A company has built a regression model to predict the number of labor hours (Yi) required to process a batch of parts (Xi). It has developed the following Excel spreadsheet of the results. A B C D E F G 1 Regression Statistics 2 Multiple R 0.9970 3 R Square 0.9941 4 Adjusted R Square 0.9933 5 Standard Error 0.3679 6 Observations 10 7 8 ANOVA 9 df SS MS F Significance F 10 Regression 1 181.5971 181.5971 1341.5500 0.0000 11 Residual 8 1.0829 0.1354 12 Total 9 182.6800 13 14 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 15 Intercept 4.8400 0.2513 19.2571 0.0000 4.2604 5.4196 16 X Variable 1 1.4836 0.0405 36.6272 0.0000 1.3902 1.5770 Interpret the meaning of the "Lower 95%" and "Upper 95%" terms in cells F16:G16 of the spreadsheet. Group of answer choices We are 95% confident that 1.3902 <= Beta1 <= 1.5770. We are 95% confident that errors are normally distributed. We are 95% confident that the residual value of the error will be within that range. We are 95% confident that the variable is significant