Question

Given are five observations for two variables, $x$ and $y$. (a) Develop a scatter diagram for these data. (b) What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? ? There appears to be a negative linear relationship between $x$ and $y$. ? There appears to be a positive linear relationship between $x$ and $y$. ? There appears to be no noticeable relationship between $x$ and $y$. (c) Try to approximate the relationship between $x$ and $y$ by drawing a straight line through the data. (d) Develop the estimated regression equation by computing the values of $b_0$ and $b_1$, using $b_1 = \frac{\sum_{i=1}^{n}(x_i-\bar{x})(y_i-\bar{y})}{\sum_{i=1}^{n}(x_i-\bar{x})^2}$ and $b_0 = \bar{y} - b_1\bar{x}$. (e) Use the estimated regression equation to predict the value of $y$ when $x = 2$.

          Given are five observations for two variables, $x$ and $y$.

(a) Develop a scatter diagram for these data.

(b) What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
? There appears to be a negative linear relationship between $x$ and $y$.
? There appears to be a positive linear relationship between $x$ and $y$.
? There appears to be no noticeable relationship between $x$ and $y$.

(c) Try to approximate the relationship between $x$ and $y$ by drawing a straight line through the data.

(d) Develop the estimated regression equation by computing the values of $b_0$ and $b_1$, using $b_1 = \frac{\sum_{i=1}^{n}(x_i-\bar{x})(y_i-\bar{y})}{\sum_{i=1}^{n}(x_i-\bar{x})^2}$ and $b_0 = \bar{y} - b_1\bar{x}$.

(e) Use the estimated regression equation to predict the value of $y$ when $x = 2$.

Given are five observations for two variables, x and y.

(a) Develop a scatter diagram for these data.

(b) What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
? There appears to be a negative linear relationship between x and y.
? There appears to be a positive linear relationship between x and y.
? There appears to be no noticeable relationship between x and y.

(c) Try to approximate the relationship between x and y by drawing a straight line through the data.

(d) Develop the estimated regression equation by computing the values of b0 and b1, using b1 = (∑i=1^n(xi-x̅)(yi-y̅))/(∑i=1^n(xi-x̅)^2) and b0 = y̅ - b1x̅.

(e) Use the estimated regression equation to predict the value of y when x = 2.

Added by Becky A.

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