1. Multiple Linear Regression is used to develop a mathematical model to predict the weight (M in grams) of calamansi basing from the big diameter (D in mm) and the small diameter (d in mm). Table 1 shows the MS Excel regression analysis from the data. From this findings, predict the weight of a calamansi if its big diameter is 30 mm and its small diameter is 25 mm. (6 pts) Table 1. Summary Output for the Regression Analysis SUMMARY OUTPUT Regression Statistics Multiple R 0.9067 R Square 0.8221 Adjusted R Square 0.8194 Standard Error 0.9394 Observations 132.0000 ANOVA df SS MS F Significance F Regression 2.0000 526.1426 263.0713 298.0919 0.0000 Residual 129.0000 113.8447 0.8825 Total 131.0000 639.9873 Coefficients Standard Error t Stat P-value Lower 95% Intercept -17.5763 1.1793 -14.9044 0.0000 -19.9095 D (Big diameter, mm) 0.5015 0.0464 10.8027 0.0000 0.4097 d (Small diameter, mm) 0.5937 0.0533 11.1439 0.0000 0.4883