{"id":152,"date":"2020-07-10T02:34:44","date_gmt":"2020-07-10T02:34:44","guid":{"rendered":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/chapter\/chapter-2-test-planning-and-results\/"},"modified":"2026-03-16T13:58:15","modified_gmt":"2026-03-16T13:58:15","slug":"chapter-2-test-planning-and-results","status":"publish","type":"chapter","link":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/chapter\/chapter-2-test-planning-and-results\/","title":{"raw":"Chapter 1: Test Planning and Results","rendered":"Chapter 1: Test Planning and Results"},"content":{"raw":"<strong><span style=\"color: #1b3b80;\">Watch the Interactive Video: Test Planning Overview<\/span><\/strong>\n\nThe original version of this chapter contained H5P content. You may want to remove or replace this element.\n<h2><strong><span style=\"color: #1b3b80;\">Testing Inferences<\/span><\/strong><\/h2>\nSuppose you tested your prototype with independent variable \"A\" at level <em>a<\/em>, and an observed dependent variable \"<em>B\"<\/em> at level <em>b<\/em>.\n\nWhat happens for other levels of\u00a0<em>A<\/em>? Did you measure for everything that changed, which may have been more than just\u00a0<em>A<\/em>?\n\nLooking back at the studying example, your independent variables of study time and location may affect more than just your test score. For example, they may also affect your homework scores. Could the result simply be due to \"random chance\"?\n<h2><strong><span style=\"color: #1b3b80;\">Hypotheses<\/span><\/strong><\/h2>\nA\u00a0<strong>hypothesis<\/strong>\u00a0is a testable statement that predicts observable phenomena.\u00a0It comprises two parts:\n<ul>\n \t<li>What happens to\u00a0<em>B<\/em>\u00a0when\u00a0<em>A<\/em>\u00a0is changed?<\/li>\n \t<li>What happens to\u00a0<em>B<\/em>\u00a0when\u00a0<em>A<\/em>\u00a0is\u00a0<strong>not<\/strong>\u00a0changed?<\/li>\n<\/ul>\nA famous hypothesis is that objects of different weights fall at the same rate. A hypothesis we can make about studying is that studying longer with peers will improve your test score.\n\nWhen evaluating a hypothesis, it can be accepted (true) or rejected (false).\n\n<strong>Hypotheses give us testable and systematic explanations for observable phenomena and help to focus our attention during testing.<\/strong>\u00a0The knowledge gained from testing a hypothesis provides rigorous support for further experiments and design decisions. The data gained can prove or disprove a hypothesis using statistical analysis.\n\n<strong><span style=\"color: #1b3b80;\">Watch the Video: Test Plan Example<\/span><\/strong>\n\nThe original version of this chapter contained H5P content. You may want to remove or replace this element.\n<h2><span style=\"color: #1b3b80;\"><strong>Three Test Plans and Results:\u00a0 Corn Grinder Prototype Example in ME 2700<\/strong><\/span><\/h2>\nClick on the link below to download and review three examples of test plans and results using the ME 2700 DMADVR toolbox template. The test plan is the first item shown, and scrolling down that same page are the testing results for each of the tabbed tests #1-3. This example is also available Canvas Modules 0 &amp; 00, Module 1 Quiz and Assignments, and Resources.\n\n<a href=\"https:\/\/libraryresources.nse.org.ng\/wp-content\/uploads\/sites\/11\/2022\/01\/Test-Plan-and-Analysis_Examples.xlsx\">Three test plans and results examples<\/a>\n<h2><span style=\"color: #1b3b80;\"><strong>Data Analysis<\/strong><\/span><\/h2>\n<span class=\"tight\">Once the data is collected from the tests, it can be subjected to data analysis. Some common methods of statistical analysis are:<\/span>\n<ul>\n \t<li><span class=\"tight\">Measures of central tendency- mean, median, and mode<\/span><\/li>\n \t<li><span class=\"tight\">Measures of deviation from central tendency- variance, standard deviation<\/span><\/li>\n \t<li><span class=\"tight\">Regression- Fitting models to data, linear, log-linear, log-log, etc.<\/span><\/li>\n<\/ul>\nThe original version of this chapter contained H5P content. You may want to remove or replace this element.","rendered":"<p><strong><span style=\"color: #1b3b80;\">Watch the Interactive Video: Test Planning Overview<\/span><\/strong><\/p>\n<p>The original version of this chapter contained H5P content. You may want to remove or replace this element.<\/p>\n<h2><strong><span style=\"color: #1b3b80;\">Testing Inferences<\/span><\/strong><\/h2>\n<p>Suppose you tested your prototype with independent variable &#8220;A&#8221; at level <em>a<\/em>, and an observed dependent variable &#8220;<em>B&#8221;<\/em> at level <em>b<\/em>.<\/p>\n<p>What happens for other levels of\u00a0<em>A<\/em>? Did you measure for everything that changed, which may have been more than just\u00a0<em>A<\/em>?<\/p>\n<p>Looking back at the studying example, your independent variables of study time and location may affect more than just your test score. For example, they may also affect your homework scores. Could the result simply be due to &#8220;random chance&#8221;?<\/p>\n<h2><strong><span style=\"color: #1b3b80;\">Hypotheses<\/span><\/strong><\/h2>\n<p>A\u00a0<strong>hypothesis<\/strong>\u00a0is a testable statement that predicts observable phenomena.\u00a0It comprises two parts:<\/p>\n<ul>\n<li>What happens to\u00a0<em>B<\/em>\u00a0when\u00a0<em>A<\/em>\u00a0is changed?<\/li>\n<li>What happens to\u00a0<em>B<\/em>\u00a0when\u00a0<em>A<\/em>\u00a0is\u00a0<strong>not<\/strong>\u00a0changed?<\/li>\n<\/ul>\n<p>A famous hypothesis is that objects of different weights fall at the same rate. A hypothesis we can make about studying is that studying longer with peers will improve your test score.<\/p>\n<p>When evaluating a hypothesis, it can be accepted (true) or rejected (false).<\/p>\n<p><strong>Hypotheses give us testable and systematic explanations for observable phenomena and help to focus our attention during testing.<\/strong>\u00a0The knowledge gained from testing a hypothesis provides rigorous support for further experiments and design decisions. The data gained can prove or disprove a hypothesis using statistical analysis.<\/p>\n<p><strong><span style=\"color: #1b3b80;\">Watch the Video: Test Plan Example<\/span><\/strong><\/p>\n<p>The original version of this chapter contained H5P content. You may want to remove or replace this element.<\/p>\n<h2><span style=\"color: #1b3b80;\"><strong>Three Test Plans and Results:\u00a0 Corn Grinder Prototype Example in ME 2700<\/strong><\/span><\/h2>\n<p>Click on the link below to download and review three examples of test plans and results using the ME 2700 DMADVR toolbox template. The test plan is the first item shown, and scrolling down that same page are the testing results for each of the tabbed tests #1-3. This example is also available Canvas Modules 0 &amp; 00, Module 1 Quiz and Assignments, and Resources.<\/p>\n<p><a href=\"https:\/\/libraryresources.nse.org.ng\/wp-content\/uploads\/sites\/11\/2022\/01\/Test-Plan-and-Analysis_Examples.xlsx\">Three test plans and results examples<\/a><\/p>\n<h2><span style=\"color: #1b3b80;\"><strong>Data Analysis<\/strong><\/span><\/h2>\n<p><span class=\"tight\">Once the data is collected from the tests, it can be subjected to data analysis. Some common methods of statistical analysis are:<\/span><\/p>\n<ul>\n<li><span class=\"tight\">Measures of central tendency- mean, median, and mode<\/span><\/li>\n<li><span class=\"tight\">Measures of deviation from central tendency- variance, standard deviation<\/span><\/li>\n<li><span class=\"tight\">Regression- Fitting models to data, linear, log-linear, log-log, etc.<\/span><\/li>\n<\/ul>\n<p>The original version of this chapter contained H5P content. You may want to remove or replace this element.<\/p>\n","protected":false},"author":1,"menu_order":3,"template":"","meta":{"pb_show_title":"","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-152","chapter","type-chapter","status-publish","hentry"],"part":144,"_links":{"self":[{"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/pressbooks\/v2\/chapters\/152","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":1,"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/pressbooks\/v2\/chapters\/152\/revisions"}],"predecessor-version":[{"id":153,"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/pressbooks\/v2\/chapters\/152\/revisions\/153"}],"part":[{"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/pressbooks\/v2\/parts\/144"}],"metadata":[{"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/pressbooks\/v2\/chapters\/152\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/wp\/v2\/media?parent=152"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/pressbooks\/v2\/chapter-type?post=152"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/wp\/v2\/contributor?post=152"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/libraryresources.nse.org.ng\/me270baughman\/wp-json\/wp\/v2\/license?post=152"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}