"And from the slope of the line we calculate . . ."

The major problems encountered by the student have little to do with the computer. They arise in deeidingwhich variables are to be plotted, in transfo...
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"And from the Slope of the Line We Calculate

.. ."

The availability of pre-programmed hand-held cslculators and small computers has made computation of the linear regression best fit to experimental data a simple, wutine operation for undergraduate students. We now expect students to be able to manipulate raw data, fit it to a straight line, and perform some final calculatiun of a physical constant ur concentration. The major problems encountered by the student have little to do with the computer. They arise in deeidingwhich variables are to be plotted, in transforming raw data to a form suitable for plotting, and in converting calculated values of slope or intercept to a correct numerical answer. I conclude that the underlying cause of the difficulties is the lackof practicalexperience in working this sort of problem. They simply have not examined the practicalities of what we mean when we talk about alinear relationship betweenvariables. This conclusion comes from three years of watching quantitative analysis students struggle with data from an excellent experiment that is designed to provide an exercise in the use of programmable calculators.' I t is worthwhile to note that these problems are not a t all apparent when linear regression analysis is applied to a simple ease such as a Beer's Law

End log k = log A - --2.303RT

No specific mention of the two variables to be plotted was made, but the equation was stated to be representable as a straight line. The problems encountered were numerous. These included a) Having no idea where to begin b) Plotting k versus T C) Plotting log k versus T d) Reporting the slope as EaCt 4 Using the y-intercept to calculate EaCt f ) Omitting the negative sign in calculating using a single data pair and the calculated value of log A g) Solving Cor This dry lab is done on the departmental Tektronin 31 computer interfaced to an X-Yplotter using a standard linear regression program. I t can be done on hand-held calculators, but there are some advantages to having one student a t a time work the computer after doing a preliminary organization of data and in having the data and best line plotted. There have been two positive results in this exercise which also include the use of a data plotting program. The haziness in understanding how to manipulate raw data and calculated slopes (intercepts) has been greatly reduced. The mystique of the departmental computer has been removed, and the students are using it successfully in evaluating patentiumetric titration data1 and spedrophotometric dataZfrom laboratory experiments. 'Seymour, M. D., and Fernando, Q., J. CHEM. EDUC., 54,221 (1971). Standard experiments for Cu and Fe content by atomic absorption, Fe(o-phen):j by spectruphotometry. Rlchard J. Stolzberg University of Alaska Fairbanks. AK 99701

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of Chemical Education