R video tutorial, we will learn how to conduct the Pearson’s chi-square test of independence and Fisher's Exact test in R; we will also learn to produce cross tabulations using R programming language. Pearson's chi square test of independence and Fisher’s exact test can be used to test if two variables are independent or dependent and is often used with categorical data. The Chi-Square Test can also be used to test how well a particular distribution fits a set of observed data and is referred to as Pearson's Goodness of Fit Test. Chi Squared test works by comparing the observed contingency table, to what the table would be expected to look like, if the null hypothesis is true, and X and Y are independent. While Chi-Square Test technically is referred to as a non-parametric test, the assumptions and approach to the test look more like a parametric test. If the null hypothesis is rejected, this test tells us nothing about the strength or direction of the association between X and Y, and we must use other measures of association to try and address this. Fisher's exact test is an alternative to the chi-square test of independence, which doesn't rely on large sample theory Cross-tabulation ( contingency tables or cross tabs) displays the frequency distribution of the variables to understand the correlation between them. It also shows how correlations change from one variable grouping to another. It is usually used in statistical analysis to find patterns, trends, and probabilities within raw data These video tutorials are useful for anyone interested in learning data science and statistics with R programming language using RStudio. Table of Content: 0:00:10 when should we use chi-square test of independence 0:00:35 how to use the "chisq.test" in R statistical software 0:00:42 how to access the Help menu in R for the chi-square test of independence 0:00:53 how to use "table" function in R to produce a contingency table for two categorical variables 0:01:15 how to visually examine the relationship between two categorical variables in R before conducting the chi-square test of independence 0:01:26 how to produce clustered bar charts in R programming language using "besides" argument 0:01:42 how to use the "chisq.test" function in R to conduct chi-squared test 0:01:54 how to use "correct" argument in R to do the Yate's continuity correction for the chi-square test 0:02:30 how to ask R to return attributes in an object using "attributes" function 0:02:42 how to extract certain attributes from an object in R using the "$" 0:03:00 when should we use Fisher's exact test 0:03:07 how to use the "fisher.test" function in R to conduct Fisher's exact test 0:03:16 how to calculate the confidence interval for the odds ratio in R using the "conf.int" argument 0:03:24 how to set the desired level of confidence in R using the "conf.level" argument ► ► Watch More: ► Intro to Statistics Course: https://bit.ly/2SQOxDH ►Data Science with R https://bit.ly/1A1Pixc ►Getting Started with R (Series 1): https://bit.ly/2PkTneg ►Graphs and Descriptive Statistics in R (Series 2): https://bit.ly/2PkTneg ►Probability distributions in R (Series 3): https://bit.ly/2AT3wpI ►Bivariate analysis in R (Series 4): https://bit.ly/2SXvcRi ►Linear Regression in R (Series 5): https://bit.ly/1iytAtm ►ANOVA Concept and with R https://bit.ly/2zBwjgL ►Hypothesis Testing: https://bit.ly/2Ff3J9e ►Linear Regression Concept and with R Lectures https://bit.ly/2z8fXg1 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 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!