{"id":2144,"date":"2019-05-15T06:43:25","date_gmt":"2019-05-15T06:43:25","guid":{"rendered":"https:\/\/www.aiproblog.com\/index.php\/2019\/05\/15\/29-statistical-concepts-explained-in-simple-english-part-12\/"},"modified":"2019-05-15T06:43:25","modified_gmt":"2019-05-15T06:43:25","slug":"29-statistical-concepts-explained-in-simple-english-part-12","status":"publish","type":"post","link":"https:\/\/www.aiproblog.com\/index.php\/2019\/05\/15\/29-statistical-concepts-explained-in-simple-english-part-12\/","title":{"rendered":"29 Statistical Concepts Explained in Simple English &#8211; Part 12"},"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\/2522302367?profile=original\" target=\"_blank\" rel=\"noopener noreferrer\"><img decoding=\"async\" src=\"https:\/\/storage.ning.com\/topology\/rest\/1.0\/file\/get\/2522302367?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\/negative-binomial-experiment\/\">Negative Binomial Experiment \/ Distribution: Definition, Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/nested-model-anova-factors\/\">Nested Model, ANOVA and Factors: Simple Definitions and Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/nominal-ordinal-interval-ratio\/\">Nominal Ordinal Interval Ratio: Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/nominal-variable\/\">Nominal Variable: Definition and Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/non-differential-misclassification\/\">Differential &#038; Non-Differential Misclassification<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/nonlinear-regression\/\">Nonlinear Regression: Simple Definition &#038; Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/non-probability-sampling\/\">Non-Probability Sampling: Definition, Types<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/non-response-bias\/\">Non Response Bias: Definition, Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/normalized\/\">Normalized Data \/ Normalization<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/normal-probability-plot\/\">Normal Probability Plot: Definition, Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/normal-probability-practice-problems\/\">Normal Probability Practice Problems and Answers<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/nuisance-variable\/\">Nuisance Variable &#038; Nuisance Parameter: Definition, Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/number-needed-to-harm\/\">Number Needed to Harm NNH: Definition<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/observation-in-statistics\/\">Observation in Statistics: Simple Definition &#038; Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/observer-bias\/\">Observer Bias \/ Research or Experimenter Bias: Definition, Examples, How to Avoid<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/odds-ratio\/\">Odds Ratio Calculation and Interpretation<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/ogive-graph\/\">Ogive Graph \/ Cumulative Frequency Polygon in Easy Steps<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/omega-squared\/\">Omega Squared: Definition<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/one-sample-t-test\/\">One Sample T Test: How to Run It, Step by Step<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/one-sample-z-test\/\">One Sample Z Test: How to Run One<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/open-ended-distribution\/\">Open Ended Distribution: Definition and Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/order-effects\/\">Order Effects: Definition, Examples and Solutions<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/order-of-integration\/\">Order of Integration (Time Series): Simple Definition \/ Overview<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/order-statistics\/\">Order Statistics: Simple Definition, Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/ordinal-numbers\/\">Ordinal Numbers, Variables and Data: Definition and Examples<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/pairwise-independent-mutually\/\">Pairwise Independent, Mutually Independent: Definition, Example<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/parallel-design-parallel-group-study\/\">Parallel Design \/ Parallel Group Study<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/parallel-forms-reliability\/\">Parallel Forms Reliability (Equivalent Forms)<\/a><\/li>\n<li><a href=\"https:\/\/www.statisticshowto.datasciencecentral.com\/parametric-and-non-parametric-data\/\">Non Parametric Data and Tests (Distribution Free Tests)<\/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| <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><\/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:825206\">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\/15\/29-statistical-concepts-explained-in-simple-english-part-12\/\">Read More<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":464,"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\/2144"}],"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=2144"}],"version-history":[{"count":0,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/posts\/2144\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media\/456"}],"wp:attachment":[{"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/media?parent=2144"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/categories?post=2144"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.aiproblog.com\/index.php\/wp-json\/wp\/v2\/tags?post=2144"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}