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

question 90

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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 is the form of the null hypothesis?


Definitions:

Factor Overlaps

Situations where different elements or variables in a study or analysis share common characteristics, leading to redundancy or confusion.

Gender Bias

Prejudice or discrimination based on someone's gender, often favoring one gender over another.

Living Wage

The minimum income necessary for a worker to meet their basic needs, including housing, food, healthcare, and education.

Minimum Wage

The lowest hourly, daily, or monthly remuneration that employers may legally pay to workers.

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