Corrected minor typos
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@ -152,7 +152,7 @@ Defining the *design matrix*
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$$ \mathbf{X} = \left( \begin{array}{cccc}
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1 & x_{11} & \ldots & x_{1p} \\
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\vdots & \vdots & \ddots & \vdots \\
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1 & x_{11} & \ldots & x_{1p}
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1 & x_{n1} & \ldots & x_{np}
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\end{array}\right) \qquad
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(\text{size } n \times (p+1)), $$
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@ -177,7 +177,7 @@ regression model, but we provide explicit formulas now:
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- estimated standard errors:
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$$
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\hat s_{\beta_i} = \sqrt{([\mathbf{X}^\top \mathbf{X}]^{-1})_{ii} \frac 1 {n-p} \|\mathbf{y} - \mathbf{X} \beta\|^2}
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\hat s_{\beta_i} = \sqrt{([\mathbf{X}^\top \mathbf{X}]^{-1})_{ii} \frac 1 {n-p-1} \|\mathbf{y} - \mathbf{X} \beta\|^2}
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$$
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- $t$-statistics:
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@ -187,7 +187,7 @@ regression model, but we provide explicit formulas now:
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- $p$-values:
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$$
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p\text{-value} = \mathbb{P}(|T| > t_i), \quad \text{where } T \sim t_{n-p}
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p\text{-value} = \mathbb{P}(|T| > t_i), \quad \text{where } T \sim t_{n-p-1}
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$$
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::: {.callout-caution collapse="false"}
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