A study looked at multiple factors that could affect the 'Sales' for a number of pharmacies. A correlation matrix was obtained for the variables and a multiple linear regression model was fitted for 'Sales' on 'Floor Space', 'Prescription Sales', 'Parking', 'Shopping Centre' and 'Income'. // 'n Studie het gekyk na verskeie faktore wat die Verkope ("Sales) vir 'n aantal apteke kan beinvloed. 'n Korrelasiematriks is vir die veranderlikes verkry en 'n meervoudige lineere regressiemodel is vir 'Sales' op 'Floor Space, 'Prescription Sales',""Parking', 'Shopping Centre' en 'Income' gepas. Correlation matrix: Floor Prescription Parking Shopping Income Sales Space Sales Centre Floor Space 0.751 0.504 0.710 0.863 0.183 Prescription Sales 0.751 0.328 0.341 -0.845 0.663 Parking 0.504 -0.328 0.482 0.393 0.069 Shopping Centre 0.710 0.341 0.482 0.645 0.203 Income 0.863 -0.845 0.393 0.645 0.385 Sales 0.183 -0.663 0.069 0.203 0.385 Model parameters (Sales): Standard Source Value Pr > It error Intercept 42.087 10.438 4.032 0.001 Floor Space 0.002 0.002 1.315 0.210 Prescription Sales 0.500 0.164 3.046 0.009 Parking 0.037 0.065 0.564 0.582 Shopping Centre 3.100 3.250 0.954 0.356 Income 0.107 0.427 0.250 0.807 Select the correct options below based on the outputs provided (wrong answers will be negatively marked): // Kies die korrekte opsies hieronder gebaseer op die afvoer wat verskaf word (verkeerde antwoorde sal negatief gemerk word): Select one or more: a. There is evidence of multicollinearity between the independent variables 'Income' and 'Sales'. // Daar is bewyse van multikollineariteit tussen die onafhanklike veranderlikes 'Income'en 'Sales'. b. The equation for this regression model is: 1/ Die vergelyking vir hierdie regressiemodel is: Y = 42.087 - 0.002(Floor Space) - 0.500(Prescriptions Sales) - 0.037(Parking) - 3.100(Shopping Centre) + 0.107(Income) MacBook Air