{"id":66989,"date":"2026-10-13T11:01:18","date_gmt":"2026-10-13T08:01:18","guid":{"rendered":"https:\/\/wpcalc.com\/en\/?p=66989"},"modified":"2026-10-13T11:01:18","modified_gmt":"2026-10-13T08:01:18","slug":"kruskal-wallis-test-calculator","status":"publish","type":"post","link":"https:\/\/wpcalc.com\/en\/statistics\/kruskal-wallis-test-calculator\/","title":{"rendered":"Kruskal\u2013Wallis Test Calculator"},"content":{"rendered":"<section class=\"not-prose calculator-box\" aria-labelledby=\"calculator-title\"><div class=\"flex items-baseline sm:items-center justify-between gap-2 sm:gap-3\"><div class=\"flex flex-col sm:flex-row sm:items-center gap-2\"><span class=\"icon icon-calculator text-primary-700! text-base! dark:text-primary-300!\" aria-hidden=\"true\"><\/span><h2 id=\"calculator-title\" class=\"text-lg font-display font-bold\">Compare Three or More Groups by Ranks<\/h2><\/div><div class=\"calcdash-favorite group\">\n  <button type=\"button\" class=\"favorite\" id=\"favorite\" data-favorite-id=\"66989\" data-favorite-title=\"Kruskal\u2013Wallis Test\" data-favorite-url=\"https:\/\/wpcalc.com\/en\/statistics\/kruskal-wallis-test-calculator\/\" data-favorite-excerpt=\"Enter the observations of three or four groups and this calculator runs the Kruskal\u2013Wallis test: it ranks all values together, computes the tie-corrected H statistic, degrees of freedom, p-value and the decision at your chosen significance level.\" aria-label=\"Add to Favorites\" data-favorite-icon=\"icon icon-wpcalc-bell-curve\">\n    <span class=\"icon icon-shape-star-empty\" aria-hidden=\"true\"><\/span>\n  <\/button>\n  <div class=\"calcdash-favorite__tip\" aria-hidden=\"true\">\n   <span class=\"favorite-tooltip\" id=\"favorite-tooltip\"><\/span>\n  <\/div>\n  <span class=\"sr-only\" role=\"status\" id=\"favorite-status\"><\/span>\n<\/div><\/div><form action=\"https:\/\/wpcalc.com\/en\/statistics\/kruskal-wallis-test-calculator\/\" method=\"POST\" class=\"calculator\" id=\"calculator-66989\" data-post=\"66989\"><fieldset class=\"fieldset-input is-1\"><legend class=\"sr-only\">Input Fields<\/legend><div class=\"field\" id=\"input-1\"><label for=\"field-1\">Group 1 observations<\/label><textarea id=\"field-1\" name=\"group_1_observations\">7; 8; 9; 9; 10<\/textarea><\/div><div class=\"field\" id=\"input-2\"><label for=\"field-2\">Group 2 observations<\/label><textarea id=\"field-2\" name=\"group_2_observations\">5; 6; 6; 7; 8<\/textarea><\/div><div class=\"field\" id=\"input-3\"><label for=\"field-3\">Group 3 observations<\/label><textarea id=\"field-3\" name=\"group_3_observations\">3; 4; 4; 5; 6; 7<\/textarea><\/div><div class=\"field\" id=\"input-4\"><label for=\"field-4\">Group 4 observations (optional)<\/label><textarea id=\"field-4\" name=\"group_4_observations_optional\"><\/textarea><\/div><div class=\"field has-term\" id=\"input-5\"><label for=\"field-5\">Significance level<\/label><div class=\"term\">\u03b1<\/div>  <div class=\"absolute bottom-0 left-16 top-8 w-2 h-0.5 bg-blue-500\"><\/div><input type=\"text\" name=\"significance_level\" id=\"field-5\" aria-describedby=\"calc-info-5\" data-number inputmode=\"decimal\" autocomplete=\"off\" spellcheck=\"false\" placeholder=\"e.g. 0.05\" min=\"0.0001\" max=\"0.5\" value=\"0.05\"\/><small id=\"calc-info-5\">Type I error rate \u03b1, the threshold below which the p-value counts as statistically significant. 0.05 is the conventional choice.<\/small><\/div><\/fieldset><div class=\"buttons\"><button type=\"submit\" data-text=\"Re-Calculate\" id=\"calculate-button\" data-post=\"66989\">Calculate<\/button><button type=\"reset\">Reset<\/button><\/div><div class=\"field is-checkbox hidden!\" id=\"field-auto-calc\"><input type=\"checkbox\" id=\"auto-calc\"><label for=\"auto-calc\">Calculate automatically<\/label><small>If enabled, the result will update automatically when you change any value.<\/small><\/div><div class=\"fieldset-result is-hidden\" aria-labelledby=\"result-title\" aria-live=\"polite\" role=\"region\"> <h3 class=\"result-title bg-gradient-to-r from-primary-50 to-gray-50 dark:from-primary-900 dark:to-gray-800\" id=\"result-title\"><span class=\"icon icon-s-pulse\" aria-hidden=\"true\"><\/span> Kruskal\u2013Wallis Test Results<\/h3><div class=\"result-box\"><div class=\"field-result\" id=\"output-1\"><span class=\"field-title\"><span>H statistic (tie-corrected)<\/span><span class=\"result-term\">H\u2032<\/span><\/span><span class=\"field-value\" id=\"result-1\"><\/span><button type=\"button\" class=\"copy-result\" data-tooltip=\"Copy Result\" aria-label=\"Copy Result\"><span class=\"copy-icon icon icon-document-copy\" aria-hidden=\"true\"><\/span><\/button><\/div><div class=\"field-result\" id=\"output-2\"><span class=\"field-title\"><span>H before tie correction<\/span><span class=\"result-term\">H<\/span><\/span><span class=\"field-value\" id=\"result-2\"><\/span><button type=\"button\" class=\"copy-result\" data-tooltip=\"Copy Result\" aria-label=\"Copy Result\"><span class=\"copy-icon icon icon-document-copy\" aria-hidden=\"true\"><\/span><\/button><\/div><div class=\"field-result\" id=\"output-3\"><span class=\"field-title\"><span>Degrees of freedom<\/span><span class=\"result-term\">\u03bd<\/span><\/span><span class=\"field-value\" id=\"result-3\"><\/span><button type=\"button\" class=\"copy-result\" data-tooltip=\"Copy Result\" aria-label=\"Copy Result\"><span class=\"copy-icon icon icon-document-copy\" aria-hidden=\"true\"><\/span><\/button><\/div><div class=\"field-result\" id=\"output-4\"><span class=\"field-title\"><span>p-value (chi-square approximation)<\/span><span class=\"result-term\">p<\/span><\/span><span class=\"field-value\" id=\"result-4\"><\/span><button type=\"button\" class=\"copy-result\" data-tooltip=\"Copy Result\" aria-label=\"Copy Result\"><span class=\"copy-icon icon icon-document-copy\" aria-hidden=\"true\"><\/span><\/button><\/div><div class=\"field-result\" id=\"output-5\"><span class=\"field-title\"><span>Decision at significance level \u03b1<\/span><\/span><span class=\"field-value\" id=\"result-5\"><\/span><button type=\"button\" class=\"copy-result\" data-tooltip=\"Copy Result\" aria-label=\"Copy Result\"><span class=\"copy-icon icon icon-document-copy\" aria-hidden=\"true\"><\/span><\/button><\/div><div class=\"field-result is-column\" id=\"output-6\"><span class=\"field-title\"><span>Group ranks and medians<\/span><\/span><span class=\"field-value\" id=\"result-6\"><\/span><button type=\"button\" class=\"copy-result\" data-tooltip=\"Copy Result\" aria-label=\"Copy Result\"><span class=\"copy-icon icon icon-document-copy\" aria-hidden=\"true\"><\/span><\/button><\/div><div class=\"field-result is-column\" id=\"output-7\"><span class=\"field-title\"><span>How the test works and interpretation<\/span><\/span><span class=\"field-value\" id=\"result-7\"><\/span><button type=\"button\" class=\"copy-result\" data-tooltip=\"Copy Result\" aria-label=\"Copy Result\"><span class=\"copy-icon icon icon-document-copy\" aria-hidden=\"true\"><\/span><\/button><\/div><\/div><div class=\"result-actions\"><button type=\"button\" class=\"copy-link\"><svg viewBox=\"0 0 20 20\" fill=\"currentColor\" aria-hidden=\"true\"><path d=\"M12.232 4.232a2.5 2.5 0 0 1 3.536 3.536l-1.225 1.224a.75.75 0 0 0 1.061 1.06l1.224-1.224a4 4 0 0 0-5.656-5.656l-3 3a4 4 0 0 0 .225 5.865.75.75 0 0 0 .977-1.138 2.5 2.5 0 0 1-.142-3.667l3-3Z\"\/><path d=\"M11.603 7.963a.75.75 0 0 0-.977 1.138 2.5 2.5 0 0 1 .142 3.667l-3 3a2.5 2.5 0 0 1-3.536-3.536l1.225-1.224a.75.75 0 0 0-1.061-1.06l-1.224 1.224a4 4 0 1 0 5.656 5.656l3-3a4 4 0 0 0-.225-5.865Z\"\/><\/svg><span class=\"copy-link__text\">Copy link to this calculation<\/span><\/button><span class=\"sr-only\" role=\"status\" id=\"copy-link-status\"><\/span><\/div><\/div><a href=\"#respond\" class=\"hidden transition-opacity duration-300 opacity-0 w-50 text-sm justify-center items-center gap-2 px-4 py-2 rounded bg-gray-200 text-gray-700 hover:bg-gray-300\" id=\"leave-comment\"><span class=\"icon icon-comments\" aria-hidden=\"true\"><\/span>Leave a Comment<\/a><\/form><\/section><section id=\"calc-reactions\" class=\"not-prose hidden my-12 bg-gradient-to-r from-primary-50 to-gray-50 border border-indigo-100 rounded-xl px-6 py-4 shadow-sm\" data-post=\"66989\" aria-live=\"polite\" aria-labelledby=\"calc-reactions-title\"><p id=\"calc-reactions-title\" class=\"text-sm text-gray-500 text-center mb-2\">How did this result make you feel?<\/p><div role=\"group\" aria-labelledby=\"calc-reactions-title\" class=\"grid grid-cols-3 sm:flex sm:flex-row sm:justify-around gap-4 sm:items-center sm:flex-wrap\"><button type=\"button\" aria-pressed=\"false\" class=\"reaction-btn flex flex-col items-center gap-1 text-sm text-gray-700 hover:text-primary-600 cursor-pointer transition-transform hover:scale-105\" data-reaction=\"like\"><span class=\"reaction-count\" data-reaction-count=\"like\">0<\/span><span class=\"reaction text-3xl\" aria-hidden=\"true\">\ud83d\ude00 <\/span><span class=\"reaction-description font-medium\">Like <\/span><\/button><button type=\"button\" aria-pressed=\"false\" class=\"reaction-btn flex flex-col items-center gap-1 text-sm text-gray-700 hover:text-primary-600 cursor-pointer transition-transform hover:scale-105\" data-reaction=\"helpful\"><span class=\"reaction-count\" data-reaction-count=\"helpful\">0<\/span><span class=\"reaction text-3xl\" aria-hidden=\"true\">\ud83d\udca1 <\/span><span class=\"reaction-description font-medium\">Helpful <\/span><\/button><button type=\"button\" aria-pressed=\"false\" class=\"reaction-btn flex flex-col items-center gap-1 text-sm text-gray-700 hover:text-primary-600 cursor-pointer transition-transform hover:scale-105\" data-reaction=\"confused\"><span class=\"reaction-count\" data-reaction-count=\"confused\">0<\/span><span class=\"reaction text-3xl\" aria-hidden=\"true\">\ud83d\ude15 <\/span><span class=\"reaction-description font-medium\">Confused <\/span><\/button><button type=\"button\" aria-pressed=\"false\" class=\"reaction-btn flex flex-col items-center gap-1 text-sm text-gray-700 hover:text-primary-600 cursor-pointer transition-transform hover:scale-105\" data-reaction=\"disappointed\"><span class=\"reaction-count\" data-reaction-count=\"disappointed\">0<\/span><span class=\"reaction text-3xl\" aria-hidden=\"true\">\ud83d\ude1e <\/span><span class=\"reaction-description font-medium\">Disappointed <\/span><\/button><button type=\"button\" aria-pressed=\"false\" class=\"reaction-btn flex flex-col items-center gap-1 text-sm text-gray-700 hover:text-primary-600 cursor-pointer transition-transform hover:scale-105\" data-reaction=\"inaccurate\"><span class=\"reaction-count\" data-reaction-count=\"inaccurate\">0<\/span><span class=\"reaction text-3xl\" aria-hidden=\"true\">\u274c <\/span><span class=\"reaction-description font-medium\">Inaccurate <\/span><\/button><\/div><div id=\"reaction-message\" class=\"hidden mt-8 rounded-md border border-primary-100 bg-white\/50 backdrop-blur-sm px-4 py-2 text-sm text-center shadow-sm\"><\/div><\/section><div class=\"calcdash-ad not-prose calcdash-ad--calc_result calcdash-ad--in-article\"><ins class=\"adsbygoogle\" style=\"display:block\" data-ad-client=\"ca-pub-1721569815777345\" data-ad-slot=\"6317458308\" data-ad-layout=\"in-article\" data-ad-format=\"fluid\"><\/ins><script>(adsbygoogle = window.adsbygoogle || []).push({});<\/script><\/div>\n<style id=\"wpcoderpro-inline-1\">.formula-box {\r\n\tborder-bottom: none !important;\r\n}<\/style><section class=\"formula-box\" aria-labelledby=\"formula-title\">\r\n\t<div id=\"formula-title\" class=\"not-prose font-display mb-4\"><span class=\"icon icon-formula\" aria-hidden=\"true\"><\/span><h2>Kruskal\u2013Wallis Test Formula<\/h2><\/div>\r\n\t<figure class=\"not-prose formula\">\r\n\t\t<figcaption class=\"formula-title\">Formula<\/figcaption>\r\n\t\t<div class=\"text-base text-gray-800\" id=\"formula\">\n\\[ H = \\frac{12}{N(N+1)} \\sum_{j=1}^{k} \\frac{R_j^2}{n_j} - 3(N+1) \\\\ H' = \\frac{H}{C}, \\quad C = 1 - \\frac{\\sum \\left(t^3 - t\\right)}{N^3 - N} \\\\ p = P\\!\\left(\\chi^2_{k-1} \\ge H'\\right) \\]\n<\/div>\r\n\t<\/figure>\r\n\t<\/p>\n<p><strong>Where:<\/strong><\/p>\n<ul>\n<li>\\(k\\) \u2014 number of groups<\/li>\n<li>\\(n_j\\) \u2014 number of observations in group \\(j\\)<\/li>\n<li>\\(N\\) \u2014 total number of observations across all groups, \\(N = \\sum n_j\\)<\/li>\n<li>\\(R_j\\) \u2014 sum of the ranks of group \\(j\\), where all \\(N\\) observations are ranked together from smallest (1) to largest (\\(N\\)), and tied values share the average of their ranks<\/li>\n<li>\\(t\\) \u2014 size of each group of tied values (used in the tie correction factor \\(C\\))<\/li>\n<li>\\(\\chi^2_{k-1}\\) \u2014 chi-square distribution with \\(k-1\\) degrees of freedom<\/li>\n<\/ul>\n<p>The statistic \\(H\\) compares the average rank of each group with the overall average rank \\((N+1)\/2\\). If all groups come from the same distribution, every group should have a similar mean rank and \\(H\\) will be small; if one group tends to contain larger (or smaller) values, its mean rank departs from the average and \\(H\\) grows. Under the null hypothesis, \\(H'\\) approximately follows a chi-square distribution with \\(k-1\\) degrees of freedom, which yields the p-value.<\/p>\n<p>\r\n<\/section>\n<style id=\"wpcoderpro-inline-459\">.calculation-box {\r\n\tborder-bottom: none !important;\r\n}<\/style><section id=\"calculation\" class=\"calculation-box\" aria-labelledby=\"calculation-title\">\r\n\t<div id=\"calculation-title\" class=\"not-prose font-display\"><span class=\"icon icon-unordered-list\" aria-hidden=\"true\"><\/span><h2>Kruskal\u2013Wallis Test \u2013 Calculation Example<\/h2><\/div>\r\n\r\n<\/p>\n<p><strong>Example:<\/strong> a researcher compares patient satisfaction scores (0\u201310) under three treatments. Group 1: 7; 8; 9; 9; 10. Group 2: 5; 6; 6; 7; 8. Group 3: 3; 4; 4; 5; 6; 7. Here \\(k = 3\\), \\(N = 16\\).<\/p>\n<p>Ranking all 16 observations together (ties get average ranks) gives rank sums \\(R_1 = 67.5\\), \\(R_2 = 41\\), \\(R_3 = 27.5\\).<\/p>\n<p>\\[ H = \\frac{12}{16 \\cdot 17}\\left(\\frac{67.5^2}{5} + \\frac{41^2}{5} + \\frac{27.5^2}{6}\\right) - 3 \\cdot 17 = \\frac{12}{272} \\cdot 1373.4917 - 51 = 9.5952 \\]<\/p>\n<p>The data contain ties (six tie groups with sizes 2, 2, 3, 3, 2, 2), so \\(\\sum(t^3 - t) = 72\\) and \\(N^3 - N = 4080\\):<\/p>\n<p>\\[ C = 1 - \\frac{72}{4080} = 0.9824, \\quad H' = \\frac{9.5952}{0.9824} = 9.7674 \\]<\/p>\n<p>With \\(\\nu = k - 1 = 2\\) degrees of freedom, the chi-square approximation gives \\(p = 0.0076\\).<\/p>\n<p><strong>Result:<\/strong> \\(H' = 9.7674\\), \\(p = 0.0076 \\le \\alpha = 0.05\\), so the null hypothesis is rejected \u2014 at least one treatment tends to produce different scores. Group 1 has the highest mean rank (13.5 vs the overall average of 8.5), indicating generally larger values.<\/p>\n<p>\n\r\n<\/section>\n<h2>How to use the calculator<\/h2>\n<ol>\n<li>Enter the observations of your first group in <strong>Group 1 observations<\/strong>. Separate numbers with spaces, new lines or semicolons; decimal commas (e.g. 7,5) are accepted.<\/li>\n<li>Fill in <strong>Group 2 observations<\/strong> and <strong>Group 3 observations<\/strong> in the same format. All groups must measure the same variable on the same scale.<\/li>\n<li>If you have a fourth group, enter it in <strong>Group 4 observations (optional)<\/strong>; leave it empty when comparing only three groups. Any group you leave empty is simply skipped.<\/li>\n<li>Set the <strong>Significance level<\/strong> (default 0.05) \u2014 the threshold below which the p-value counts as statistically significant.<\/li>\n<li>Press <strong>Calculate<\/strong>. You get the tie-corrected statistic \\(H'\\), the uncorrected \\(H\\), the degrees of freedom, the p-value, the decision at your chosen \\(\\alpha\\), and a table with each group's size, rank sum, mean rank and median.<\/li>\n<\/ol>\n<h2>What the Kruskal\u2013Wallis test is<\/h2>\n<p>The Kruskal\u2013Wallis test is a nonparametric method for comparing three or more independent groups. It extends the Mann\u2013Whitney U test (the two-group case) in the same way that one-way ANOVA extends the t-test. Instead of comparing group means, it pools all observations, replaces each value by its rank, and asks whether the ranks are distributed evenly across the groups. If one group systematically contains the largest values, its mean rank will sit well above the overall average rank of \\((N+1)\/2\\), inflating the statistic \\(H\\).<\/p>\n<p>Because the test works on ranks, it makes no assumption about the shape of the underlying distributions. It does not require normality, it tolerates skewed data, and it is robust to outliers \u2014 a single extreme value can distort a mean but only shifts a rank by a fixed amount. This makes it the standard alternative to a <a href=\"https:\/\/wpcalc.com\/en\/statistics\/anova-calculator\/\">one-way ANOVA<\/a> when the ANOVA assumptions (approximately normal residuals, similar variances) are doubtful, or when the data are ordinal ratings, ranks, or scores on an arbitrary scale. The logic of rank-based comparison is the same as in the <a href=\"https:\/\/wpcalc.com\/en\/statistics\/spearman-rank-correlation-calculator\/\">Spearman rank correlation<\/a>.<\/p>\n<p>The null hypothesis states that all groups are drawn from the same distribution, i.e. no group tends to yield larger or smaller values than the others. A small p-value (at or below \\(\\alpha\\)) means the observed rank differences are unlikely under random sampling, so you reject the null and conclude that at least one group differs. Note what the test does <em>not<\/em> tell you: which groups differ from which. For that, follow up with a post-hoc procedure such as Dunn's test, or pairwise Mann\u2013Whitney U tests using a Bonferroni-adjusted threshold of \\(\\alpha \/ (k(k-1)\/2)\\). If you are unsure how to read the result, the <a href=\"https:\/\/wpcalc.com\/en\/statistics\/p-value-calculator\/\">p-value calculator<\/a> explains the logic of significance testing in more detail.<\/p>\n<p>The interpretation of medians deserves care. Strictly speaking, the Kruskal\u2013Wallis test compares whole distributions (whether one group's values tend to dominate another's). It can be read as a comparison of medians only when the group distributions have roughly the same shape and spread. The calculator reports each group's median and mean rank so you can see where the differences come from, but the formal conclusion is always about the distributions, not a single summary statistic.<\/p>\n<h2>Assumptions, limitations and practical tips<\/h2>\n<ul>\n<li><strong>Independent samples.<\/strong> The groups must be unrelated (different subjects in each). For paired or repeated-measures designs the Kruskal\u2013Wallis test is not appropriate \u2014 the Friedman test is the usual choice there.<\/li>\n<li><strong>Independent observations within groups.<\/strong> Each value should come from a different subject or experimental unit; replicated measurements of the same unit inflate the effective sample size.<\/li>\n<li><strong>Ordinal or continuous data.<\/strong> Values must at least be rankable. Nominal categories (colors, blood types) cannot be tested this way \u2014 use a <a href=\"https:\/\/wpcalc.com\/en\/statistics\/chi-square-test-calculator\/\">chi-square test<\/a> for categorical data instead.<\/li>\n<li><strong>Chi-square approximation.<\/strong> The p-value comes from approximating \\(H'\\) with a \\(\\chi^2_{k-1}\\) distribution. This works best when each group has at least 5 observations. With smaller groups, treat the p-value with caution; an exact or permutation-based method is preferable.<\/li>\n<li><strong>Ties are handled correctly.<\/strong> Tied values receive average ranks and the statistic is adjusted by the correction factor \\(C\\), so moderate numbers of ties (common with rating scales) are not a problem. The calculator shows both \\(H\\) and the corrected \\(H'\\) so you can see the size of the adjustment.<\/li>\n<li><strong>Similar distributions help interpretation.<\/strong> If the groups have clearly different shapes or variances, a significant \\(H'\\) reflects a difference in the whole distribution, not necessarily in location alone.<\/li>\n<li><strong>Group sizes need not be equal.<\/strong> The formula accounts for unequal \\(n_j\\); only very small groups weaken the chi-square approximation.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Enter the observations of three or four groups and this calculator runs the Kruskal\u2013Wallis test: it ranks all values together, computes the tie-corrected H statistic, degrees of freedom, p-value and the decision at your chosen significance level.<\/p>\n","protected":false},"author":3168,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[74],"tags":[79],"class_list":["post-66989","post","type-post","status-publish","format-standard","hentry","category-statistics","tag-hypothesis-testing"],"acf":[],"_links":{"self":[{"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/posts\/66989","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/users\/3168"}],"replies":[{"embeddable":true,"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/comments?post=66989"}],"version-history":[{"count":1,"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/posts\/66989\/revisions"}],"predecessor-version":[{"id":66990,"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/posts\/66989\/revisions\/66990"}],"wp:attachment":[{"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/media?parent=66989"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/categories?post=66989"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wpcalc.com\/en\/wp-json\/wp\/v2\/tags?post=66989"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}