{"id":1805,"date":"2023-04-14T14:34:38","date_gmt":"2023-04-14T14:34:38","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/?post_type=chapter&#038;p=1805"},"modified":"2024-10-18T20:54:43","modified_gmt":"2024-10-18T20:54:43","slug":"sampling-and-experimentation-fresh-take","status":"web-only","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/chapter\/sampling-and-experimentation-fresh-take\/","title":{"raw":"Sampling and Experimentation: Fresh Take","rendered":"Sampling and Experimentation: Fresh Take"},"content":{"raw":"<section class=\"textbox learningGoals\">\r\n<ul>\r\n \t<li>Identify methods for obtaining a random sample of the intended population of a study<\/li>\r\n \t<li>Identify types of sample bias<\/li>\r\n \t<li>Identify the differences between observational studies and experiments, and the treatment in an experiment<\/li>\r\n \t<li>Determine whether an experiment may have been influenced by confounding<\/li>\r\n<\/ul>\r\n<\/section>\r\n<h2>Random Sampling<\/h2>\r\n<div class=\"textbox shaded\">\r\n\r\n<strong>The Main Idea\u00a0<\/strong>\r\n\r\nSampling methods that are not statistically random are\u00a0<strong>biased<\/strong>. That is, they inherently exclude certain members of the population from being selected in the sample.\r\n<div style=\"font-weight: 400;\">\r\n\r\n<strong>Unbiased<\/strong> sampling produces samples that are<strong> representative<\/strong> of the population.\r\n\r\n<\/div>\r\n<div style=\"font-weight: 400;\">\r\n\r\nRepresentative samples can be used to<strong> generalize<\/strong> results from the sample to the population.\r\n\r\n<\/div>\r\n<div style=\"font-weight: 400;\">\r\n\r\n<strong>Random sampling<\/strong> methods eliminate bias by removing human opinion or preference from the sampling method.\r\n\r\n<strong>Simple random sampling<\/strong> is a method of random sampling in which every member of the population has an equal chance of being selected in the sample. We can assign a unique number to each population member and use a <strong>random number generator<\/strong> to collect random samples.\r\n\r\n<\/div>\r\n<\/div>\r\n<h2>Sampling Methods<\/h2>\r\n<div class=\"textbox shaded\">\r\n\r\n<strong>The Main Idea<\/strong>\r\n\r\n<strong>Simple random sampling<\/strong> assigns a number to every member of the population, then uses a random number generator to select a sample.\r\n\r\n<strong>Systematic sampling<\/strong> assigns a number to every member of the population, then choses individuals\/entities from the population at regular intervals (e.g. every [latex]4[\/latex]th individual from a randomly selected starting point).\r\n\r\n<strong>Stratified sampling<\/strong> divides a population into groups via some criterion, then uses simple random selection or systematic selection to collect a sample from each group.\r\n\r\n<strong>Convenience sampling<\/strong> selects a sample most accessible to the researcher.\r\n\r\n<\/div>\r\nThe video below discusses sampling bias and sampling methods.\r\n\r\n<section class=\"textbox watchIt\"><iframe src=\"\/\/plugin.3playmedia.com\/show?mf=10356053&amp;p3sdk_version=1.10.1&amp;p=20361&amp;pt=375&amp;video_id=pTuj57uXWlk&amp;video_target=tpm-plugin-qta5bbz3-pTuj57uXWlk\" width=\"800px\" height=\"450px\" frameborder=\"0\" marginwidth=\"0px\" marginheight=\"0px\"><\/iframe>\r\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/Types+of+Sampling+Methods+(4.1).txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cTypes of Sampling Methods (4.1)\u201d here (opens in new window).<\/a><\/p><\/section>\r\n<h2>Biased Sampling Methods<\/h2>\r\n<div class=\"textbox shaded\">\r\n\r\n<strong>The Main Idea<\/strong>\r\n\r\nNon-random sampling methods can exclude certain members of a population from having a chance to be selected in the sample. A sampling method like this is called a <strong>biased<\/strong> sampling method because it will tend to favor certain population groups over others.\r\n\r\nYou learned about different kinds of sampling bias in this section.\r\n<ul>\r\n \t<li><strong>Sampling bias<\/strong> \u2013 when the sample is not representative of the population<\/li>\r\n \t<li><strong>Voluntary response bias<\/strong> \u2013 the sampling bias that often occurs when the sample is volunteers<\/li>\r\n \t<li><strong>Self-interest study<\/strong> \u2013 bias that can occur when the researchers have an interest in the outcome<\/li>\r\n \t<li><strong>Response bias<\/strong> \u2013 when the responder gives inaccurate responses for any reason<\/li>\r\n \t<li><strong>Perceived lack of anonymity<\/strong> \u2013 when the responder fears giving an honest answer might negatively affect them<\/li>\r\n \t<li><strong>Loaded questions<\/strong> \u2013 when the question wording influences the responses<\/li>\r\n \t<li><strong>Non-response bias<\/strong> \u2013 when people refusing to participate in the study can influence the validity of the outcome<\/li>\r\n \t<li><strong>Undercoverage<\/strong>\u00a0occurs when some groups of the population are left out of the sampling process.<\/li>\r\n<\/ul>\r\n<\/div>\r\n<section class=\"textbox watchIt\"><iframe src=\"\/\/plugin.3playmedia.com\/show?mf=10356054&amp;p3sdk_version=1.10.1&amp;p=20361&amp;pt=375&amp;video_id=th_nXWnaseM&amp;video_target=tpm-plugin-5av5wyao-th_nXWnaseM\" width=\"800px\" height=\"450px\" frameborder=\"0\" marginwidth=\"0px\" marginheight=\"0px\"><\/iframe>\r\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/Biased+Sampling+Methods.txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cBiased Sampling Methods\u201d here (opens in new window).<\/a><\/p><\/section>\r\n<h2>Experiments<\/h2>\r\n<div class=\"textbox shaded\">\r\n\r\n<strong>The Main Idea<\/strong>\r\n<ul>\r\n \t<li>An <strong>observational study<\/strong> is a study based on observations or measurements<\/li>\r\n \t<li>An <strong>experiment<\/strong> is a study in which the effects of a <strong>treatment<\/strong> are measured<\/li>\r\n \t<li>A <strong>treatment <\/strong>in an experiment refers to a specific intervention or condition that is applied to the subjects or participants in order to test its effects on a particular outcome variable.<\/li>\r\n \t<li>The <strong>experimental group<\/strong> is the group that receives the treatment<\/li>\r\n \t<li>The <strong>control group<\/strong> is the group that does not receive the treatment<\/li>\r\n \t<li><strong>Confounding<\/strong> occurs when there are two potential variables that could have caused the outcome and it is not possible to determine which actually caused the result.<\/li>\r\n \t<li>The <strong>placebo effect<\/strong> is when the effectiveness of a treatment is influenced by the patient\u2019s perception of how effective they think the treatment will be, so a result might be seen even if the treatment is ineffectual.<\/li>\r\n \t<li>A <strong>placebo<\/strong> is a dummy treatment given to control for the placebo effect.<\/li>\r\n \t<li>An experiment that gives the control group a placebo is called a <strong>placebo controlled experiment<\/strong>.<\/li>\r\n \t<li>A <strong>blind study<\/strong> is one in which the participant does not know whether they are receiving the treatment or a placebo.<\/li>\r\n \t<li>A <strong>double-blind study<\/strong> is one in which those interacting with the participants don\u2019t know who is in the treatment group and who is in the control group.<\/li>\r\n<\/ul>\r\n<\/div>\r\n<section class=\"textbox watchIt\"><iframe src=\"\/\/plugin.3playmedia.com\/show?mf=10356055&amp;p3sdk_version=1.10.1&amp;p=20361&amp;pt=375&amp;video_id=2OnduwEujlk&amp;video_target=tpm-plugin-trtxpp0o-2OnduwEujlk\" width=\"800px\" height=\"450px\" frameborder=\"0\" marginwidth=\"0px\" marginheight=\"0px\"><\/iframe>\r\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/Observational+Study+vs+Experiment.txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cObservational Study vs Experiment\u201d here (opens in new window).<\/a><\/p><\/section><section class=\"textbox watchIt\"><iframe src=\"\/\/plugin.3playmedia.com\/show?mf=10356056&amp;p3sdk_version=1.10.1&amp;p=20361&amp;pt=375&amp;video_id=sKkCZqqZ3qE&amp;video_target=tpm-plugin-6lxje33p-sKkCZqqZ3qE\" width=\"800px\" height=\"450px\" frameborder=\"0\" marginwidth=\"0px\" marginheight=\"0px\"><\/iframe>\r\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/What+is+a+Confounding+Variable%3F.txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cWhat is a Confounding Variable?\u201d here (opens in new window).<\/a><\/p><\/section><section class=\"textbox watchIt\"><iframe title=\"YouTube video player\" src=\"https:\/\/www.youtube.com\/embed\/z03FQGlGgo0\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe>\r\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/The+power+of+the+placebo+effect+-+Emma+Bryce.txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cThe power of the placebo effect - Emma Bryce\u201d here (opens in new window).<\/a><\/p><\/section>","rendered":"<section class=\"textbox learningGoals\">\n<ul>\n<li>Identify methods for obtaining a random sample of the intended population of a study<\/li>\n<li>Identify types of sample bias<\/li>\n<li>Identify the differences between observational studies and experiments, and the treatment in an experiment<\/li>\n<li>Determine whether an experiment may have been influenced by confounding<\/li>\n<\/ul>\n<\/section>\n<h2>Random Sampling<\/h2>\n<div class=\"textbox shaded\">\n<p><strong>The Main Idea\u00a0<\/strong><\/p>\n<p>Sampling methods that are not statistically random are\u00a0<strong>biased<\/strong>. That is, they inherently exclude certain members of the population from being selected in the sample.<\/p>\n<div style=\"font-weight: 400;\">\n<p><strong>Unbiased<\/strong> sampling produces samples that are<strong> representative<\/strong> of the population.<\/p>\n<\/div>\n<div style=\"font-weight: 400;\">\n<p>Representative samples can be used to<strong> generalize<\/strong> results from the sample to the population.<\/p>\n<\/div>\n<div style=\"font-weight: 400;\">\n<p><strong>Random sampling<\/strong> methods eliminate bias by removing human opinion or preference from the sampling method.<\/p>\n<p><strong>Simple random sampling<\/strong> is a method of random sampling in which every member of the population has an equal chance of being selected in the sample. We can assign a unique number to each population member and use a <strong>random number generator<\/strong> to collect random samples.<\/p>\n<\/div>\n<\/div>\n<h2>Sampling Methods<\/h2>\n<div class=\"textbox shaded\">\n<p><strong>The Main Idea<\/strong><\/p>\n<p><strong>Simple random sampling<\/strong> assigns a number to every member of the population, then uses a random number generator to select a sample.<\/p>\n<p><strong>Systematic sampling<\/strong> assigns a number to every member of the population, then choses individuals\/entities from the population at regular intervals (e.g. every [latex]4[\/latex]th individual from a randomly selected starting point).<\/p>\n<p><strong>Stratified sampling<\/strong> divides a population into groups via some criterion, then uses simple random selection or systematic selection to collect a sample from each group.<\/p>\n<p><strong>Convenience sampling<\/strong> selects a sample most accessible to the researcher.<\/p>\n<\/div>\n<p>The video below discusses sampling bias and sampling methods.<\/p>\n<section class=\"textbox watchIt\"><iframe loading=\"lazy\" src=\"\/\/plugin.3playmedia.com\/show?mf=10356053&amp;p3sdk_version=1.10.1&amp;p=20361&amp;pt=375&amp;video_id=pTuj57uXWlk&amp;video_target=tpm-plugin-qta5bbz3-pTuj57uXWlk\" width=\"800px\" height=\"450px\" frameborder=\"0\" marginwidth=\"0px\" marginheight=\"0px\"><\/iframe><\/p>\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/Types+of+Sampling+Methods+(4.1).txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cTypes of Sampling Methods (4.1)\u201d here (opens in new window).<\/a><\/p>\n<\/section>\n<h2>Biased Sampling Methods<\/h2>\n<div class=\"textbox shaded\">\n<p><strong>The Main Idea<\/strong><\/p>\n<p>Non-random sampling methods can exclude certain members of a population from having a chance to be selected in the sample. A sampling method like this is called a <strong>biased<\/strong> sampling method because it will tend to favor certain population groups over others.<\/p>\n<p>You learned about different kinds of sampling bias in this section.<\/p>\n<ul>\n<li><strong>Sampling bias<\/strong> \u2013 when the sample is not representative of the population<\/li>\n<li><strong>Voluntary response bias<\/strong> \u2013 the sampling bias that often occurs when the sample is volunteers<\/li>\n<li><strong>Self-interest study<\/strong> \u2013 bias that can occur when the researchers have an interest in the outcome<\/li>\n<li><strong>Response bias<\/strong> \u2013 when the responder gives inaccurate responses for any reason<\/li>\n<li><strong>Perceived lack of anonymity<\/strong> \u2013 when the responder fears giving an honest answer might negatively affect them<\/li>\n<li><strong>Loaded questions<\/strong> \u2013 when the question wording influences the responses<\/li>\n<li><strong>Non-response bias<\/strong> \u2013 when people refusing to participate in the study can influence the validity of the outcome<\/li>\n<li><strong>Undercoverage<\/strong>\u00a0occurs when some groups of the population are left out of the sampling process.<\/li>\n<\/ul>\n<\/div>\n<section class=\"textbox watchIt\"><iframe loading=\"lazy\" src=\"\/\/plugin.3playmedia.com\/show?mf=10356054&amp;p3sdk_version=1.10.1&amp;p=20361&amp;pt=375&amp;video_id=th_nXWnaseM&amp;video_target=tpm-plugin-5av5wyao-th_nXWnaseM\" width=\"800px\" height=\"450px\" frameborder=\"0\" marginwidth=\"0px\" marginheight=\"0px\"><\/iframe><\/p>\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/Biased+Sampling+Methods.txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cBiased Sampling Methods\u201d here (opens in new window).<\/a><\/p>\n<\/section>\n<h2>Experiments<\/h2>\n<div class=\"textbox shaded\">\n<p><strong>The Main Idea<\/strong><\/p>\n<ul>\n<li>An <strong>observational study<\/strong> is a study based on observations or measurements<\/li>\n<li>An <strong>experiment<\/strong> is a study in which the effects of a <strong>treatment<\/strong> are measured<\/li>\n<li>A <strong>treatment <\/strong>in an experiment refers to a specific intervention or condition that is applied to the subjects or participants in order to test its effects on a particular outcome variable.<\/li>\n<li>The <strong>experimental group<\/strong> is the group that receives the treatment<\/li>\n<li>The <strong>control group<\/strong> is the group that does not receive the treatment<\/li>\n<li><strong>Confounding<\/strong> occurs when there are two potential variables that could have caused the outcome and it is not possible to determine which actually caused the result.<\/li>\n<li>The <strong>placebo effect<\/strong> is when the effectiveness of a treatment is influenced by the patient\u2019s perception of how effective they think the treatment will be, so a result might be seen even if the treatment is ineffectual.<\/li>\n<li>A <strong>placebo<\/strong> is a dummy treatment given to control for the placebo effect.<\/li>\n<li>An experiment that gives the control group a placebo is called a <strong>placebo controlled experiment<\/strong>.<\/li>\n<li>A <strong>blind study<\/strong> is one in which the participant does not know whether they are receiving the treatment or a placebo.<\/li>\n<li>A <strong>double-blind study<\/strong> is one in which those interacting with the participants don\u2019t know who is in the treatment group and who is in the control group.<\/li>\n<\/ul>\n<\/div>\n<section class=\"textbox watchIt\"><iframe loading=\"lazy\" src=\"\/\/plugin.3playmedia.com\/show?mf=10356055&amp;p3sdk_version=1.10.1&amp;p=20361&amp;pt=375&amp;video_id=2OnduwEujlk&amp;video_target=tpm-plugin-trtxpp0o-2OnduwEujlk\" width=\"800px\" height=\"450px\" frameborder=\"0\" marginwidth=\"0px\" marginheight=\"0px\"><\/iframe><\/p>\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/Observational+Study+vs+Experiment.txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cObservational Study vs Experiment\u201d here (opens in new window).<\/a><\/p>\n<\/section>\n<section class=\"textbox watchIt\"><iframe loading=\"lazy\" src=\"\/\/plugin.3playmedia.com\/show?mf=10356056&amp;p3sdk_version=1.10.1&amp;p=20361&amp;pt=375&amp;video_id=sKkCZqqZ3qE&amp;video_target=tpm-plugin-6lxje33p-sKkCZqqZ3qE\" width=\"800px\" height=\"450px\" frameborder=\"0\" marginwidth=\"0px\" marginheight=\"0px\"><\/iframe><\/p>\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/What+is+a+Confounding+Variable%3F.txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cWhat is a Confounding Variable?\u201d here (opens in new window).<\/a><\/p>\n<\/section>\n<section class=\"textbox watchIt\"><iframe loading=\"lazy\" title=\"YouTube video player\" src=\"https:\/\/www.youtube.com\/embed\/z03FQGlGgo0\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p>You can view the\u00a0<a href=\"https:\/\/course-building.s3.us-west-2.amazonaws.com\/Quantitative+Reasoning+-+2023+Build\/Transcriptions\/The+power+of+the+placebo+effect+-+Emma+Bryce.txt\" target=\"_blank\" rel=\"noopener\">transcript for \u201cThe power of the placebo effect &#8211; Emma Bryce\u201d here (opens in new window).<\/a><\/p>\n<\/section>\n","protected":false},"author":15,"menu_order":18,"template":"","meta":{"_candela_citation":"[]","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"part":86,"module-header":"fresh_take","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\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/1805"}],"collection":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/users\/15"}],"version-history":[{"count":25,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/1805\/revisions"}],"predecessor-version":[{"id":15401,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/1805\/revisions\/15401"}],"part":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/parts\/86"}],"metadata":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/1805\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/media?parent=1805"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapter-type?post=1805"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/contributor?post=1805"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/license?post=1805"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}