{"id":1869,"date":"2008-09-04T15:34:04","date_gmt":"2008-09-04T22:34:04","guid":{"rendered":""},"modified":"2020-03-18T10:45:33","modified_gmt":"2020-03-18T17:45:33","slug":"1869","status":"publish","type":"post","link":"https:\/\/www.vernier.com\/til\/1869","title":{"rendered":"How do you calculate linear fits in Logger <i>Pro<\/i>?"},"content":{"rendered":"<p>Logger <i>Pro<\/i> calculates the &#8220;best fit&#8221; line on graphs by using linear regression by the method of least squares. The equations used are linked below.<\/p>\n<p><strong>Note:<\/strong> This PDF document ensures that superscipts and subscripts are not lost.<\/p>\n<p><a href=\"http:\/\/www2.vernier.com\/til\/1869\/logger_pro_linear_fits.pdf\">http:\/\/www2.vernier.com\/til\/1869\/logger_pro_linear_fits.pdf<\/a><\/p>\n<p>This document also explains how the correlation coefficient of the regression line and the uncertainties of the slope and intercept are determined.<\/p>\n<p>These are fairly standard formulas. The correlation coefficient of the regression line is a useful measure of how well the data fits a straight line, but it should not be overused. Always examine the graph. The coefficient is greatly affected by a few extreme points.<\/p>\n<p>Refer to a statistics text for more information; for example, <em>An Introduction to Error Analysis<\/em> by John R. Taylor, Oxford University Press, 1982.<\/p>","protected":false},"excerpt":{"rendered":"<p>Logger Pro calculates the &#8220;best fit&#8221; line on graphs by using linear regression by the method of least squares. The equations used are linked below&#8230;.<\/p>\n","protected":false},"author":9585,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[],"tags":[2885,2879,2878,2884,2397,2882,2191,84,382,2880,2881,2883],"class_list":["post-1869","post","type-post","status-publish","format-standard","hentry","tag-correlation","tag-curve-fir","tag-fit","tag-intercept","tag-labquest","tag-least-squares","tag-linear","tag-logger-pro","tag-loggerpro","tag-regression","tag-regression-line","tag-slope"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/posts\/1869","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/users\/9585"}],"replies":[{"embeddable":true,"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/comments?post=1869"}],"version-history":[{"count":0,"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/posts\/1869\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/media?parent=1869"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/categories?post=1869"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.vernier.com\/til\/wp-json\/wp\/v2\/tags?post=1869"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}