The following MINITAB output presents a multiple regression equation

\hat { y } = b _ { 0 } + b _ { 1 } x _ { 1 } +

b _ { 2 } x _ { 2 } + b _ { 3 } x _ { 3 } + b _ { 4 } x _ { 4 }

The regression equation is

\mathrm { Y } = 5.5079 + 1.6552 \mathrm { X } 1 - 1.1088 \mathrm { X } 2 + 1.3981 \mathrm { X } 3 - 1.2465 \mathrm { X } 4

\begin{array}{lllll}\text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\\text { Constant } & 5.5079 & 0.7640 & 1.1002 & 0.314 \\\text { X1 } & 1.6552 & 0.7032 & 3.1929 & 0.002 \\\text { X2 } & -1.1088 & 0.6023 & -3.2310 & 0.005 \\\text { X3 } & 1.3981 & 0.8970 & 1.8137 & 0.087 \\\text { X4 } & -1.2465 & 0.8251 & -1.1433 & 0.354\end{array}

\mathrm{S}=2.2181 \quad \mathrm{R}-\mathrm{Sq}=41.6 \% \mathrm{R}-\mathrm{Sq}(\text { adj })=35.0 \%

\begin{array}{l}\text { Analysis of Variance }\\\begin{array}{lcccrr}\text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F P } & \\\text { Regression } & 4 & 637.5 & 159.4 & 7.1480 & 0.003 \\\text { Residual Error } & 40 & 893.2 & 22.3 & & \\\text { Total } & 44 & 1530.7 & & & \\\hline\end{array}\end{array}

Let

\beta _ { 1 }

be the coefficient

X _ { 1 }

Test the hypothesis

H _ { 0 } : \beta _ { 1 } = 0

versus

H _ { 1 } : \beta 1 \neq 0

at the

\alpha = 0.05 \text { level. }

What do you conclude?
A) Do not reject H₀
B) Reject H₀

Following Are Observed Frequencies H0:p1=0.45,p2=0.25H _ { 0 } : p _ { 1 } = 0.45 , p _ { 2 } = 0.25H0​:p1​=0.45,p2​=0.25

Multiple Choice