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Instruction 16-2
a Chemist Employed by a Pharmaceutical Firm Has

question 33

True/False

Instruction 16-2
A chemist employed by a pharmaceutical firm has developed a muscle relaxant. She took a sample of 14 people suffering from extreme muscle constriction. She gave each a vial containing a dose (X) of the drug and recorded the time to relief (Y) measured in seconds for each. She fit a quadratic model to this data. The results obtained by Microsoft Excel follow.
 OUTPU?  Regression  Statistics  Multiple R 0.747 R Square 0.558 Adj. R Square 0.478 Std. Error 863.1 Observations 14 ANOVA df Ss  MS F Signif F  Regression 210,344,7975,172,3996.940.0110 Residual 118,193,929744,903 Total 1318,538,726 Coeff  Std. Error  t stat P-value  Intercept 1283.0352.03.650.0040 CenDose 25.2288.6312.920.0140 CenDoseSq 0.86040.37222.310.0410\begin{array}{|c|c|c|c|c|c|}\hline & \text { OUTPU? } & & & & \\\hline \text { Regression } & \text { Statistics } & & & & \\\hline \text { Multiple R } & & 0.747 & & & \\\hline \text { R Square } & & 0.558 & & & \\\hline \text { Adj. R Square } & & 0.478 & & & \\\hline \text { Std. Error } & & 863.1 & & & \\\hline \text { Observations } & & 14 & & & \\\hline & & & & & \\\hline \text { ANOVA } & & & & & \\\hline & d f & \text { Ss } & \text { MS } & F & \text { Signif F } \\\hline \text { Regression } & 2 & 10,344,797 & 5,172,399 & 6.94 & 0.0110 \\\hline \text { Residual } & 11 & 8,193,929 & 744,903 & & \\\hline \text { Total } & 13 & 18,538,726 & & & \\\hline & & & & & \\\hline & \text { Coeff } & \text { Std. Error } & \text { t stat } & P \text {-value } & \\\hline \text { Intercept } & 1283.0 & 352.0 & 3.65 & 0.0040 & \\\hline \text { CenDose } & 25.228 & 8.631 & 2.92 & 0.0140 & \\\hline \text { CenDoseSq } & 0.8604 & 0.3722 & 2.31 & 0.0410 & \\\hline\end{array}
Note: Adj. R Square = Adjusted R Square; Std. Error = Standard Error
-Referring to Instruction 16-2,suppose the chemist decides to use a t test to determine if there is a significant difference between a linear model and a quadratic model that includes a linear term.If she used a level of significance of 0.01,she would decide that the linear model is sufficient.


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