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TABLE 14-16
the Superintendent of a School District Wanted to Predict

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Short Answer

TABLE 14-16
The superintendent of a school district wanted to predict the percentage of students passing a sixth-grade 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:
Regression Statistics Multiple R 0.7930R Square0.6288Adjusted R Square0.6029Standard Error 10.4570Observations 47\begin{array}{lr}\hline\text {Regression Statistics } \\\hline \text {Multiple R }& 0.7930 \\\text {R Square} & 0.6288 \\\text {Adjusted R Square} & 0.6029 \\\text {Standard Error }& 10.4570 \\\text {Observations }& 47 \\\hline\end{array}


ANOVA
 d f  SS  MS  F  Significance F Regression 37965.082655.0324.28022.3853E09 Residual434702.02109.35 Total 4612667.11\begin{array}{lccccc}\hline &\text { d f } &\text { SS }& \text { MS }& \text { F } & \text { Significance F} \\\hline \text { Regression }& 3 & 7965.08 & 2655.03 & 24.2802 & 2.3853 \mathrm{E}-09 \\\text { Residual} & 43 & 4702.02 & 109.35 & & \\\text { Total }& 46 & 12667.11 & & & \\\hline\end{array}

 Coeffs Stnd Err t Stat p -value  Lower 95% Upper 95% Intercept 753.4225101.11497.45112.88E09957.3401549.5050% Attend 8.50141.07717.89296.73E106.329210.6735 Salary6.85E070.00060.00110.99910.00130.0013 Spending 0.00600.00461.28790.20470.00340.0153\begin{array}{lrrrrrr}\hline &\text { Coeffs} & \text { Stnd Err} &\text { t Stat} &\text { p -value }&\text { Lower 95\%} \text { Upper 95\%} \\\hline\text { Intercept }& -753.4225 & 101.1149 & -7.4511 & 2.88 \mathrm{E}-09 & -957.3401 & -549.5050 \\\%\text { Attend }& 8.5014 & 1.0771 & 7.8929 & 6.73 \mathrm{E}-10 & 6.3292 & 10.6735 \\\text { Salary} & 6.85 \mathrm{E}-07 & 0.0006 & 0.0011 & 0.9991 & -0.0013 & 0.0013 \\\text { Spending }& 0.0060 & 0.0046 & 1.2879 & 0.2047 & -0.0034 & 0.0153 \\\hline\end{array}

-Referring to Table 14-16, what is the value of the test statistic to determine whether there is a significant relationship between percentage of students passing the proficiency test and the entire set of explanatory variables?

Understand the equivalence between different forms of propositions involving negation.
Identify the categorical quality of propositions and their negations.
Identify and understand compound propositions.
Understand the formulation of logical syllogisms involving disjunctive and categorical propositions.

Definitions:

Surplus Material

Excess materials that are not required for current production needs and may be sold or reused in future projects.

Purchased Lots

Refers to parcels or quantities of goods acquired by a company, often used in reference to real estate or bulk purchases of inventory.

Relevant Cost

Costs that will be affected by a decision and will have an impact on the future.

Variable Production Cost

Charges that fluctuate in line with production levels, such as direct labor and materials used.

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