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1 Basic ANOVA concepts - Calvin University

Math143 ANOVA1 AnalysisofVariance( ANOVA )Recall,whenwewa ntedtocompare twopopulationmeans, 'sexpandthistocomparek 3 ,wecangraphicallygetanideaofwhatis goingonbylookingatside-by-sideboxplots.( , , , ) , weare consideringa quantitativeresponsevariableasit relatestooneormore explanatoryvariables, tthissetting:(i)Whichacademicdepartmenti nthesciencesgivesoutthelowestaveragegrad es?(Explanatoryvari-able:department; Responsevariable:studentGPA's forindividualcourses)(ii)Whichkindofprom otionalcampaignleadstogreateststore incomeatChristmastime?(Explanatoryvariab le:promotiontype; Responsevariable:dailystore income)(iii)Howdothetypeofcareerandmarit alstatusofa personrelatetothetotalcostinannualclaims she/heislikelytomakeonherhealthinsurance .

(ii) look at normal quantile plots for each group and, in each case, see that the data points fall close to a line. (iii) compute the standard deviations for each group sample, and see that the ratio of the largest to the ... meaning that it has a similar interpretation to that for R2 in linear regression. 2.4 Multiple Comparisons

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1 Eigenvalues and Eigenvectors - Calvin University

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1 = (1,0,3) and u 2 = (1,1,3). It is a fact that all other eigenvectors associated with λ 2 = −2 are in the span of these two; that is, all others can be written as linear combinations c 1u 1 +c 2u 2 using an appropriate choices of the constants c 1 and c 2. Example: Find the eigenvalues and associated eigenvectors of the matrix A = −1 2 0 ...

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