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Estudos Gerais • 04/28/2025

Sobre o estimador de MQO para a inclinação da reta da regres...

Sobre o estimador de MQO para a inclinação da reta da regressão linear, dado por β1^\widehat{\beta_1}, assinale a alternativa correta:

A β1^=∑i=1n(xi−xˉ)(yi−yˉ)∑i=1n(xi−xˉ)2\widehat{\beta_1} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (x_i - \bar{x})^2}

B β1^=∑i=1n(xi−xˉ)(yi−yˉ)∑i=1n(yi−yˉ)2\widehat{\beta_1} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (y_i - \bar{y})^2}

C β1^=∑i=1n(xi−xˉ)(yi−yˉ)∑i=1n(xi−xˉ)2\widehat{\beta_1} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (x_i - \bar{x})^2}

D β1^=∑i=1n(xi−xˉ)(yi−yˉ)∑i=1n(xi−xˉ)3\widehat{\beta_1} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (x_i - \bar{x})^3}

E β1^=Covariancia amostral(xi,yi)Varia^ncia amostral(yi)\widehat{\beta_1} = \frac{Covariancia \ amostral(x_i,y_i)}{Variância \ amostral(y_i)}

Sobre o estimador de MQO para a inclinação da reta da regressão linear, dado por $\widehat{\beta_1}$, assinale a alternativa correta: A $\widehat{\beta_1} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (x_i - \bar{x})^2}$ B $\widehat{\beta_1} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (y_i - \bar{y})^2}$ C $\widehat{\beta_1} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (x_i - \bar{x})^2}$ D $\widehat{\beta_1} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n} (x_i - \bar{x})^3}$ E $\widehat{\beta_1} = \frac{Covariancia \ amostral(x_i,y_i)}{Variância \ amostral(y_i)}$
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