1. Based on the Information Provided in the SPSS Output of OLS Regression Analysis (see below), interpret the results of the Model Summary table focusing on the Adjusted R Square, the Standard Error of the Estimate, and determine if the model is statistically significant. Also, identify the dependent and independent variables of the OLS Regression Model, and interpret each of the unstandardized coefficients (B) for each of the variables as listed in the Coefficients table and based on the t-values and significance column (Sig.) determine which of the independent variables have a statistically significant relationship with the dependent variable.

Model R R Square Adjusted R Std. Error Square of the Estimate 1 .699a 0.489 0.479 7.14817Model Sum of df Mean F Sig Squres Square 9543.721 4 2385.930 46.695 .000a Regressi on Residual 9963.779 195 51.096 Total 19507.50 199 O (a predictors: (Constant), reading score, female, social studies score, math score) (b. Dependant Variable: science score)Coefficients Unstandardized Standardized 95% Coefficients coefficients Confidence Interval for B Model B Std. Beta Sig. Lower Upper Error Bound Bound 1 12.325 3.194 3.85 0.00 6.027 18.624 (Constant) 9 0 Math 0.389 0.074 0.368 5.25 0.00 0.243 0.535 score 2 0 female -2.101 1.023 -0. 101 -1.9 0.05 -4.027 0.007 65 Social 0.050 0.062 0.054 0.80 0.42 -0.073 0.173 studies 4 score Reading 0.333 0.073 0.347 4.60 0.00 0.192 0.479 scroe 7 0