What is the correct answer? I only got 2/4 points. The comment at the bottom is from my professor.

Question 1 2 / 4 pts Based on the correlation matrix below, should we expect the linear regression model Y = 3.2 + 4X1 + 7X2 + 13.5 X3 to have multicollinearity? Explain. Be sure to cite specific evidence from the table. Correlation matrix: X3 X2 . X3 .0.95226-506 X2 0.81575472 -0.88254405 x1 0.91554414 -0.94931639 0.97744912 Your Answer: Multicollinearity is present when a predictor variable is highly correlated with the remaining predictor variables. Based on the correlation matrix above I would argue that multicollinearity is present because the predictor variables are highly correlated. X3 and Y have a strong negative correlation of -0.95. X2 and Y have a strong positive correlation of 0.82. X1 and Y have a strong positive correlation of 0.92. X1 and X3 have a strong negative correlation of -0.95. X2 and X3 have a strong negative correlation of -0.88. X1 and X2 have a strong positive correlation of 0.98. We want strong correlations between predictors and Y - this correlation has nothing to do with multicollinearity