Emotional intelligence and team performance. Refer to the Engineering Project Organizational Journal (Vol. 3, 2013) study of the relationship between emotional intelligence of individual team members and their performance during an engineering project, Exercise 12.33 (p. 736). Using data on n = 23 teams, you fit a first-order model for mean project score 1y2 as a function of range of interpersonal scores 1x12, range of stress management scores 1x22, and range of mood scores 1x32. The regression results, as well as a correlation matrix for the independent variables, are displayed in the Minitab printout (next page). Do you detect any signs of multicollinearity TEAMPERF 12.121 Consider fitting the multiple regression model E1y2 = b0 + b1x1 + b2x2 + b3x3 + b4x4 A matrix of correlations for all pairs of independent variables is given below. Do you detect a multicollinearity problem? Explain. x1 x2 x3 x4 x1 — 0.21 0.07 0.30 x2 — -0.98 0.44 x3 — 0.91 x4 12.122 Emotional intelligence and team performance. Refer to the Engineering Project Organizational Journal (Vol. 3, 2013) study of the relationship between emotional intelligence of individual team members and their performance during an engineering project, Exercise 12.33 (p. 736). Using data on n = 23 teams, you fit a first-order model for mean project score 1y2 as a function of range of interpersonal scores 1x12, range of stress management scores 1x22, and range of mood scores 1x32. The regression results, as well as a correlation matrix for the independent variables, are displayed in the Minitab printout (next page). Do you detect any signs of multicollinearity in the data? [Note: The researchers expect the linear relationship between project score and each independent variable to be negative for range of interpersonal scores and positive for both range of stress management scores and mood scores.]