{"id":1243,"date":"2023-06-22T02:09:32","date_gmt":"2023-06-22T02:09:32","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/introstatstest\/chapter\/errors-in-hypothesis-testing-learn-it-2\/"},"modified":"2025-05-16T03:39:48","modified_gmt":"2025-05-16T03:39:48","slug":"errors-in-hypothesis-testing-learn-it-2","status":"publish","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/introstatstest\/chapter\/errors-in-hypothesis-testing-learn-it-2\/","title":{"raw":"Errors in Hypothesis Testing: Learn It 2","rendered":"Errors in Hypothesis Testing: Learn It 2"},"content":{"raw":"<section class=\"textbox learningGoals\">\r\n<ul>\r\n\t<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;Recognize Type I and Type II errors and their consequences&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:4609,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0,&quot;15&quot;:&quot;Calibri&quot;}\">Recognize Type I and Type II errors and their consequences.<\/span><\/li>\r\n<\/ul>\r\n<\/section>\r\n<h3>How might a type I error arise?<\/h3>\r\n<p>There are several ways in which a Type I error might arise. For example:<\/p>\r\n<ul>\r\n\t<li>Setting a higher significance level increases the chance of rejecting the null hypothesis, making it more likely to commit a Type I error.<\/li>\r\n\t<li>When conducting multiple hypothesis tests simultaneously, the likelihood of making at least one Type I error across all the tests increases<\/li>\r\n\t<li>Outliers or extreme data points can disproportionately influence the results and lead to an erroneous rejection of the null hypothesis.<\/li>\r\n<\/ul>\r\n<h3>How might a type II error arise?<\/h3>\r\n<p class=\"para\">As a researcher, there are two main reasons that you are not able to come to the correct conclusion:<\/p>\r\n<ul>\r\n\t<li class=\"para\">It is too hard to gather enough evidence to reject the null hypothesis. This is typically caused by a small sample size.<\/li>\r\n\t<li class=\"para\">It could be a case where the researcher simply had an \u201cunlucky\u201d sample that resulted in a large P-value.<\/li>\r\n\t<li>Poorly designed experiments with insufficient control groups can lead to a higher chance of Type II errors.<\/li>\r\n\t<li>If the assumptions underlying the statistical test are not met, the test may not perform optimally, leading to an increased risk of Type II errors.<\/li>\r\n<\/ul>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]955[\/ohm2_question]<\/section>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]956[\/ohm2_question]<\/section>","rendered":"<section class=\"textbox learningGoals\">\n<ul>\n<li><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;Recognize Type I and Type II errors and their consequences&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:4609,&quot;3&quot;:{&quot;1&quot;:0},&quot;12&quot;:0,&quot;15&quot;:&quot;Calibri&quot;}\">Recognize Type I and Type II errors and their consequences.<\/span><\/li>\n<\/ul>\n<\/section>\n<h3>How might a type I error arise?<\/h3>\n<p>There are several ways in which a Type I error might arise. For example:<\/p>\n<ul>\n<li>Setting a higher significance level increases the chance of rejecting the null hypothesis, making it more likely to commit a Type I error.<\/li>\n<li>When conducting multiple hypothesis tests simultaneously, the likelihood of making at least one Type I error across all the tests increases<\/li>\n<li>Outliers or extreme data points can disproportionately influence the results and lead to an erroneous rejection of the null hypothesis.<\/li>\n<\/ul>\n<h3>How might a type II error arise?<\/h3>\n<p class=\"para\">As a researcher, there are two main reasons that you are not able to come to the correct conclusion:<\/p>\n<ul>\n<li class=\"para\">It is too hard to gather enough evidence to reject the null hypothesis. This is typically caused by a small sample size.<\/li>\n<li class=\"para\">It could be a case where the researcher simply had an \u201cunlucky\u201d sample that resulted in a large P-value.<\/li>\n<li>Poorly designed experiments with insufficient control groups can lead to a higher chance of Type II errors.<\/li>\n<li>If the assumptions underlying the statistical test are not met, the test may not perform optimally, leading to an increased risk of Type II errors.<\/li>\n<\/ul>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm955\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=955&theme=lumen&iframe_resize_id=ohm955&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm956\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=956&theme=lumen&iframe_resize_id=ohm956&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n","protected":false},"author":8,"menu_order":25,"template":"","meta":{"_candela_citation":"[]","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"part":1205,"module-header":"learn_it","content_attributions":[],"internal_book_links":[],"video_content":null,"cc_video_embed_content":{"cc_scripts":"","media_targets":[]},"try_it_collection":null,"_links":{"self":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters\/1243"}],"collection":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/users\/8"}],"version-history":[{"count":8,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters\/1243\/revisions"}],"predecessor-version":[{"id":6763,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters\/1243\/revisions\/6763"}],"part":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/parts\/1205"}],"metadata":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters\/1243\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/media?parent=1243"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapter-type?post=1243"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/contributor?post=1243"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/license?post=1243"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}