mba 522 F-tests for b1 in mulitple regression

mba 522 F-tests for b1 in mulitple regression - Carrying...

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Carrying out a test of significance is not difficult at all. All that you should do is apply the formula correctly. For an F-test for multiple regression, you would use equation 13.14 to compute the "observed" F-value. We call it "observed" or “calculated” because it is calculated from sample data that we examine. For the example problem in your book (on page 550): Observed F-value = MSR/MSE = 10.8/0.328 = 32.9 These figures are reported on the Excel printout ANOVA section if you run Excel. The Minitab output on top of page 550 also reports these values. Now that we know the calculated-F, we must gauge it against the "table" F-value (also called the "critical F-value"). If the calculated F-statistic is higher than the critical F, then the test is significant (meaning that we can reject the null hypothesis which says: b1=0). To find the critical F from the table, you must know a couple of things: 1) Two values for degrees of freedom (df) for MSR and for MSE. ***The df for MSR (numerator) is "p" which is the number of X variables (i.e., predictor
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This note was uploaded on 11/13/2011 for the course MBA 522 taught by Professor Nabavi during the Spring '08 term at Bellevue.

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mba 522 F-tests for b1 in mulitple regression - Carrying...

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