{"id":166,"date":"2004-07-22T10:04:42","date_gmt":"2004-07-22T10:04:42","guid":{"rendered":"http:\/\/idiolect.truth.posiweb.net\/notes\/?p=166"},"modified":"2004-07-22T10:04:42","modified_gmt":"2004-07-22T10:04:42","slug":"understanding-sampling","status":"publish","type":"post","link":"https:\/\/idiolect.org.uk\/notes\/2004\/07\/22\/understanding-sampling\/","title":{"rendered":"Understanding sampling"},"content":{"rendered":"<p>Thanks to <a href=\"http:\/\/www.jigsawresearch.com.au\/\">Kat<\/a> for this, from <a href=\"http:\/\/www.oztam.com.au\/faq\/#erwin\">oztam.com<\/a><\/p>\n<blockquote><p><i>People ? often do not have a good sense of the limitations of sample-based research. Warren Cordell, chief statistical officer at Nielsen for many years, devised a wonderful visual explanation for [the United States] Congress, which went as follows. The picture (below) is comprised of several hundred thousand tiny dots (the population).<\/p>\n<p align=\"center\"><img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/www.idiolect.org.uk\/docs\/jul04\/pic.gif?w=580\"><\/p>\n<p>The three smaller pictures contain 250, 1,000 and 2,000 dots (the samples). They are &#8216;area probability&#8217; samples of the original picture, because the dots are distributed in proportion to their distribution in the picture. If we think of homes [or persons, consumers] instead of dots, this is the sampling method used for most media research studies.<\/p>\n<table width=\"100%\" border=\"0\">\n<tr>\n<td><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/www.idiolect.org.uk\/docs\/jul04\/coarse.gif?resize=200%2C200\" width=\"200\" height=\"200\"><\/td>\n<td><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/www.idiolect.org.uk\/docs\/jul04\/medium.gif?resize=200%2C200\" width=\"200\" height=\"200\"><\/td>\n<td><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/www.idiolect.org.uk\/docs\/jul04\/fine.gif?resize=200%2C200\" width=\"200\" height=\"200\"><\/td>\n<\/tr>\n<\/table>\n<p>Now move back 30 inches or so. When the eye stops trying to read the dots, even the smallest sample provides a recognisable picture (you can use top-line data). But you would have trouble picking her out of a group of women based on the 250-dot sample (do not try reading demographic breaks). At 1,000 dots, if you squint to read the pattern of light and dark, you would recognise her in a group (now you can read major demographics). At 2,000 dots, you see her more clearly &#8211; but the real improvement is between 250 and 1,000 &#8211; an important point. In sampling, the ability to see greater detail is a &#8216;squared function&#8217; &#8211; it takes four times as large a sample to see twice the detail. This is the strength and weakness of sample-based research. You get the general picture cheap, but precision costs a bundle.<\/i><\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>Thanks to Kat for this, from oztam.com People ? often do not have a good sense of the limitations of sample-based research. Warren Cordell, chief statistical officer at Nielsen for many years, devised a wonderful visual explanation for [the United States] Congress, which went as follows. The picture (below) is comprised of several hundred thousand [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false},"version":2}},"categories":[9],"tags":[],"class_list":["post-166","post","type-post","status-publish","format-standard","hentry","category-science"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p5KQtW-2G","jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/posts\/166"}],"collection":[{"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/comments?post=166"}],"version-history":[{"count":0,"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/posts\/166\/revisions"}],"wp:attachment":[{"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/media?parent=166"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/categories?post=166"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/idiolect.org.uk\/notes\/wp-json\/wp\/v2\/tags?post=166"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}