1- The data in file T4P1.csv contain data on the performance of electronic inverters. About 30 percent of the observations were randomly select for validation, indicated by P. Use the data labeled E to build a regression equation to predict y from x1-x4 and use that model to predict y for the prediction set. Perform a complete analysis of how well the model works for the validation set.
2- For the data in T4P2.csv fit the nonlinear regression model: 𝑦= 𝜃1e^(θ_2 x)+𝜀. Report how you obtained initial guesses for the parameters and completely report on the results including parameter estimates, tests of significance and an analysis of residuals.
3- A study was conducted to investigate the relationship between family income and home ownership. The data are in file T4P3 where x is the estimated family income and y equals 1 if the family owned the home and 0 if they didn’t. Fit a logistic regression model to the data to determine whether a linear or quadratic relationship in x is appropriate.
4- The data in file T4P4 are from an experiment designed to study the advance rate, y, of a drill. The four design factors are x1=load, x2=flow, x3=drilling speed, and x4=type of drilling mud. Fit a generalized linear model to advance rate using a Gamma distribution for the response and the log link function. Comment on the fit of the model, and the significance of the factors in the model.
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