Halloween is a fun night. It seems that older children might get more candy because they can travel further while
trick-or-treating. But perhaps the youngest kids get extra candy because they are so cute. Here are some data that examine
this question, along with the regression output. Dependent Variable: candy
Sample size: 9

R

(correlation coefficient)

= \mathbf { 0 . 1 9 5 3 4 4 2 5 }

\mathrm { R } - \mathrm { sq } = 0.038159375

s = 11.297554

\begin{array} { l r r } \text { Parameter } & \text { Estimate } & \text { Std. Err. } \\ \text { Intercept } & 13.569231 & 9.0783516 \\ \text { Age } & 3.4038462 & 1.0175376 \end{array}

$Halloween is a fun night. It seems that older children might get more candy because they can travel further while trick-or-treating. But perhaps the youngest kids get extra candy because they are so cute. Here are some data that examine this question, along with the regression output. Dependent Variable: candy Sample size: 9 R (correlation coefficient) = \mathbf { 0 . 1 9 5 3 4 4 2 5 } \mathrm { R } - \mathrm { sq } = 0.038159375 s = 11.297554 \begin{array} { l r r } \text { Parameter } & \text { Estimate } & \text { Std. Err. } \\ \text { Intercept } & 13.569231 & 9.0783516 \\ \text { Age } & 3.4038462 & 1.0175376 \end{array} -The next day, a young girl reveals that her older brother also went trick-or-treating, but didn't want to admit that he participated. He was added to the data set and these are the results. Dependent Variable: candy Sample size: 10 R (correlation coefficient ) = 0.76362369 \mathrm { R } - \mathrm { sq } = 0.58312115 \mathrm { s } = 12.709041 \begin{array} { l r r } \text { Parameter } & \text { Estimate } & \text { Std. Err. } \\ \text { Intercept } & 13.569231 & 9.0783516 \\ \text { Age } & 3.4038462 & 1.0175376 \end{array} Describe the effect of this new candy collector on the regression model.$

-The next day, a young girl reveals that her older brother also went trick-or-treating, but
didn't want to admit that he participated. He was added to the data set and these are the
results. Dependent Variable: candy
Sample size: 10

R

(correlation coefficient

) = 0.76362369

\mathrm { R } - \mathrm { sq } = 0.58312115

\mathrm { s } = 12.709041

\begin{array} { l r r } \text { Parameter } & \text { Estimate } & \text { Std. Err. } \\ \text { Intercept } & 13.569231 & 9.0783516 \\ \text { Age } & 3.4038462 & 1.0175376 \end{array}

$Halloween is a fun night. It seems that older children might get more candy because they can travel further while trick-or-treating. But perhaps the youngest kids get extra candy because they are so cute. Here are some data that examine this question, along with the regression output. Dependent Variable: candy Sample size: 9 R (correlation coefficient) = \mathbf { 0 . 1 9 5 3 4 4 2 5 } \mathrm { R } - \mathrm { sq } = 0.038159375 s = 11.297554 \begin{array} { l r r } \text { Parameter } & \text { Estimate } & \text { Std. Err. } \\ \text { Intercept } & 13.569231 & 9.0783516 \\ \text { Age } & 3.4038462 & 1.0175376 \end{array} -The next day, a young girl reveals that her older brother also went trick-or-treating, but didn't want to admit that he participated. He was added to the data set and these are the results. Dependent Variable: candy Sample size: 10 R (correlation coefficient ) = 0.76362369 \mathrm { R } - \mathrm { sq } = 0.58312115 \mathrm { s } = 12.709041 \begin{array} { l r r } \text { Parameter } & \text { Estimate } & \text { Std. Err. } \\ \text { Intercept } & 13.569231 & 9.0783516 \\ \text { Age } & 3.4038462 & 1.0175376 \end{array} Describe the effect of this new candy collector on the regression model.$

Describe the effect of this new candy collector on the regression model.

Which Is True? I. Random Scatter in the Residuals Indicates a Model with a Model

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