Consider the two regressions immediately obove. In using the Akalke i.pdf

A

Consider the two regressions immediately obove. In using the Akalke information Criterion and the Bayesian information Criterion, "cioseness" counts (as in the game of horseshoes). Using the rule of thumb we learned in class regarding the interpretation of the information criteria, we could correctly say Multiple choice both modeb hove "yubstontial suppert' because the A.C and BiC ore so close in value to one another oniy Regrevion x1 has "substantiai suppon" becouse of the diferences in the values of the AIC and BiC. only fiegression 12 thas 'rubstantial suppor' becaure at the difterences in the velues of the AIC and BiC.

Consider the two regressions immediately obove. In using the Akalke information Criterion and
the Bayesian information Criterion, "cioseness" counts (as in the game of horseshoes). Using the
rule of thumb we learned in class regarding the interpretation of the information criteria, we
could correctly say Multiple choice both modeb hove "yubstontial suppert' because the A.C and
BiC ore so close in value to one another oniy Regrevion x1 has "substantiai suppon" becouse of
the diferences in the values of the AIC and BiC. only fiegression 12 thas 'rubstantial suppor'
becaure at the difterences in the velues of the AIC and BiC

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Consider the two regressions immediately obove. In using the Akalke i.pdf

  • 1. Consider the two regressions immediately obove. In using the Akalke information Criterion and the Bayesian information Criterion, "cioseness" counts (as in the game of horseshoes). Using the rule of thumb we learned in class regarding the interpretation of the information criteria, we could correctly say Multiple choice both modeb hove "yubstontial suppert' because the A.C and BiC ore so close in value to one another oniy Regrevion x1 has "substantiai suppon" becouse of the diferences in the values of the AIC and BiC. only fiegression 12 thas 'rubstantial suppor' becaure at the difterences in the velues of the AIC and BiC