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10.10: Formula Review

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    10.2 Comparing Two Independent Population Means

    Standard error: \(S E=\sqrt{\frac{\left(s_1\right)^2}{n_1}+\frac{\left(s_2\right)^2}{n_2}}\)

    Test statistic ( \(t\)-score): \(t_c=\frac{\left(\bar{x}_1-\bar{x}_2\right)-\delta_0}{\sqrt{\frac{\left(s_1\right)^2}{n_1}+\frac{\left(s_2\right)^2}{n_2}}}\)

    Degrees of freedom:
    \[d f=\frac{\left(\frac{\left(s_1\right)^2}{n_1}+\frac{\left(s_2\right)^2}{n_2}\right)^2}{\left(\frac{1}{n_1-1}\right)\left(\frac{\left(s_1\right)^2{n_1}\right)^2+\left(\frac{1}{n_2-1}\right)\left(\frac{\left(s_2\right)^2}{n_2}\right)^2}\]

    where:

    \(s_1\) and \(s_2\) are the sample standard deviations, and \(n_1\) and \(n_2\) are the sample sizes.

    \(\bar{x}_1\) and \(\bar{x}_2\) are the sample means.

    10.3 Cohen's Standards for Small, Medium, and Large Effect Sizes

    Cohen's \(d\) is the measure of effect size:

    \[d=\frac{\bar{x}_1-\bar{x}_2}{s_{\text {pooled }}}\]

    where \(s_{\text {pooled }}=\sqrt{\frac{\left(n_1-1\right) s_1^2+\left(n_2-1\right) s_2^2}{n_1+n_2-2}}\)

    10.4 Test for Differences in Means: Assuming Equal Population Variances

    \[t_c=\frac{\left(\bar{x}_1-\bar{x}_2\right)-\delta_0}{\sqrt{S_p^2\left(\frac{1}{n_1}+\frac{1}{n_2}\right)}}\]

    where \(S p\) is the pooled variance given by the formula:

    \[S p=\frac{\left(n_1-1\right) s_1^2-\left(n_2-1\right) s_2^2}{n_1+n_2-2}\]

    10.5 Comparing Two Independent Population Proportions

    Pooled Proportion: \(p_C=\frac{x_A+x_B}{n_A+n_B}\)

    Test Statistic (z-score): \(Z_c=\frac{\left(p^{\prime}{ }_A-p_B^{\prime} B\right)}{\sqrt{p_c\left(1-p_c\right)\left(\frac{1}{n_A}+\frac{1}{n_B}\right)}}\)

    where

    \(p_A^{\prime}\) and \(p_B^{\prime}\) are the sample proportions, \(p_A\) and \(p_B\) are the population proportions,
    \(P_C\) is the pooled proportion, and \(n_A\) and \(n_B\) are the sample sizes.

    10.6 Two Population Means with Known Standard Deviations

    Test Statistic ( \(z\)-score):

    \[Z_c=\frac{\left(\bar{x}_1-\bar{x}_2\right)-\delta_0}{\sqrt{\frac{\left(\sigma_1\right)^2}{n_1}+\frac{\left(\sigma_2\right)^2}{n_2}}\]

    where:

    \(\sigma_1\) and \(\sigma_2\) are the known population standard deviations. \(n_1\) and \(n_2\) are the sample sizes. \(\bar{x}_1\) and \(\bar{x}_2\) are the sample means. \(\mu_1\) and \(\mu_2\) are the population means.

    10.7 Matched or Paired Samples

    Test Statistic ( \(t\)-score): \(t_c=\frac{\bar{x}_d-\mu_d}{\left(\frac{s_d}{\sqrt{n}}\right)}\)

    where:

    \(\bar{x}_d\) is the mean of the sample differences. \(\mu_{\mathrm{d}}\) is the mean of the population differences. \(s_d\) is the sample standard deviation of the differences. \(n\) is the sample size.


    10.10: Formula Review is shared under a not declared license and was authored, remixed, and/or curated by LibreTexts.

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