Instruction 13-13
the Education Department's Regional Executive Officer Wanted to Predict

Instruction 13-13
The education department's regional executive officer wanted to predict the percentage of students passing a Grade 6 proficiency test.She obtained the data on percentage of students passing the proficiency test (% Passing),daily average of the percentage of students attending class (% Attendance),average teacher salary in dollars (Salaries),and instructional spending per pupil in dollars (Spending)of 47 schools in the state.
Following is the multiple regression output with Y = % Passing as the dependent variable,
X₁ = % Attendance,X₂ = Salaries and X₃ = Spending:
$\begin{array}{lr}\hline {\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.7930 \\\text { R Square } & 0.6288 \\\text { Adjusted R } & 0.6029 \\\text { Square } & \\\text { Standard } & 10.4570 \\\text { Error } & \\\text { Observations } & 47\end{array}$
ANOVA
$\begin{array}{lrrrrr} & \text { df } &{\text { SS }} & \text { MS } & F&\text { Significance F } \\\hline \text { Regression } & 3 & 7965.08 & 2655.03 & 24.2802 & 0.0000 \\\text { Residual } & 43 & 4702.02 & 109.35 & & \\\text { Total } & 46 & 12667.11 & & &\end{array}$

$\begin{array}{lrrrrrr} & \text { Coefficients } & \begin{array}{c}\text { Standard } \\\text { Error }\end{array} & t \text { Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & -753.4225 & 101.1149 & -7.4511 & 0.0000 & -957.3401 & -549.5050 \\\text { \% Attendance } & 8.5014 & 1.0771 & 7.8929 & 0.0000 & 6.3292 & 10.6735 \\\text { Salary } & 0.000000685 & 0.0006 & 0.0011 & 0.9991 & -0.0013 & 0.0013 \\\text { Spending } & 0.0060 & 0.0046 & 1.2879 & 0.2047 & -0.0034 & 0.0153\end{array}$
-Referring to Instruction 13-13,the null hypothesis H₀: ?₁ = ?₂ = ?₃= 0 implies that percentage of students passing the proficiency test is not related to one of the explanatory variables.