{"id":1144,"date":"2021-08-19T17:49:57","date_gmt":"2021-08-19T17:49:57","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/?post_type=chapter&#038;p=1144"},"modified":"2023-12-05T09:00:59","modified_gmt":"2023-12-05T09:00:59","slug":"summary-terminology","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/chapter\/summary-terminology\/","title":{"raw":"Summary: Terminology","rendered":"Summary: Terminology"},"content":{"raw":"<h2>Key Concepts<\/h2>\r\n<ul>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">A sample space or two-way tables can be used to calculate basic probabilities, where you count the number of items of interest and divide by the total number of items.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">If two events are complementary, the sum of their probabilities is 1.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">[latex]P(A \\ \\mathrm{and} \\ B)[\/latex] means events [latex]A[\/latex] and [latex]B[\/latex] must happen in the same outcome.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">[latex]P(A \\ \\mathrm{or} \\ B)[\/latex] means either event [latex]A[\/latex] or [latex]B[\/latex] (or both) must happen in the outcome.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Conditional probability is calculated as:\r\n<ul>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">[latex]P(A|B) = \\frac{P(A \\ \\mathrm{and} \\ B)}{P(B)}[\/latex]<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\n<h2>Glossary<\/h2>\r\n<strong>chance experiment:\u00a0<\/strong>an experiment where\u00a0the result is not predetermined\r\n\r\n<strong>complement of an event: <\/strong>the complement of event [latex]A[\/latex] consists of all outcomes that are NOT in [latex]A[\/latex]\r\n\r\n<strong>conditional probability:\u00a0<\/strong>the likelihood that an event will occur given that another event has already occurred. [latex]P(A|B)[\/latex] is the conditional probability that event [latex]A[\/latex] will occur given that the event [latex]B[\/latex] has already occurred.\r\n\r\n<strong>empirical:\u00a0<\/strong>a description of an event or experiment that is observed\r\n\r\n<strong>equally likely: <\/strong>each outcome of an experiment has the same probability\r\n\r\n<strong>event:\u00a0<\/strong>a subset of the set of all outcomes of an experiment; the set of all outcomes of an experiment is called a sample space and is usually denoted by [latex]S[\/latex]. An event is an arbitrary subset in [latex]S[\/latex]. It can contain one outcome, two outcomes, no outcomes (empty subset), the entire sample space, and the like. Standard notations for events are capital letters such as [latex]A, B, C,[\/latex] and so on.\r\n\r\n<strong>experiment:\u00a0<\/strong>a planned activity carried out under controlled conditions\r\n\r\n<strong>law of large numbers:\u00a0<\/strong>as more experiments are done, the experimental probability approaches the theoretical probability\r\n\r\n<strong>outcome:\u00a0<\/strong>a particular result of an experiment\r\n\r\n<strong>probability:\u00a0<\/strong>a number between zero and one, inclusive, that gives the likelihood that a specific event will occur; also described as long-term relative frequency. Probabilities are between 0 and 1, inclusive.\r\n\r\n<strong>sample space:\u00a0<\/strong>the set of all possible outcomes of an experiment","rendered":"<h2>Key Concepts<\/h2>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">A sample space or two-way tables can be used to calculate basic probabilities, where you count the number of items of interest and divide by the total number of items.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">If two events are complementary, the sum of their probabilities is 1.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">[latex]P(A \\ \\mathrm{and} \\ B)[\/latex] means events [latex]A[\/latex] and [latex]B[\/latex] must happen in the same outcome.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">[latex]P(A \\ \\mathrm{or} \\ B)[\/latex] means either event [latex]A[\/latex] or [latex]B[\/latex] (or both) must happen in the outcome.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Conditional probability is calculated as:\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">[latex]P(A|B) = \\frac{P(A \\ \\mathrm{and} \\ B)}{P(B)}[\/latex]<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h2>Glossary<\/h2>\n<p><strong>chance experiment:\u00a0<\/strong>an experiment where\u00a0the result is not predetermined<\/p>\n<p><strong>complement of an event: <\/strong>the complement of event [latex]A[\/latex] consists of all outcomes that are NOT in [latex]A[\/latex]<\/p>\n<p><strong>conditional probability:\u00a0<\/strong>the likelihood that an event will occur given that another event has already occurred. [latex]P(A|B)[\/latex] is the conditional probability that event [latex]A[\/latex] will occur given that the event [latex]B[\/latex] has already occurred.<\/p>\n<p><strong>empirical:\u00a0<\/strong>a description of an event or experiment that is observed<\/p>\n<p><strong>equally likely: <\/strong>each outcome of an experiment has the same probability<\/p>\n<p><strong>event:\u00a0<\/strong>a subset of the set of all outcomes of an experiment; the set of all outcomes of an experiment is called a sample space and is usually denoted by [latex]S[\/latex]. An event is an arbitrary subset in [latex]S[\/latex]. It can contain one outcome, two outcomes, no outcomes (empty subset), the entire sample space, and the like. Standard notations for events are capital letters such as [latex]A, B, C,[\/latex] and so on.<\/p>\n<p><strong>experiment:\u00a0<\/strong>a planned activity carried out under controlled conditions<\/p>\n<p><strong>law of large numbers:\u00a0<\/strong>as more experiments are done, the experimental probability approaches the theoretical probability<\/p>\n<p><strong>outcome:\u00a0<\/strong>a particular result of an experiment<\/p>\n<p><strong>probability:\u00a0<\/strong>a number between zero and one, inclusive, that gives the likelihood that a specific event will occur; also described as long-term relative frequency. Probabilities are between 0 and 1, inclusive.<\/p>\n<p><strong>sample space:\u00a0<\/strong>the set of all possible outcomes of an experiment<\/p>\n\n\t\t\t <section class=\"citations-section\" role=\"contentinfo\">\n\t\t\t <h3>Candela Citations<\/h3>\n\t\t\t\t\t <div>\n\t\t\t\t\t\t <div id=\"citation-list-1144\">\n\t\t\t\t\t\t\t <div class=\"licensing\"><div class=\"license-attribution-dropdown-subheading\">CC licensed content, Original<\/div><ul class=\"citation-list\"><li><strong>Provided by<\/strong>: Lumen Learning. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><\/ul><div class=\"license-attribution-dropdown-subheading\">CC licensed content, Shared previously<\/div><ul class=\"citation-list\"><li>Introductory Statistics. <strong>Authored by<\/strong>: Barbara Illowsky, Susan Dean. <strong>Provided by<\/strong>: OpenStax. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"https:\/\/openstax.org\/books\/introductory-statistics\/pages\/3-key-terms\">https:\/\/openstax.org\/books\/introductory-statistics\/pages\/3-key-terms<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em>. <strong>License Terms<\/strong>: Access for free at https:\/\/openstax.org\/books\/introductory-statistics\/pages\/1-introduction<\/li><\/ul><\/div>\n\t\t\t\t\t\t <\/div>\n\t\t\t\t\t <\/div>\n\t\t\t <\/section>","protected":false},"author":169134,"menu_order":9,"template":"","meta":{"_candela_citation":"[{\"type\":\"cc\",\"description\":\"Introductory Statistics\",\"author\":\"Barbara Illowsky, Susan Dean\",\"organization\":\"OpenStax\",\"url\":\"https:\/\/openstax.org\/books\/introductory-statistics\/pages\/3-key-terms\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"Access for free at https:\/\/openstax.org\/books\/introductory-statistics\/pages\/1-introduction\"},{\"type\":\"original\",\"description\":\"\",\"author\":\"\",\"organization\":\"Lumen Learning\",\"url\":\"\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"\"}]","CANDELA_OUTCOMES_GUID":"","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-1144","chapter","type-chapter","status-publish","hentry"],"part":43,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/pressbooks\/v2\/chapters\/1144","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/wp\/v2\/users\/169134"}],"version-history":[{"count":8,"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/pressbooks\/v2\/chapters\/1144\/revisions"}],"predecessor-version":[{"id":3448,"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/pressbooks\/v2\/chapters\/1144\/revisions\/3448"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/pressbooks\/v2\/parts\/43"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/pressbooks\/v2\/chapters\/1144\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/wp\/v2\/media?parent=1144"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/pressbooks\/v2\/chapter-type?post=1144"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/wp\/v2\/contributor?post=1144"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/introstatscorequisite\/wp-json\/wp\/v2\/license?post=1144"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}