{"id":3942,"date":"2024-05-15T07:07:45","date_gmt":"2024-05-15T07:07:45","guid":{"rendered":"https:\/\/interfinance.tsue.uz\/?p=3942"},"modified":"2024-05-15T07:15:46","modified_gmt":"2024-05-15T07:15:46","slug":"bootstrap-standard-errors-and-intervals-under-different-sample-size-in-ols","status":"publish","type":"post","link":"https:\/\/interfinance.tsue.uz\/?p=3942","title":{"rendered":"BOOTSTRAP STANDARD ERRORS AND INTERVALS UNDER DIFFERENT SAMPLE SIZE IN OLS"},"content":{"rendered":"<p style=\"text-align: center;\"><strong><em>Zarrukh Rakhimov,<\/em><\/strong><\/p>\n<p style=\"text-align: center;\"><em>PhD candidate in Econometrics and Statistics<\/em><\/p>\n<p style=\"text-align: center;\"><em>Email: <a href=\"mailto:zrakhimov@wiut.uz\">zrakhimov@wiut.uz<\/a> <\/em><\/p>\n<p style=\"text-align: center;\"><em>Westminster International University in Tashkent<\/em><\/p>\n<p style=\"text-align: center;\"><em>Istiqbol str. 12, 100047 Tashkent, Uzbekistan<\/em><\/p>\n<p style=\"text-align: center;\"><em>ORCID:\u00a0 0009-0001-0583-4819<\/em><\/p>\n<p><strong><em>Abstract:<\/em><\/strong><em> Linear regression is one of the widely used statistical methods in social sciences. The core part of the regressions are coefficients, which bring some inference. Yet, we rely on hypothesis testing or confidence intervals and certain assumptions underlying linear models such as sample size being large enough. In this study, we suggest alternative way of constructing confidence intervals using bootstrap, which is expected to work well even when the sample size is smaller than required per OLS assumptions. We find that even in small samples, bootstrap confidence intervals can perform better than traditional interval estimations due to larger interval size<\/em><\/p>\n<p><strong><em>Keywords:<\/em><\/strong><em> sample size, linear model, confidence Interval, bootstrap, accuracy, interval size<\/em><\/p>\n\n\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/interfinance.tsue.uz\/wp-content\/uploads\/2024\/05\/article_32.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of article_32.\"><\/object><a id=\"wp-block-file--media-a0b192f1-2966-4fcd-9c9f-9e4663f0d314\" href=\"https:\/\/interfinance.tsue.uz\/wp-content\/uploads\/2024\/05\/article_32.pdf\">article_32<\/a><a href=\"https:\/\/interfinance.tsue.uz\/wp-content\/uploads\/2024\/05\/article_32.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-a0b192f1-2966-4fcd-9c9f-9e4663f0d314\">Download<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Zarrukh Rakhimov, PhD candidate in Econometrics and Statistics Email: zrakhimov@wiut.uz Westminster International University in Tashkent Istiqbol str. 12, 100047 Tashkent, Uzbekistan ORCID:\u00a0 0009-0001-0583-4819 Abstract: Linear regression is one of the widely used statistical methods in social sciences. The core part <a href=\"https:\/\/interfinance.tsue.uz\/?p=3942\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62],"tags":[],"class_list":["post-3942","post","type-post","status-publish","format-standard","hentry","category-2024-2-issue-1-6"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>BOOTSTRAP STANDARD ERRORS AND INTERVALS UNDER DIFFERENT SAMPLE SIZE IN OLS - Journal of International Finance and Accounting<\/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:\/\/interfinance.tsue.uz\/?p=3942\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"BOOTSTRAP STANDARD ERRORS AND INTERVALS UNDER DIFFERENT SAMPLE SIZE IN OLS - Journal of International Finance and Accounting\" \/>\n<meta property=\"og:description\" content=\"Zarrukh Rakhimov, PhD candidate in Econometrics and Statistics Email: zrakhimov@wiut.uz Westminster International University in Tashkent Istiqbol str. 12, 100047 Tashkent, Uzbekistan ORCID:\u00a0 0009-0001-0583-4819 Abstract: Linear regression is one of the widely used statistical methods in social sciences. 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