A researcher is analyzing whether the rate of unlawful breaking is effected by the percent of poverty, percent male, percent nonwhite, and the percent of individuals between the ages of 15 and 24 residing in the census block. Given the following SPSS output, what would the researcher conclude? State the null and alternative hypotheses, discuss the F-statistic, the R², R²change, the beta coefficients, and which variable significantly affect the dependent variable.

\begin{array}{|l|l|l|l|l|l|l|l|l|l|}\hline\\\hline \text { Mod } & & \text { R } & \text { Adjust } & \text { Std. Error } & \text { R } & & & &\text { Sig. F }\\&&\text { Squar } & \text { ed R } & \text { of the } & \text { Square } & & & \\\text { el } & \text { S } & \text { e } & \text { Square} & \text { Estimate } & \text { Change } & \text { F Change } & \text { df1 } & \text { df2 } & \text { Change } \\\\\hline 1 & .195^{\mathrm{a}} & .038 & .031 & 1843.30459 & .038 & 5.294 & 2 & 267 & .006 \\2 & 407 \mathrm{~b} & 166 & 153 & 1723.12310 & 128 & 20.272 & 2 & 265 & .000\\\hline\end{array}

a. Predictors: (Constant), percent nonwhite, percent poverty
b. Predictors: (Constant), percent nonwhite, percent poverty, percent 15 to 24, percent male

\begin{array}{|l|l|l|l|l|l|} \hline \text { Model }& \text {Sum of Squares } & \text { df } & \text { Mean Square }& \text { F }& \text { Sig. } \\\hline 1 \text { Regression } & 35977621.414 & 2 & 17988810.707 &5.294 & .006^{\mathrm{b}} \\\text { Residual } & 907205072.766 & 267 & 3397771.808 \\\text { Total } & 943182694.179 & 269 & \\\hline 2 \text { Regression } & 156357090.146 & 4 & 39089272.537&13.165 & .000^{\mathrm{c}} \\\text { Residual } & 786825604.033 & 265 & 2969153.223 \\\text { Total } & 943182694.179 & 269 & \\\hline\end{array}

a. Dependent Variable: rateofubev
b. Predictors: (Constant), percent nonwhite, percent poverty
c. Predictors: (Constant), percent nonwhite, percent poverty, percent 15 to 24, percent male

\begin{array}{l} \begin{array}{|l|l|l|l|}\hline &\text { Unstandardized }&&\text { Standardized }\\ &\text { Coefficients }& &\text { Coefficients }\\\hline \text { Model }& \text { B } & \text { Std. Error }&\text { Beta } \\\hline1\text { (Constant) } & 76.230 & 258.075 \\\text { percentpoverty } & 27.276 & 8.606&.239 \\\hline \text { percentnonwhite } & -5.544 & 4.157&-.101 \\\hline 2\text { (Constant) } & -5080.529 & 1006.335 \\\text { percentpoverty } & 21.254 & 8.173 &.186\\\hline \text { percentnonwhite } & 246 & 3.991 &.004 \\\text { percent15to24 } & -39.467 & 17.899&-.126 \\\text { percentmale } & 116.906 & 19.763&.340\\\hline\end{array}\begin{array}{l|l|}\hline\\\\ t & \text { Sig. } \\\hline .295 & .768 \\3.169 & .002 \\\hline-1.334 & .183 \\\hline-5.049 & .000 \\2.601 & .010 \\\hline .062 & .951 \\\hline-2.205 & .028 \\5.916 & .000 \\\hline\end{array}\end{array}

a. Dependent Variable: rateofubev

To Obtain the F-Statistic of a Regression Equation, One Must

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