Hi tutors, I need help for these 2 questions. Thanks in advance! :)

Correlations Value of Floor area in monthly sales sq mts in $k in 2007 Floor area in sq mts Pearson Correlation .954 Sig. (2-tailed) 000 N 14 14 Value of monthly sales in Pearson Correlation 954 $k in 2007 Sig. (2-tailed) 000 N 14 14 ** Correlation is significant at the 0.01 level (2-tailed).Based on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumptions while considering normality has been met. Follow the decision map steps for interpretation, and then report the results in an academic style. 12000.00 10000.00 8000.00 Value of monthly sales in $k in 2007 6000.00 4000.00 2000.00 1000.00 2000.00 3000.00 4000.00 5000.00 6000.00 Floor area in sq mtsCoefficients Standardized Unstandardized Coefficients Coefficients 95.0% Confidence Interval for B Correlations Collinearity Statistics Model B Std. Error Beta Sig Lower Bound Upper Bound Zero-order Partial Part Tolerance VIF 1 (Constant) -1.219 410 -2.976 003 -2.025 -.414 Number of cylinders .141 .051 .145 2.786 006 .042 241 840 140 060 172 5.816 Hores Power of the 1.844 .269 425 6.859 000 Engine 1.315 2.372 .854 .329 .148 120 8.305 Weight in 100 lb 834 .123 425 6.790 000 593 1.076 .886 .326 .146 118 8.449 Seconds to reach to .053 021 087 2.527 .012 012 094 speed 60 from 0 -.456 .127 054 388 2.580 a. Dependent Variable: GallonsPer100Miles Collinearity Diagnostics Variance Proportions Seconds to reach to Condition Number of Hores Power Weight in 100 speed 60 Model Dimension Eigenvalue Index (Constant) cylinders of the Engine Ib from 0 1 1 4.809 1.000 .00 .00 .00 .00 .00 2 161 5.464 .01 .01 .02 .00 .04 3 017 16.753 07 30 .34 05 01 009 23.065 .14 57 .01 43 07 5 003 37.208 .79 13 63 .51 88 a. Dependent Variable: GallonsPer1 00MilesHistogram Dependent Variable: GallonsPer100Miles Mean = -4.96E-15 60 Std. Dev. = 0.995 N = 392 50 40 Frequency 30 20 10 0 -4 -2 0 2 Regression Standardized ResidualScatterplot Dependent Variable: GallonsPer100Miles 2 0CO 20 00 0 Regression Standardized Residual 0 CO O -2 -4 -2 -1 0 2 3 Regression Standardized Predicted ValueBased on the tables and graphs below, interpret and report the results. You need to identify the test, discuss the assumptions. Follow the decision steps for interpretation, and then report the results in an academic style. Note that if any of the assumptions have been violated, you need to report it and continue as if it has not been violated. Variables Entered/Removeda Variables Variables Model Entered Removed Method Seconds to Enter Model Summary" reach to speed 60 Adjusted R Std. Error of from 0, Model R R Square Square the Estimate Weight in 100 906 821 819 70987 Ib, Number of cylinders, a. Predictors: (Constant), Seconds to reach to speed 60 from Hores Power 0, Weight in 100 lb, Number of cylinders, Hores Power of of the Engine the Engine b. Dependent Variable: GallonsPer1 00Miles a. Dependent Variable: GallonsPer1 00Miles b. All requested variables entered. ANOVA Sum of Model Squares df Mean Square F Sig Regression 893.674 223.418 443.367 000b Residual 195.014 387 504 Total 1088.688 391 a. Dependent Variable: GallonsPer100Miles b. Predictors: (Constant), Seconds to reach to speed 60 from 0, Weight in 100 lb, Number of cylinders, Hores Power of the Engine