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A Multiple Regression Analysis Produced the Following Tables Using α\alpha

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A multiple regression analysis produced the following tables.  Predictor  Coefficierts  Stardard Error Etatisticp-value  Irntercept 752.083333631582.2362410.042132x111.873755.320472.2317110.042493x21.9081830.6627422.8792260.01213\begin{array} { | c | c | c | c | c | } \hline \text { Predictor } & \text { Coefficierts } & \text { Stardard Error } & \mathbf { E t a t i s t i c } & \boldsymbol { p } \text {-value } \\\hline \text { Irntercept } & 752.0833 & \mathbf { 3 3 6 3 1 5 8 } & \mathbf { 2 . 2 3 6 2 4 1 } & \mathbf { 0 . 0 4 2 1 3 2 } \\\hline \mathbf { x } _ { 1 } & 11.87375 & 5.32047 & \mathbf { 2 . 2 3 1 7 1 1 } & \mathbf { 0 . 0 4 2 4 9 3 } \\\hline \mathbf { x } _ { 2 } & 1.908183 & \mathbf { 0 . 6 6 2 7 4 2 } & \mathbf { 2 . 8 7 9 2 2 6 } & \mathbf { 0 . 0 1 2 1 3 } \\\hline\end{array}  Source df SS  MS Fp-value  Regression 2203693.3101846.76.7454060.010884 Residual 12181184.115098.67 Total 14384877.4\begin{array} { | c | c | c | c | c | c | } \hline \text { Source } & \mathrm { df } & \text { SS } & \text { MS } & F & p \text {-value } \\\hline \text { Regression } & 2 & 203693.3 & 101846.7 & 6.745406 & 0.010884 \\\hline \text { Residual } & 12 & 181184.1 & 15098.67 & & \\\hline \text { Total } & 14 & 384877.4 & & & \\\hline\end{array} Using α\alpha = 0.10 to test the null hypothesis H0: β\beta 1 = β\beta 2 = 0, the critical F value is ______.


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Gutenberg’s invention that allowed individual letters or images to be moved without influencing the surrounding text.

Innis's Theories

The ideas and theories of Harold Innis, a Canadian economist and scholar known for his contributions to media theory and economic history, especially the concepts of time-biased and space-biased media.

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