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1.1
date	2018.03.14.16.38.53;	author root;	state Exp;
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@This document (4.1 introduction) is re-created by administrator on 29 July 2017
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1.1
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@Initial revision
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    "content": "<div id=\"scstyle\">\r\n<style scoped=\"\" type=\"text/css\">@@import \"/static/ndf/css/clix-activity-styles.css\";\r\n@@import \"/static/ndf/css/rubik-font.css\";\r\n@@import \"/static/ndf/css/sgc-toc.css\";\r\n@@import \"/static/ndf/css/video-js.css\";\r\n@@import \"/static/ndf/css/videojs-skin-color\";\r\n</style>\r\n<script src=\"/static/ndf/js/jquery-3.0.0.min.js\" type=\"text/javascript\"></script><script src=\"/static/ndf/js/Video.js\" type=\"text/javascript\"></script><script src=\"/static/ndf/js/photo-zoom.js\" type=\"text/javascript\"></script>\r\n<div class=\"row\">\r\n<header class=\"medium-10 columns\">\r\n<h1>Finding patterns in data: simulation tutorial</h1>\r\n\r\n<hr /></header>\r\n\r\n<main class=\"medium-8 large-centered columns\" style=\"float: left;\">\r\n<p class=\"sigil_not_in_toc\"><span style=\"font-size:20px;\">Data is a way of trying to understand the world, we can observe it and try to see if there are any meaningful patterns.&nbsp;<br />\r\n<br />\r\nPublic health officials are especially interested in disease patterns in a populations. Patterns help us predict who might get sick, possibly help prevent some diseases or target treatment for certain diseases.<br />\r\n<br />\r\nFor example, if public health experts observe a pattern in which people who live in areas which get flooded often tend to get malaria, they might focus providing mosquito nets to those people since they are closer to mosquitos.<br />\r\n<br />\r\nWhy are some people at greater risk of getting sick than others? We can answer questions like this by exploring data. Data lets us see patterns. These patterns might not be obvious without looking at the data. Today, we will be using a computer model to investigate a group of people.&nbsp;<br />\r\n<br />\r\nIn this model, each circle represents a person. So if there are 20 circles, there are 20 people in our dataset.</span><br />\r\n<br />\r\n<img alt=\"anemia1\" src=\"/media/8/e/d/81fc56a30883886d3c5df14f3dce7a2b6435fa4214a9e6179ca59ebb81fb3.png\" style=\"width: 640px; height: 280px;\" /><br />\r\n&nbsp;</p>\r\n\r\n<p class=\"small-block-grid-1\"><span style=\"font-size:20px;\">Anemia is a serious disease. Many people in our country suffer from anemia. It can be caused by deficiency of Iron in blood.&nbsp;<br />\r\nIn our model, each person is either anemic (a yellow circle) or not anemic (a magenta circle).</span><br />\r\n<br />\r\n<img 2=\"\" alt=\"anemia\" src=\"/media/7/a/6/a14f514206bff6028f83f3559675cecf9294545b2376e11b94fcbd148da1d.png\" style=\"width: 640px; height: 280px;\" /><br />\r\n<br />\r\n<span style=\"font-size:20px;\">The people in our data set have other traits as well. For example, in addition to being anemic or not anemic, each person is ALSO either male or female. In order to \u201csee\u201d each person\u2019s gender, we need to sort them. In this screenshot, males are grouped on the left and females are grouped on the right.&nbsp;\u200b</span><br />\r\n<img 3=\"\" alt=\"anaemia\" height=\"175\" src=\"/media/b/5/6/291b014c7b4af74d2a4d8c4ea66af210d66acd6216db7de552d08bce94af4.png\" width=\"640\" /><br />\r\n<br />\r\n&nbsp;</p>\r\n</main>\r\n</div>\r\n</div>\r\n\r\n<p>&nbsp;</p>\r\n",
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