{"id":48524,"date":"2025-11-19T14:09:31","date_gmt":"2025-11-19T14:09:31","guid":{"rendered":"https:\/\/certifeka-edu.com\/programs\/research-for-strategic-development-professional-certificate-3\/lessons\/lesson-2-3-shades-of-data-accuracy-3\/"},"modified":"2025-11-19T14:09:31","modified_gmt":"2025-11-19T14:09:31","slug":"lesson-2-3-shades-of-data-accuracy-3","status":"publish","type":"lesson","link":"https:\/\/certifeka-edu.com\/ar\/programs\/research-for-strategic-development-module\/lessons\/lesson-2-3-shades-of-data-accuracy-3\/","title":{"rendered":"Lesson 2: 3 Shades of Data Accuracy"},"content":{"rendered":"<p><img loading=\"lazy\" decoding=\"async\" width=\"96\" height=\"114\" src=\"https:\/\/certifeka-edu.com\/wp-content\/uploads\/2025\/04\/logos-png-01-296x57-1.png\" alt=\"\" srcset=\"https:\/\/certifeka-edu.com\/wp-content\/uploads\/2025\/04\/logos-png-01-296x57-1.png 96w, https:\/\/certifeka-edu.com\/wp-content\/uploads\/2025\/04\/logos-png-01-296x57-1-10x12.png 10w, https:\/\/certifeka-edu.com\/wp-content\/uploads\/2025\/04\/logos-png-01-296x57-1-42x50.png 42w\" sizes=\"auto, (max-width: 96px) 100vw, 96px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/p>\n<h2>Lesson 2: Data Quality testing &amp; Data types<\/h2>\n<h3>3 Shades of Data Accuracy<\/h3>\n<h3>Type 1: Absolute Accuracy:<\/h3>\n<h5>This refers to data that is 100% accurate and without any errors. It is the highest level of accuracy and is often difficult to achieve, especially with large datasets.<\/h5>\n<h5>Here are some examples to help understand absolute accuracy:<\/h5>\n<details id=\"e-n-accordion-item-2270\" open>\n<summary data-accordion-index=\"1\" tabindex=\"0\" aria-expanded=\"true\" aria-controls=\"e-n-accordion-item-2270\" >\n\t\t\t\t\t Measurement of physical constants<br \/>\n\t\t\t<svg aria-hidden=\"true\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><br \/>\n\t\t\t<svg aria-hidden=\"true\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><br \/>\n\t\t\t\t\t\t<\/summary>\n<h5>\u00a0In science, certain physical constants such as the speed of light or gravitational constant are considered to be known with absolute accuracy. The values of these constants are derived from rigorous measurements and are universally accepted.<\/h5>\n<\/details>\n<details id=\"e-n-accordion-item-2271\" >\n<summary data-accordion-index=\"2\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2271\" >\n\t\t\t\t\t DNA sequencing<br \/>\n\t\t\t<svg aria-hidden=\"true\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><br \/>\n\t\t\t<svg aria-hidden=\"true\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><br \/>\n\t\t\t\t\t\t<\/summary>\n<h5><font color=\"#000080\">In genetic research, DNA sequencing is a technique used to determine the exact order of nucleotides in a DNA molecule. When sequencing is done with a high level of precision and accuracy, it can be considered to be approaching absolute accuracy.<\/font><\/h5>\n<\/details>\n<h5>\u00a0In science, certain physical constants such as the speed of light or gravitational constant are considered to be known with absolute accuracy. The values of these constants are derived from rigorous measurements and are universally accepted.<\/h5>\n<h5><font color=\"#000080\">In genetic research, DNA sequencing is a technique used to determine the exact order of nucleotides in a DNA molecule. When sequencing is done with a high level of precision and accuracy, it can be considered to be approaching absolute accuracy.<\/font><\/h5>\n<h3>Type 2: Relative Accuracy<br \/>\n<\/h3>\n<h5>This refers to data that is accurate within a certain range or margin of error. This level of accuracy is often used in surveys or experiments where there may be some variability in the data.<\/h5>\n<h5>This level of accuracy is often used in surveys or experiments where there may be some variability in the data due to factors such as sampling error or measurement error.<\/h5>\n<h5>For example, let&#8217;s say a researcher is conducting a survey on the satisfaction level of customers in a particular store.<\/h5>\n<h5>\u00a0<\/h5>\n<h5>The researcher collects data from a sample of 500 customers and finds that 70% of them are satisfied with their shopping experience.<\/h5>\n<h5>\u00a0<\/h5>\n<h5>However, the margin of error is \u00b1 5%, meaning that the actual satisfaction level in the population could be as low as 65% or as high as 75%. In this case, the data is relatively accurate but not 100% accurate.<\/h5>\n<p>\u00a0\t\t<\/p>\n<h3>Type 3: Apparent Accuracy:<br \/>\n<\/h3>\n<h5>This refers to data that appears to be accurate but may not be. This can happen when data is incomplete, outdated, or biased. It is important to be aware of the potential for apparent accuracy and to take steps to ensure that data is as accurate as possible.<\/h5>\n<h5>Here are some examples of how apparent accuracy can be misleading:<\/h5>\n<details id=\"e-n-accordion-item-2420\" open>\n<summary data-accordion-index=\"1\" tabindex=\"0\" aria-expanded=\"true\" aria-controls=\"e-n-accordion-item-2420\" >\n\t\t\t\t\t  Incomplete Data<br \/>\n\t\t\t<svg aria-hidden=\"true\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><br \/>\n\t\t\t<svg aria-hidden=\"true\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><br \/>\n\t\t\t\t\t\t<\/summary>\n<h5>Apparent accuracy can result from incomplete data that does not provide a complete picture of a situation. For instance, if a company only surveys their most satisfied customers, they may get positive feedback that makes it appear as if they are doing well. However, if they don&#8217;t also survey dissatisfied customers, they may not get a complete picture of what is actually going on with their product or service.<\/h5>\n<\/details>\n<details id=\"e-n-accordion-item-2421\" >\n<summary data-accordion-index=\"2\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2421\" >\n\t\t\t\t\t Biased Data<br \/>\n\t\t\t<svg aria-hidden=\"true\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><br \/>\n\t\t\t<svg aria-hidden=\"true\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><br \/>\n\t\t\t\t\t\t<\/summary>\n<h5>Apparent accuracy can also result from biased data that is skewed towards a certain perspective or agenda. For instance, if a pharmaceutical company funds a study on the effectiveness of their drug, there may be a bias towards positive results that support the company&#8217;s interests.<\/h5>\n<\/details>\n<h5>Apparent accuracy can result from incomplete data that does not provide a complete picture of a situation. For instance, if a company only surveys their most satisfied customers, they may get positive feedback that makes it appear as if they are doing well. However, if they don&#8217;t also survey dissatisfied customers, they may not get a complete picture of what is actually going on with their product or service.<\/h5>\n<h5>Apparent accuracy can also result from biased data that is skewed towards a certain perspective or agenda. For instance, if a pharmaceutical company funds a study on the effectiveness of their drug, there may be a bias towards positive results that support the company&#8217;s interests.<\/h5>","protected":false},"comment_status":"open","ping_status":"closed","template":"","class_list":["post-48524","lesson","type-lesson","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Lesson 2: 3 Shades of Data Accuracy - Certifeka-edu<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/certifeka-edu.com\/ar\/programs\/research-for-strategic-development-module\/lessons\/lesson-2-3-shades-of-data-accuracy-3\/\" \/>\n<meta property=\"og:locale\" content=\"ar_AR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Lesson 2: 3 Shades of Data Accuracy - Certifeka-edu\" \/>\n<meta property=\"og:description\" content=\"Lesson 2: Data Quality testing &amp; Data types 3 Shades of Data Accuracy Type 1: Absolute Accuracy: This refers to data that is 100% accurate and without any errors. 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