At a hydrocarbon processing factory, procest control involves petiodic analysis of samplos for a certain procoss quality paramethe, The analytic procedure currenty used is costly and time consuming. A faster and more economical atternative procedure has been proposed. However, the numbers for the quality parameter given by the alternative procedire are somewhat different trone those given by the curtent procodure, not because of any intherent erroes but because of changes in the nature of the cherrical analysis. Manapement believes that it the numbers from the new procedure can be used to forecast relably the corrasponding nuimbers from the current procedure, switching to the now procedure would be reasonable and cost effective. The following data were obtained for the quatify parameter by analyzing samples using both procedures? a. Use inear regression to find a relation to forecast y, which is the cuatty paramelor from the curent procedure, using the vatues from the proposed procedurn, X. The forecasting model is gyen by the equatien Y= At a hydrocarbon processing factory, procest control involves petiodic analysis of samplos for a certain procoss quality paramethe, The analytic procedure currenty used is costly and time consuming. A faster and more economical atternative procedure has been proposed. However, the numbers for the quality parameter given by the alternative procedire are somewhat different trone those given by the curtent procodure, not because of any intherent erroes but because of changes in the nature of the cherrical analysis. Manapement believes that it the numbers from the new procedure can be used to forecast relably the corrasponding nuimbers from the current procedure, switching to the now procedure would be reasonable and cost effective. The following data were obtained for the quatify parameter by analyzing samples using both procedures? a. Use inear regression to find a relation to forecast y, which is the cuatty paramelor from the curent procedure, using the vatues from the proposed procedurn, X. The forecasting model is gyen by the equatien Y=