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docs: use displaystyle in fractions with summation symbol
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‎lib/node_modules/@stdlib/stats/bartlett-test/README.md‎

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For `k` groups each with `n_i` observations, the test statistic is
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<!-- <equation class="equation" label="eq:bartlett-test-statistic" align="center" raw="\chi^2 = \frac{N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}" alt="Equation for Bartlett's test statistic."> -->
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<!-- <equation class="equation" label="eq:bartlett-test-statistic" align="center" raw="\chi^2 = \frac{\displaystyle N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{\displaystyle 1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}" alt="Equation for Bartlett's test statistic."> -->
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```math
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\chi^2 = \frac{N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}
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\chi^2 = \frac{\displaystyle N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{\displaystyle 1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}
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```
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<!-- <div class="equation" align="center" data-raw-text="\chi^2 = \frac{N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}" data-equation="eq:bartlett-test-statistic">
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<!-- <div class="equation" align="center" data-raw-text="\chi^2 = \frac{\displaystyle N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{\displaystyle 1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}" data-equation="eq:bartlett-test-statistic">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@4b1db4ebd815eb54bf53a3fa132b992604743d9c/lib/node_modules/@stdlib/stats/bartlett-test/docs/img/equation_bartlett-test-statistic.svg" alt="Equation for Bartlett's test statistic.">
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</div> -->

‎lib/node_modules/@stdlib/stats/incr/apcorr/README.md‎

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For a sample of size `n`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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```math
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r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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```
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@80f96253bf726f33bc71d8eb68037ab203ae4cf9/lib/node_modules/@stdlib/stats/incr/apcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg" alt="Equation for the sample Pearson product-moment correlation coefficient.">
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‎lib/node_modules/@stdlib/stats/incr/hmean/README.md‎

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The [harmonic mean][harmonic-mean] of positive real numbers `x_0, x_1, ..., x_{n-1}` is defined as
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<!-- <equation class="equation" label="eq:harmonic_mean" align="center" raw="\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" alt="Equation for the harmonic mean."> -->
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<!-- <equation class="equation" label="eq:harmonic_mean" align="center" raw="\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{\displaystyle n}{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{\displaystyle n} \biggr)^{-1}\end{align}" alt="Equation for the harmonic mean."> -->
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```math
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\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}
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\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{\displaystyle n}{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{\displaystyle n} \biggr)^{-1}\end{align}
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```
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<!-- <div class="equation" align="center" data-raw-text="\begin{align}H &amp;= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &amp;= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &amp;= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" data-equation="eq:harmonic_mean">
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<!-- <div class="equation" align="center" data-raw-text="\begin{align}H &amp;= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &amp;= \frac{\displaystyle n}{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &amp;= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{\displaystyle n} \biggr)^{-1}\end{align}" data-equation="eq:harmonic_mean">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@2b632747053b9e357a4663369528fe62b29a6d55/lib/node_modules/@stdlib/stats/incr/hmean/docs/img/equation_harmonic_mean.svg" alt="Equation for the harmonic mean.">
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</div> -->

‎lib/node_modules/@stdlib/stats/incr/kurtosis/README.md‎

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The previous equation is, however, a biased estimator of the population excess kurtosis. An alternative estimator which is unbiased under normality is
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<!-- <equation class="equation" label="eq:corrected_sample_excess_kurtosis" align="center" raw="G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}" alt="Equation for the corrected sample excess kurtosis."> -->
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<!-- <equation class="equation" label="eq:corrected_sample_excess_kurtosis" align="center" raw="G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}" alt="Equation for the corrected sample excess kurtosis."> -->
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```math
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G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}
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G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}
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```
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<!-- <div class="equation" align="center" data-raw-text="G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}" data-equation="eq:corrected_sample_excess_kurtosis">
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<!-- <div class="equation" align="center" data-raw-text="G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}" data-equation="eq:corrected_sample_excess_kurtosis">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@49d8cabda84033d55d7b8069f19ee3dd8b8d1496/lib/node_modules/@stdlib/stats/incr/kurtosis/docs/img/equation_corrected_sample_excess_kurtosis.svg" alt="Equation for the corrected sample excess kurtosis.">
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</div> -->

‎lib/node_modules/@stdlib/stats/incr/mae/README.md‎

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The [mean absolute error][mean-absolute-error] is defined as
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<!-- <equation class="equation" label="eq:mean_absolute_error" align="center" raw="\operatorname{MAE} = \frac{\sum_{i=0}^{n-1} |y_i - x_i|}{n}" alt="Equation for the mean absolute error."> -->
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<!-- <equation class="equation" label="eq:mean_absolute_error" align="center" raw="\operatorname{MAE} = \frac{\displaystyle\sum_{i=0}^{n-1} |y_i - x_i|}{n}" alt="Equation for the mean absolute error."> -->
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```math
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\operatorname{MAE} = \frac{\sum_{i=0}^{n-1} |y_i - x_i|}{n}
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\operatorname{MAE} = \frac{\displaystyle\sum_{i=0}^{n-1} |y_i - x_i|}{n}
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```
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<!-- <div class="equation" align="center" data-raw-text="\operatorname{MAE} = \frac{\sum_{i=0}^{n-1} |y_i - x_i|}{n}" data-equation="eq:mean_absolute_error">
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<!-- <div class="equation" align="center" data-raw-text="\operatorname{MAE} = \frac{\displaystyle\sum_{i=0}^{n-1} |y_i - x_i|}{n}" data-equation="eq:mean_absolute_error">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@49d8cabda84033d55d7b8069f19ee3dd8b8d1496/lib/node_modules/@stdlib/stats/incr/mae/docs/img/equation_mean_absolute_error.svg" alt="Equation for the mean absolute error.">
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‎lib/node_modules/@stdlib/stats/incr/mapcorr/README.md‎

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For a sample of size `W`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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```math
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r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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```
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@e7c0cbc398c5e64614baf47cf5c6259b93c0ffce/lib/node_modules/@stdlib/stats/incr/mapcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg" alt="Equation for the sample Pearson product-moment correlation coefficient.">
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‎lib/node_modules/@stdlib/stats/incr/mhmean/README.md‎

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The [harmonic mean][harmonic-mean] of positive real numbers `x_0, x_1, ..., x_{n-1}` is defined as
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<!-- <equation class="equation" label="eq:harmonic_mean" align="center" raw="\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" alt="Equation for the harmonic mean."> -->
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<!-- <equation class="equation" label="eq:harmonic_mean" align="center" raw="\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" alt="Equation for the harmonic mean."> -->
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```math
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\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}
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\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}
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```
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<!-- <div class="equation" align="center" data-raw-text="\begin{align}H &amp;= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &amp;= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &amp;= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" data-equation="eq:harmonic_mean">
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<!-- <div class="equation" align="center" data-raw-text="\begin{align}H &amp;= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &amp;= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &amp;= \biggl( \frac{\displaystyle \sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" data-equation="eq:harmonic_mean">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@0a561712608b99b59d9243f7d478a2e2a019a130/lib/node_modules/@stdlib/stats/incr/mhmean/docs/img/equation_harmonic_mean.svg" alt="Equation for the harmonic mean.">
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‎lib/node_modules/@stdlib/stats/incr/mpcorr/README.md‎

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For a sample of size `W`, the [sample Pearson product-moment correlation coefficient][pearson-correlation] is defined as
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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```math
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r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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```
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">

‎lib/node_modules/@stdlib/stats/incr/pcorr/README.md‎

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For a sample of size `n`, the [sample Pearson product-moment correlation coefficient][pearson-correlation] is defined as
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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```math
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r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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```
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@49d8cabda84033d55d7b8069f19ee3dd8b8d1496/lib/node_modules/@stdlib/stats/incr/pcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg" alt="Equation for the sample Pearson product-moment correlation coefficient.">
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‎lib/node_modules/@stdlib/stats/incr/pcorr2/README.md‎

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@@ -43,13 +43,13 @@ where the numerator is the [covariance][covariance] and the denominator is the p
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For a sample of size `n`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
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```math
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r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
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```
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
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<!-- <div class="equation" align="center" data-raw-text="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@0086d9dadd17859fedeb3c5acc3a80d7011970e1/lib/node_modules/@stdlib/stats/incr/pcorr2/docs/img/equation_sample_pearson_correlation_coefficient.svg" alt="Equation for the sample Pearson product-moment correlation coefficient.">
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