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The data in the data frame asset are from Myers (1990), \Classical and Modern Regression with Applications (Second Edition)," Duxbury. The response y here is rm return on assets for thirty companies in 1982. We wish to predict the response in terms of the predictors x1-x7. Fit a linear model including all the predictors. Use the drop1 command to rank models obtained from the original model by deleting one predictor variable. If the model can be improved by deletion of a variable, t the reduced model. Iterate this procedure of examining one variable deletions until the model can no longer be improved (according to AIC) by any one variable deletion. For the nal model, plot diagnostic quantities and comment on these plots.
There are situations where none of the three averages is fully satisfactory. For example, if the number of items in a series is very small, none of these av
Advantages By definition, mode is the most typical or representative value of a distribution. Hence, when we talk of modal wage, modal size of shoe or modal size of family i
how can i calculate seasonal index?
A real estate agency collected the data shown below, where y = sales price of a house (in thousands of dollars) x 1 = home size (in hundreds of square f
Theories of Business forecasting
Chi Square Test as a Distributional Goodness of Fit In day-to-day decision making managers often come across situations wherein they are in a state of dilemma about the applica
Different analyses of recurrent events data: The bladder cancer data listed in Wei, Lin, and Weissfeld (1989) is used in Example 54.8/49.8 of SAS to illustrate different anal
Meaning and Definitions of Business Forecasting The problem of business forecasting refers to the analysis of the past and present economic conditions. With the objectiv
Simple Regression: The Teacher Preparation Research Team conducted a study of college students who took the Praxis II-a teacher certification examination. Some variables from
Type of Variable in Regression Analysis There are two types of variable in regression analysis. These are: a. Dependent variable b. Independent variable
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