{"id":2174,"date":"2019-05-22T06:34:03","date_gmt":"2019-05-22T06:34:03","guid":{"rendered":"https:\/\/www.aiproblog.com\/index.php\/2019\/05\/22\/29-statistical-concepts-explained-in-simple-english-part-13\/"},"modified":"2019-05-22T06:34:03","modified_gmt":"2019-05-22T06:34:03","slug":"29-statistical-concepts-explained-in-simple-english-part-13","status":"publish","type":"post","link":"https:\/\/www.aiproblog.com\/index.php\/2019\/05\/22\/29-statistical-concepts-explained-in-simple-english-part-13\/","title":{"rendered":"29 Statistical Concepts Explained in Simple English &#8211; Part 13"},"content":{"rendered":"<p>Author: Vincent Granville<\/p>\n<div>\n<p>This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles,<span>\u00a0<\/span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/check-out-our-dsc-newsletter\" target=\"_blank\" rel=\"noopener noreferrer\">sign up on DSC<\/a>.<\/p>\n<p><a href=\"https:\/\/storage.ning.com\/topology\/rest\/1.0\/file\/get\/2650280130?profile=original\" target=\"_blank\" rel=\"noopener noreferrer\"><img decoding=\"async\" src=\"https:\/\/storage.ning.com\/topology\/rest\/1.0\/file\/get\/2650280130?profile=RESIZE_710x\" class=\"align-center\"><\/a><\/p>\n<p><strong>29 Statistical Concepts Explained in Simple English<\/strong><\/p>\n<ul>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/parametric-statistics\/\">Parametric Statistics, Tests and Data<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/pareto-distribution\/\">Pareto Distribution Definition<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/parsimonious-model\/\">Parsimonious Model: Definition, Ways to Compare Models<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/partial-correlation\/\">Partial Correlation &#038; Semi-Partial: Definition &#038; Example<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/pearson-mode-skewness\/\">Pearson Mode Skewness: Definition and Formulas<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/pearsons-coefficient-of-skewness\/\">Pearson&#8217;s Coefficient of Skewness<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/percent-error-difference\/\">Percent Error &#038; Percent Difference: Definition &#038; Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/percentile-z-score\/\">Z score to Percentile Calculator and Manual Methods<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/performance-bias\/\">Performance Bias: Definition and Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/permuted-block-randomization\/\">Permuted Block Randomization<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/pert-distribution\/\">PERT Distribution \/ Beta-PERT: Definition, Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/phi-coefficient-mean-square-contingency-coefficient\/\">Phi Coefficient (Mean Square Contingency Coefficient)<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/pillais-trace\/\">Pillai&#8217;s Trace<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/point-biserial-correlation\/\">Point-Biserial Correlation &#038; Biserial Correlation: Definition, Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/point-estimate\/\">Point Estimate: Definition<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/poisson-distribution\/\">Poisson Distribution \/ Poisson Curve: Simple Definition<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/pooled-standard-deviation\/\">Pooled Standard Deviation<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/population-density-definition\/\">Population Density Definition<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/population-mean\/\">Population Mean Definition<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/population-proportion\/\">Population Proportion<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/population-variance\/\">Population Variance: Definition and Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/posterior-distribution-probability\/\">Posterior Probability &#038; the Posterior Distribution<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/post-hoc\/\">Post-Hoc Definition and Types of Post Hoc Tests<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/power-law\/\">Power Law and Power Law Distribution<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/practice-effect\/\">Practice Effect &#038; Carry Over Effect Definition &#038; Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/prediction-interval\/\">Prediction Interval: Simple Definition, Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/predictive-validity\/\">Predictive Validity<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/primary-data-secondary\/\">Primary Data &#038; Secondary Data: Definition &#038; Example<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/probabilistic\/\">Probabilistic: Definition, Models and Theory Explained<\/a><\/li>\n<\/ul>\n<p>Previous editions, in alphabetical order, can be accessed here:<\/p>\n<p style=\"text-align: center;\"><span>\u00a0<\/span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/29-statistical-concepts-explained-in-simple-english-part-1\" target=\"_blank\" rel=\"noopener noreferrer\">Part 1<\/a><span>\u00a0<\/span>|<span>\u00a0<\/span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/25-statistical-concepts-explained-in-simple-english-part-2\" target=\"_blank\" rel=\"noopener noreferrer\">Part 2<\/a><span>\u00a0<\/span>|<span>\u00a0<\/span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/29-statistical-concepts-explained-in-simple-english-part-2\" target=\"_blank\" rel=\"noopener noreferrer\">Part 3<\/a>\u00a0|<span>\u00a0<\/span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/29-statistical-concepts-explained-in-simple-english-part-4\" target=\"_blank\" rel=\"noopener noreferrer\">Part 4<\/a>\u00a0|<span>\u00a0<\/span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/27-statistical-concepts-explained-in-simple-english-part-5\" target=\"_blank\" rel=\"noopener noreferrer\">Part 5<\/a>\u00a0|<span>\u00a0<\/span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/26-statistical-concepts-explained-in-simple-english-part-6\" target=\"_blank\" rel=\"noopener noreferrer\">Part 6<\/a><em>\u00a0|<\/em><span>\u00a0<\/span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/23-statistical-concepts-explained-in-simple-english-part-7\" target=\"_blank\" rel=\"noopener noreferrer\">Part 7<\/a><em>\u00a0|<\/em><span>\u00a0<\/span><span><a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/31-statistical-concepts-explained-in-simple-english-part-8\" target=\"_blank\" rel=\"noopener noreferrer\">Part 8<\/a>\u00a0|\u00a0<a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/31-statistical-concepts-explained-in-simple-english-part-9\" target=\"_blank\" rel=\"noopener noreferrer\">Part 9<\/a>\u00a0|\u00a0<a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/33-statistical-concepts-explained-in-simple-english\" target=\"_blank\" rel=\"noopener noreferrer\">Part 10<\/a>\u00a0|\u00a0<a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/32-statistical-concepts-explained-in-simple-english-part-11\" target=\"_blank\" rel=\"noopener noreferrer\">Part 11<\/a><\/span>\u00a0| <a href=\"https:\/\/www.datasciencecentral.com\/profiles\/blogs\/32-statistical-concepts-explained-in-simple-english-part-12\" target=\"_blank\" rel=\"noopener noreferrer\">Part 12<\/a><\/p>\n<p><em>To make sure you keep getting these emails, please add\u00a0\u00a0mail@newsletter.datasciencecentral.com\u00a0<\/em><span><em>to your address book or whitelist us.\u00a0<\/em>\u00a0<\/span><\/p>\n<\/div>\n<p><a href=\"https:\/\/www.datasciencecentral.com\/xn\/detail\/6448529:BlogPost:829002\">Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Author: Vincent Granville This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, [&hellip;] <span class=\"read-more-link\"><a class=\"read-more\" href=\"https:\/\/www.aiproblog.com\/index.php\/2019\/05\/22\/29-statistical-concepts-explained-in-simple-english-part-13\/\">Read More<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":475,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[26],"tags":[],"_links":{"self":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/2174"}],"collection":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/comments?post=2174"}],"version-history":[{"count":0,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/2174\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media\/458"}],"wp:attachment":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media?parent=2174"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/categories?post=2174"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/tags?post=2174"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}