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Instruction 13-8
You Worked as an Intern at We Always

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Instruction 13-8
You worked as an intern at We Always Win Car Insurance Company last summer.You notice that individual car insurance premium depends very much on the age of the individual,the number of traffic tickets received by the individual,and the population density of the city in which the individual lives.You performed a regression analysis in Microsoft Excel and obtained the following information:
 Regression Analysis  Regression Statistics  Multiple R 0.63 R Square 0.40 Adjusted R Square 0.23 Standard Error 50.00 Observations 15.00\begin{array}{l}\text { Regression Analysis }\\\begin{array}{lr}\hline {\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.63 \\\text { R Square } & 0.40 \\\text { Adjusted R Square } & 0.23 \\\text { Standard Error } & 50.00 \\\text { Observations } & 15.00\end{array}\end{array}
ANOVA
dfSSMSF Significance F Regression 35994.242.400.12 Residual 1127496.82 Total 45479.54\begin{array}{lrrrrrr} & d f & & S S & M S & F & \text { Significance } F \\\hline \text { Regression } & 3 & & 5994.24 & 2.40 & 0.12 \\\text { Residual } & 11 & 27496.82 & & & \\\text { Total } & & 45479.54 & & &\end{array}

 Coefficients  Standard t Stat  P-value  Lower 99.0%  Upper 99.0%  Intercept  Error  AGE 123.8048.712.540.0327.47275.07 TICKETS 0.820.870.950.363.511.87 DENSITY 21.2510.661.990.0711.8654.373.146.460.490.6423.1916.91\begin{array}{lrrrrrrr} & \text { Coefficients } & \text { Standard } & t \text { Stat } & \text { P-value } & \text { Lower 99.0\% } & \text { Upper 99.0\% } \\\hline \text { Intercept } & {\text { Error }} & & & & & \\\text { AGE } & 123.80 & 48.71 & 2.54 & 0.03 & -27.47 & 275.07 \\\text { TICKETS } & -0.82 & 0.87 & -0.95 & 0.36 & -3.51 & 1.87 \\\text { DENSITY } & 21.25 & 10.66 & 1.99 & 0.07 & -11.86 & 54.37 \\& -3.14 & 6.46 & -0.49 & 0.64 & -23.19 & 16.91\end{array}
-Referring to Instruction 13-8,to test the significance of the multiple regression model,what are the degrees of freedom?


Definitions:

Normal Distribution

A bell-shaped distribution curve that is symmetrical about the mean, describing how random variables are distributed.

Discrete

Refers to a variable that can take on a finite or countably infinite set of distinct values.

Exponential

Pertaining to a mathematical function or increase that grows more significant or at an increasingly rapid rate relative to its current value.

Standard Deviations

A way of evaluating the extent of dispersion or deviation in a group of values.

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