Thursday, November 5, 2009: 3:20 PM

Santa Fe (Camino Real Hotel)

This study applied regression statistical analyses to chemical kinetics for the reaction of butyl chloride with water to produce butyl alcohol and HCL, as a function of time. The methodology checked the normality of the data through probability distributions. A quadratic statistical regression model and transformed logarithmic regression model were fitted to structure the best regression equation. Their utility was validated through objectivistic statistical and subjectivistic graphical approaches. The validated regression model was used to predict the molar concentrations of the remaining substances and of the molarity of the products formed, at any time. Also, instantaneous reactions rates, of the remaining substances or of the products, at specific times, were calculated using the best regression model or through graphical analyses. Finally, graphs of logarithmic transformed molar concentrations and the reciprocal of the remaining molar concentrations of butyl chloride as a function of time were done to determine the order of the reaction. The results show that a probability normal distribution is the most plausible to represent the data butyl chloride data. Likewise, the results show that a transformed logarithmic regression model was the most appropriate one to predict the molar concentrations of the reactants and products. Similarly, the results show the reaction of butyl chloride with water is a first order reaction. Also, the results showed that the regression model can be used to calculate instantaneous reaction rates at any point in time. It is concluded that statistical methods are useful in checking the normality of the rate data before one attempt to process the data. It is also concluded that regression analyses are useful tools to structure the best regression equation that can be used to calculate instantaneous reaction rates and the molar concentrations for the reactants and products, for prediction purposes.