A data set shown partly in Table 2.4 and fully available in the Optics.dat file at the text website is taken from a math education graduate student research project. For the optics module in a high school freshman physical science class, the randomized study compared two instruction methods (1 = model building inquiry, 0 = traditional scientific). The response variable was an optics post-test score. Other explanatory variables were an optics pre-test score, gender (1 = female, 0 = male), OAA (Ohio Achievement Assessment)

reading score, OAA science score, attendance for optics module (number of days), and individualized education program (IEP) for student with disabilities (1 = yes, 0 = no).

a. Fit the linear model with instruction type, pre-test score, and attendance as explanatory variables. Summarize and interpret the software output.

b. Find and interpret diagnostics, including residual plots and measures of influence, for this model.
Table 2.4 Partial Optics Instruction Dataa for Exercise 2.45 ID Post Inst Pre Gender Reading Science Attend IEP 1 50 1 50 0 368 339 14 0 2 67 1 50 0 372 389 11 0

…

37 55 0 42 1 385 373 7 0 Source: Thanks to Harry Khamis, Wright State University, Statistical Consulting Center, for these data, provided with client permission. Complete data (n = 37) are in the file Optics.dat at www.stat.ufl

.edu/~aa/glm/data.