{"id":56563,"date":"2025-01-30T00:15:34","date_gmt":"2025-01-30T00:15:34","guid":{"rendered":"https:\/\/peraltafinancing.com\/agriculture\/spearman-rank-correlation-analysis-using-agri-analyze\/"},"modified":"2025-01-30T00:15:34","modified_gmt":"2025-01-30T00:15:34","slug":"spearman-rank-correlation-analysis-using-agri-analyze","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=56563","title":{"rendered":"Spearman Rank Correlation Analysis using Agri Analyze"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div id=\"post-body-8607996075272367444\">\n<p style=\"text-align: justify;\"><i>\u00a0The blog is about Spearman Rank Correlation theory, when to use, calculation along with formulas, testing its significance, solved example and step by step guide for Agri Analyze (Reading time 10 mins)\u00a0<\/i><\/p>\n<p><b>Correlation<\/b> is a statistical measure that quantifies the strength and direction of the relationship between two variables. For example, it can be used to assess whether there is a connection between the heights of fathers and their sons.\u00a0<\/p>\n<p>There are two primary types of correlation analysis:<\/p>\n<ul style=\"text-align: left;\">\n<li style=\"text-align: justify;\"><b>Parametric Correlation:<\/b> This method, often using Pearson&#8217;s correlation coefficient (r), measures the linear relationship between numerical variables. It assumes a specific distribution of the data.<\/li>\n<li style=\"text-align: justify;\"><b>Non-Parametric Correlation:<\/b> Employing techniques like Kendall&#8217;s tau or Spearman&#8217;s rho, these methods analyze the relationship between variables based on their ranks rather than their actual values. They are suitable for categorical data or ordinal (rank) data and do not require assumptions about data distribution.<\/li>\n<\/ul>\n<div style=\"text-align: justify;\">\n<p class=\"MsoNormal\" style=\"line-height: 150%; margin-bottom: 0in; text-indent: 0.5in;\"><span lang=\"EN-US\" style=\"font-family: &quot;Times New Roman&quot;,serif; font-size: 12pt; line-height: 150%;\">One of the key assumptions in<br \/>\ncorrelation analysis is that both variables being studied are normally<br \/>\ndistributed. If at least one of the variables follows a normal distribution,<br \/>\nlinear correlation can still be used. However, if neither variable is normally<br \/>\ndistributed, the linear correlation method is not appropriate. In such<br \/>\nsituations, rank correlation should be utilized instead.<\/span><\/p>\n<p class=\"MsoNormal\" style=\"line-height: 150%; margin-bottom: 0in; text-indent: 0.5in;\"><span lang=\"EN-US\" style=\"font-family: &quot;Times New Roman&quot;,serif; font-size: 12pt; line-height: 150%;\">There are two distinct methods for<br \/>\ncomputing rank correlation: Spearman&#8217;s rank correlation and Kendall&#8217;s tau. Both<br \/>\nmethods can be applied to the same dataset. Numerically, Spearman&#8217;s rank<br \/>\ncorrelation typically yields higher values than Kendall&#8217;s tau. However, both<br \/>\nmethods generally produce nearly identical inferences, so there is no<br \/>\ncompelling reason to favor one over the other. Spearman&#8217;s rank correlation is<br \/>\nmore widely used due to its computational simplicity. <\/span><\/p>\n<p class=\"MsoNormal\" style=\"line-height: 150%; margin-bottom: 0in; text-indent: 0.5in;\"><span lang=\"EN-US\" style=\"font-family: &quot;Times New Roman&quot;,serif; font-size: 12pt; line-height: 150%;\">Spearman&#8217;s rank correlation is<br \/>\nsometimes called <\/span><!--[if gte msEquation 12]><m:oMath><span lang=EN-US\n style=\"font-size:12.0pt;line-height:150%;font-family:\"Cambria Math\",serif;\n mso-bidi-font-family:\"Times New Roman\"\"><m:r><m:rPr><m:scr m:val=\"roman\"\/><m:sty\n    m:val=\"p\"\/><\/m:rPr>&rho;<\/m:r><\/span><\/m:oMath><![endif]--><!--[if !msEquation]--><span face=\"&quot;Aptos&quot;,sans-serif\" lang=\"EN-US\" style=\"font-size: 11pt; line-height: 107%; mso-ansi-language: EN-US; mso-ascii-theme-font: minor-latin; mso-bidi-font-family: &quot;Times New Roman&quot;; mso-bidi-language: AR-SA; mso-bidi-theme-font: minor-bidi; mso-fareast-font-family: Aptos; mso-fareast-language: EN-US; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-text-raise: -4.0pt; position: relative; top: 4pt;\"><shapetype coordsize=\"21600,21600\" filled=\"f\" id=\"_x0000_t75\" o:preferrelative=\"t\" o:spt=\"75\" path=\"m@4@5l@4@11@9@11@9@5xe\" stroked=\"f\"><br \/>\n <stroke joinstyle=\"miter\"><br \/>\n <formulas>\n  <f eqn=\"if lineDrawn pixelLineWidth 0\"><br \/>\n  <f eqn=\"sum @0 1 0\"><br \/>\n  <f eqn=\"sum 0 0 @1\"><br \/>\n  <f eqn=\"prod @2 1 2\"><br \/>\n  <f eqn=\"prod @3 21600 pixelWidth\"><br \/>\n  <f eqn=\"prod @3 21600 pixelHeight\"><br \/>\n  <f eqn=\"sum @0 0 1\"><br \/>\n  <f eqn=\"prod @6 1 2\"><br \/>\n  <f eqn=\"prod @7 21600 pixelWidth\"><br \/>\n  <f eqn=\"sum @8 21600 0\"><br \/>\n  <f eqn=\"prod @7 21600 pixelHeight\"><br \/>\n  <f eqn=\"sum @10 21600 0\"><br \/>\n <\/f><\/f><\/f><\/f><\/f><\/f><\/f><\/f><\/f><\/f><\/f><\/f><\/formulas>\n <path gradientshapeok=\"t\" o:connecttype=\"rect\" o:extrusionok=\"f\">\n <lock aspectratio=\"t\" v:ext=\"edit\"><br \/>\n<\/lock><\/path><\/stroke><\/shapetype><shape id=\"_x0000_i1025\" style=\"height: 15pt; width: 6.6pt;\" type=\"#_x0000_t75\"><br \/>\n <imagedata chromakey=\"white\" o:title=\"\" src=\"https:\/\/agriculturalstatistic.blogspot.com\/2024\/07\/file:\/\/\/C:\/Users\/raj\/AppData\/Local\/Temp\/msohtmlclip1\/01\/clip_image001.png\"><br \/>\n<\/imagedata><\/shape><\/span><!--[endif]--><span lang=\"EN-US\" style=\"font-family: &quot;Times New Roman&quot;,serif; font-size: 12pt; line-height: 150%;\">. In order to avoid confusion with<br \/>\nthe population correlation coefficient <\/span><!--[if gte msEquation 12]><m:oMath><span\n lang=EN-US style=\"font-size:12.0pt;line-height:150%;font-family:\"Cambria Math\",serif;\n mso-bidi-font-family:\"Times New Roman\"\"><m:r><m:rPr><m:scr m:val=\"roman\"\/><m:sty\n    m:val=\"p\"\/><\/m:rPr>&rho;<\/m:r><\/span><\/m:oMath><![endif]--><!--[if !msEquation]--><span face=\"&quot;Aptos&quot;,sans-serif\" lang=\"EN-US\" style=\"font-size: 11pt; line-height: 107%; mso-ansi-language: EN-US; mso-ascii-theme-font: minor-latin; mso-bidi-font-family: &quot;Times New Roman&quot;; mso-bidi-language: AR-SA; mso-bidi-theme-font: minor-bidi; mso-fareast-font-family: Aptos; mso-fareast-language: EN-US; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-text-raise: -4.0pt; position: relative; top: 4pt;\"><shape id=\"_x0000_i1025\" style=\"height: 15pt; width: 6.6pt;\" type=\"#_x0000_t75\"><br \/>\n <imagedata chromakey=\"white\" o:title=\"\" src=\"https:\/\/agriculturalstatistic.blogspot.com\/2024\/07\/file:\/\/\/C:\/Users\/raj\/AppData\/Local\/Temp\/msohtmlclip1\/01\/clip_image001.png\"><br \/>\n<\/imagedata><\/shape><\/span><!--[endif]--><span lang=\"EN-US\" style=\"font-family: &quot;Times New Roman&quot;,serif; font-size: 12pt; line-height: 150%;\">, the notation<\/span><span lang=\"EN-US\" style=\"font-family: &quot;Times New Roman&quot;,serif; font-size: 12pt; line-height: 150%; mso-fareast-font-family: &quot;Times New Roman&quot;; mso-fareast-theme-font: minor-fareast;\"><br \/>\n<\/span><!--[if gte msEquation 12]><m:oMath><m:sSub><m:sSubPr><span\n   style=\"font-size:12.0pt;mso-ansi-font-size:12.0pt;mso-bidi-font-size:12.0pt;\n   font-family:\"Cambria Math\",serif;mso-ascii-font-family:\"Cambria Math\";\n   mso-hansi-font-family:\"Cambria Math\";mso-bidi-font-family:\"Times New Roman\";\n   mso-bidi-font-style:italic\"><m:ctrlPr><\/m:ctrlPr><\/span><\/m:sSubPr><m:e><span\n   lang=EN-US style=\"font-size:12.0pt;line-height:150%;font-family:\"Cambria Math\",serif;\n   mso-bidi-font-family:\"Times New Roman\"\"><m:r><m:rPr><m:scr m:val=\"roman\"\/><m:sty\n      m:val=\"p\"\/><\/m:rPr>r<\/m:r><\/span><\/m:e><m:sub><span lang=EN-US\n   style=\"font-size:12.0pt;line-height:150%;font-family:\"Cambria Math\",serif;\n   mso-bidi-font-family:\"Times New Roman\"\"><m:r><m:rPr><m:scr m:val=\"roman\"\/><m:sty\n      m:val=\"p\"\/><\/m:rPr>s<\/m:r><\/span><\/m:sub><\/m:sSub><\/m:oMath><![endif]--><!--[if !msEquation]--><span face=\"&quot;Aptos&quot;,sans-serif\" lang=\"EN-US\" style=\"font-size: 11pt; line-height: 107%; mso-ansi-language: EN-US; mso-ascii-theme-font: minor-latin; mso-bidi-font-family: &quot;Times New Roman&quot;; mso-bidi-language: AR-SA; mso-bidi-theme-font: minor-bidi; mso-fareast-font-family: Aptos; mso-fareast-language: EN-US; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-text-raise: -4.0pt; position: relative; top: 4pt;\"><shape id=\"_x0000_i1025\" style=\"height: 15pt; width: 9.6pt;\" type=\"#_x0000_t75\"><br \/>\n <imagedata chromakey=\"white\" o:title=\"\" src=\"https:\/\/agriculturalstatistic.blogspot.com\/2024\/07\/file:\/\/\/C:\/Users\/raj\/AppData\/Local\/Temp\/msohtmlclip1\/01\/clip_image002.png\"><br \/>\n<\/imagedata><\/shape><\/span><!--[endif]--><span lang=\"EN-US\" style=\"font-family: &quot;Times New Roman&quot;,serif; font-size: 12pt; line-height: 150%;\">, is used to represent Spearman&#8217;s<br \/>\ncorrelation coefficient.\u00a0<\/span><span style=\"font-family: &quot;Times New Roman&quot;, serif; font-size: 12pt; text-indent: 0.5in;\">Spearman&#8217;s rank correlation procedure<br \/>\nstarts with ranking of the measurements of the variable X and Y separately. The<br \/>\ndifferences between the ranks of each of n pairs are then found out. They are<br \/>\ndenoted by d. The Spearman&#8217;s rank correlation is then computed by using the<br \/>\nformula:<\/span><\/p>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEjCg6EsFjliQMn3qMY2jS0A3ZbrMu24JSoAk3YbBoIgy2YUj67rk4WJ2RfRsLkKTHwCnACd_B2r-vM4NH5PgZxz3-zcr0koWebrjd5A6yM44P9m58OVjjA2ixBrLd1MvTV-C0fsqsYX-RCUm63NmHOmLEuQ1dwW8Ju3xgcnZSqaO9TkfB8DoREzBeLlDRM\/s685\/Spearman_rank_correlation1.png\" style=\"clear: left; float: left; margin-bottom: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"352\" data-original-width=\"685\" height=\"328\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEjCg6EsFjliQMn3qMY2jS0A3ZbrMu24JSoAk3YbBoIgy2YUj67rk4WJ2RfRsLkKTHwCnACd_B2r-vM4NH5PgZxz3-zcr0koWebrjd5A6yM44P9m58OVjjA2ixBrLd1MvTV-C0fsqsYX-RCUm63NmHOmLEuQ1dwW8Ju3xgcnZSqaO9TkfB8DoREzBeLlDRM\/w640-h328\/Spearman_rank_correlation1.png\" width=\"640\"\/><\/a><\/div>\n<p><\/div>\n<div style=\"text-align: justify;\">\n<p><b>Testing the Significance of the Correlation Coefficient: A Step-by-Step Guide<\/b><\/p>\n<p>To test the significance of the correlation coefficient, typically perform a hypothesis test to determine whether the observed correlation is statistically significant. The steps for testing the significance of the correlation coefficient r are as follows:<\/p>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEi3uf_GcVi5WtFiKbrdgGyBaJQSFnuFsDASz_9EJHMfkx-1Fv3uEXS0fPdCxz5XwcJcSPoN9hi9JqX-OtjbvOh_7p1YEYrO1tKg9PgHhrikkE5fQIEioHO77k1sJ8Yt7I1uyNhi4Qz79aZJts2B2O9aVE6Ab3kivo5IhiHiyI6H41YSUbZyMyHFciwZ9tA\/s705\/correlation_diagram4.png\" style=\"margin-left: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"662\" data-original-width=\"705\" height=\"600\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEi3uf_GcVi5WtFiKbrdgGyBaJQSFnuFsDASz_9EJHMfkx-1Fv3uEXS0fPdCxz5XwcJcSPoN9hi9JqX-OtjbvOh_7p1YEYrO1tKg9PgHhrikkE5fQIEioHO77k1sJ8Yt7I1uyNhi4Qz79aZJts2B2O9aVE6Ab3kivo5IhiHiyI6H41YSUbZyMyHFciwZ9tA\/w640-h600\/correlation_diagram4.png\" width=\"640\"\/><\/a><\/div>\n<p><b>Solved example of Spearman Rank Correlation<\/b><\/p>\n<div>\n<p>Problem statement: There are two variables X and Y each having 5 observations. Compute the Spearman rank correlation and also test its significance using t test. The data is shared below:<\/p>\n<p>X: 10, 20, 30, 40, 50\u00a0 and Y: 20, 25, 15, 35, 30<\/p>\n<\/div>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEjz7clhNwSTVBLDwSjQJFQ45Tu_IZ1ni_Ml4bKhDiLIoabqWusJx85_CfiDtUNR8QNxtU0-lBmf1pO4GQUOWYK835jSndle0Cn42JAszuu45Uzy9Pnx_2poIgjI-rrZ5LmgWJ_XSFIujndS-5uQyDJFaBUys42TyMiW07KxQGL_hrriFqNhHemJ11tkW4k\/s832\/Spearman_rank_correlation2.png\" style=\"margin-left: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"702\" data-original-width=\"832\" height=\"540\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEjz7clhNwSTVBLDwSjQJFQ45Tu_IZ1ni_Ml4bKhDiLIoabqWusJx85_CfiDtUNR8QNxtU0-lBmf1pO4GQUOWYK835jSndle0Cn42JAszuu45Uzy9Pnx_2poIgjI-rrZ5LmgWJ_XSFIujndS-5uQyDJFaBUys42TyMiW07KxQGL_hrriFqNhHemJ11tkW4k\/w640-h540\/Spearman_rank_correlation2.png\" width=\"640\"\/><\/a><\/div>\n<p><\/p>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEhhJFFWeTBe5mv_v76RiJcmiTb5KeyP32m8IS8ULuBB2Wca0qbx2jIqYDs7NxZqxKtU_A5-9nGRK90kRi-dp-uyZWLc34ubORr84EHl12mjI6B4AB5j0gDI6TB8gm6IfFI2SsFPSkAKLfcSraJlMYRxi2lRDlv-tR5KV8jPAUZ4kYRsYJ0IK2bpE0M390U\/s740\/Testing%20Significnace.png\" style=\"margin-left: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"711\" data-original-width=\"740\" height=\"614\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEhhJFFWeTBe5mv_v76RiJcmiTb5KeyP32m8IS8ULuBB2Wca0qbx2jIqYDs7NxZqxKtU_A5-9nGRK90kRi-dp-uyZWLc34ubORr84EHl12mjI6B4AB5j0gDI6TB8gm6IfFI2SsFPSkAKLfcSraJlMYRxi2lRDlv-tR5KV8jPAUZ4kYRsYJ0IK2bpE0M390U\/w640-h614\/Testing%20Significnace.png\" width=\"640\"\/><\/a><\/div>\n<p><b>Steps to perform Spearman Rank Correlation in Agri Analyze:<\/b><\/p>\n<\/div>\n<p>Dataset consists of 5 variables. Each has 18 observations. The snip of the dataset is shared below:<\/p>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEjd57KLKea4rfbbgGu83URWzdOT6I2uM3Wf5CUYUGpjhxndBKCTFrgUzKW7mbESLJM0K6KBms8JbFWKK8ZwqTpfWqt3w5LllI6x5i9vypsH6uBgVD22nUWmRGK5eXxmWZJoz7zLzuLnJeVQDr5_gjADMwYKIF6l72uJVtSxNS33SUNwPWg_BLLf9BFBR5M\/s678\/Spearman_rank_correlation3.png\" style=\"margin-left: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"678\" data-original-width=\"610\" height=\"640\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEjd57KLKea4rfbbgGu83URWzdOT6I2uM3Wf5CUYUGpjhxndBKCTFrgUzKW7mbESLJM0K6KBms8JbFWKK8ZwqTpfWqt3w5LllI6x5i9vypsH6uBgVD22nUWmRGK5eXxmWZJoz7zLzuLnJeVQDr5_gjADMwYKIF6l72uJVtSxNS33SUNwPWg_BLLf9BFBR5M\/w576-h640\/Spearman_rank_correlation3.png\" width=\"576\"\/><\/a><\/div>\n<p><b>Step2:<\/b> Click on ANALYTICAL TOOL followed by CORRELATION AND REGRESSION ANALYSIS followed by PEARSON CORRELATION<\/p>\n<p><b>Step3:<\/b> Upload the csv file and Click on SUBMIT button<\/p>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEiM1jXLtbQMMX4KUX_C1tcsDVs6V_Ccr5NE8Rif4pnqG9A4izpJPgzlJ-luwNYopYQjauX0OgRDKnxtEbAjtytP2vnus3LsOfYWHQiIjXjABc-YcbQIe06wwY4dfH5GVeLKrB2VhcHBbtfLCAXTwPHV4hUgWCYwPyBPtYz42tNMsZCj80gI21J6Dwx3Teo\/s1581\/Spearman_rank_correlation4.png\" style=\"margin-left: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"771\" data-original-width=\"1581\" height=\"312\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEiM1jXLtbQMMX4KUX_C1tcsDVs6V_Ccr5NE8Rif4pnqG9A4izpJPgzlJ-luwNYopYQjauX0OgRDKnxtEbAjtytP2vnus3LsOfYWHQiIjXjABc-YcbQIe06wwY4dfH5GVeLKrB2VhcHBbtfLCAXTwPHV4hUgWCYwPyBPtYz42tNMsZCj80gI21J6Dwx3Teo\/w640-h312\/Spearman_rank_correlation4.png\" width=\"640\"\/><\/a><\/div>\n<p><b>Step4:<\/b> Click on the download<\/p>\n<p><b>Output Report:<\/b><\/p>\n<p>The output will have three components 1) Heatmap 2) Correlation with p values 3) Interpretation report<\/p>\n<p><b>1) Heatmap<\/b><\/p>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEjuLZgQFswsD6bfOyNzZXdZITWSXF92UEBqBwyf0ZpwngT2svmk_iv1nhk609aPKC549qTD9lOUwdWokCADQfDk59uiOWAo5ZBVUrrV6Ykh93ZzzhWFiVi511G4Rr6uxmz2TMkbo5CqOqWg_3VRFby7GAudFGCZHuzA7zpZ6rl4tz-W8qttf3URhixYYeI\/s2695\/correlation_heatmap_with_values.jpg\" style=\"margin-left: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"2433\" data-original-width=\"2695\" height=\"289\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEjuLZgQFswsD6bfOyNzZXdZITWSXF92UEBqBwyf0ZpwngT2svmk_iv1nhk609aPKC549qTD9lOUwdWokCADQfDk59uiOWAo5ZBVUrrV6Ykh93ZzzhWFiVi511G4Rr6uxmz2TMkbo5CqOqWg_3VRFby7GAudFGCZHuzA7zpZ6rl4tz-W8qttf3URhixYYeI\/s320\/correlation_heatmap_with_values.jpg\" width=\"320\"\/><\/a><\/div>\n<p><b>2) Spearman Rank Correlation Matrix<\/b><\/p>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEhHDNK7bRbetbtF9i4_vgNLibD1XPs8T_f4Y81PzLneyWMZ8cVLKTDEJ92xVtqc_Nmw4gGOi1OAvXsFjluFInSWhzFvr-QHxONLzcJnpAe7S0J3xbZwuNTXzznArM2ss9w4FWjEixRCZLgqLC5S3-DTOaR_KWcFoYKFCVSqXDKjNZ7qkMm2wUFHAVyyr0w\/s931\/Spearman_rank_correlation5.png\" style=\"margin-left: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"331\" data-original-width=\"931\" height=\"143\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEhHDNK7bRbetbtF9i4_vgNLibD1XPs8T_f4Y81PzLneyWMZ8cVLKTDEJ92xVtqc_Nmw4gGOi1OAvXsFjluFInSWhzFvr-QHxONLzcJnpAe7S0J3xbZwuNTXzznArM2ss9w4FWjEixRCZLgqLC5S3-DTOaR_KWcFoYKFCVSqXDKjNZ7qkMm2wUFHAVyyr0w\/w400-h143\/Spearman_rank_correlation5.png\" width=\"400\"\/><\/a><\/div>\n<p><b>3) Smart interpretation<\/b><\/p>\n<div class=\"separator\" style=\"clear: both; text-align: center;\"><a href=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEiYzuJAfjnSgXuuRDJMLR-7dveKQhYV_CKvdJPEuV_eC9_813pkeWKFzx6D9Kzcs7EQHdv9-rb4ChpaRfE8TYOXjTCadQxUGCUS0fjNhZyFXBPeIxrwzXfmaHTr4-kBloucJircFuVavd9OKZoOHM3QQAtoIJho9hOz0dJssznHdxN95T22x0m40QBPHx4\/s1218\/Spearman_rank_correlation6.png\" style=\"margin-left: 1em; margin-right: 1em;\"><img loading=\"lazy\" decoding=\"async\" border=\"0\" data-original-height=\"762\" data-original-width=\"1218\" height=\"250\" src=\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEiYzuJAfjnSgXuuRDJMLR-7dveKQhYV_CKvdJPEuV_eC9_813pkeWKFzx6D9Kzcs7EQHdv9-rb4ChpaRfE8TYOXjTCadQxUGCUS0fjNhZyFXBPeIxrwzXfmaHTr4-kBloucJircFuVavd9OKZoOHM3QQAtoIJho9hOz0dJssznHdxN95T22x0m40QBPHx4\/w400-h250\/Spearman_rank_correlation6.png\" width=\"400\"\/><\/a><\/div>\n<p><b>Additional Topics:<\/b><\/p>\n<p><b>The blog is written by<\/b><\/p>\n<p>\u00a0<\/p>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>\u00a0The blog is about Spearman Rank Correlation theory, when to use, calculation along with formulas, testing its significance, solved example and step by step guide for Agri Analyze (Reading time 10 mins)\u00a0 Correlation is a statistical measure that quantifies the strength and direction of the relationship between two variables. For example, it can be used [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":56564,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12026],"tags":[25333,10990,24554,25437,31226,32208],"dealstore":[],"offerexpiration":[],"class_list":["post-56563","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-agriculture","tag-agri","tag-analysis","tag-analyze","tag-correlation","tag-rank","tag-spearman"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Spearman Rank Correlation Analysis using Agri Analyze - Som2ny Network<\/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:\/\/fivemor.com\/?p=56563\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Spearman Rank Correlation Analysis using Agri Analyze - Som2ny Network\" \/>\n<meta property=\"og:description\" content=\"\u00a0The blog is about Spearman Rank Correlation theory, when to use, calculation along with formulas, testing its significance, solved example and step by step guide for Agri Analyze (Reading time 10 mins)\u00a0 Correlation is a statistical measure that quantifies the strength and direction of the relationship between two variables. For example, it can be used [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fivemor.com\/?p=56563\" \/>\n<meta property=\"og:site_name\" content=\"Som2ny Network\" \/>\n<meta property=\"article:published_time\" content=\"2025-01-30T00:15:34+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/fivemor.com\/wp-content\/uploads\/2025\/01\/Spearman_rank_correlation1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"685\" \/>\n\t<meta property=\"og:image:height\" content=\"352\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fivemor.com\/?p=56563#article\",\"isPartOf\":{\"@id\":\"https:\/\/fivemor.com\/?p=56563\"},\"author\":{\"name\":\"admin\",\"@id\":\"https:\/\/fivemor.com\/#\/schema\/person\/b85e3c3dc0e1daea076524dc8810c371\"},\"headline\":\"Spearman Rank Correlation Analysis using Agri Analyze\",\"datePublished\":\"2025-01-30T00:15:34+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fivemor.com\/?p=56563\"},\"wordCount\":531,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fivemor.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/fivemor.com\/?p=56563#primaryimage\"},\"thumbnailUrl\":\"https:\/\/fivemor.com\/wp-content\/uploads\/2025\/01\/Spearman_rank_correlation1.png\",\"keywords\":[\"Agri\",\"Analysis\",\"analyze\",\"Correlation\",\"Rank\",\"Spearman\"],\"articleSection\":[\"Agriculture\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fivemor.com\/?p=56563#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fivemor.com\/?p=56563\",\"url\":\"https:\/\/fivemor.com\/?p=56563\",\"name\":\"Spearman Rank Correlation Analysis using Agri Analyze - 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