Wine Chemistry and Biochemistry

(Steven Felgate) #1
Chapter 13

Statistical Techniques for the Interpretation


of Analytical Data


Pedro J. Mart ́ın-Alvarez ́


Contents


13.1 UnivariateStatisticalTechniques ............................................. 677
13.1.1 StatisticalTreatmentforOnlyOneSample.............................. 678
13.1.2 StatisticalTreatmenttoCompareTwoIndependent Samples ............... 680
13.1.3 StatisticalTreatmenttoCompareTwoRelatedSamples ................... 681
13.1.4 StatisticalTreatmenttoCompareMorethanTwoIndependentSamples...... 682
13.2 BivariateStatisticalTechniques .............................................. 688
13.2.1 CorrelationAnalysis ................................................ 688
13.2.2 SimpleLinearRegressionAnalysis .................................... 689
13.3 MultivariateStatisticalTechniques............................................ 692
13.3.1 Introduction................ ........................................ 692
13.3.2 MultivariateStatisticalNonSupervisedTechniques....................... 693
13.3.3 MultivariateStatisticalSupervisedTechniques........................... 699
13.3.4 MultivariateStatisticalTechniquestoStudyDependence .................. 706
References ............................................................... 710


In this chapter, I will try to explain some of the statistical methods (univariate, bivari-


ate and multivariate) most used by our group, in the hope that it will be useful and


accessible for the majority of readers, given that the emphasis is on comprehension


of the principles of the methods, their applications and interpretation of the results


obtained.


13.1 Univariate Statistical Techniques


In this first section, we will consider the statistical methods to process data, originat-


ing in the observation ofa single continuous random variable. We will distinguish


three possible situations, with one, two or more than two data sets of the observed


variable. In the last case, we will present the Analysis of Variance (ANOVA) for one


or more factors.


P. J. M a r t ́ın-Alvarez ( ́ B)
Instituto de Fermentaciones Industriales, Consejo Superior de Investigaciones Cient ́ıficas (CSIC),
C/Juan de la Cierva 3, 28006 Madrid, Spain
e-mail: [email protected]


M.V. Moreno-Arribas, M.C. Polo (eds.),Wine Chemistry and Biochemistry,
DOI 10.1007/978-0-387-74118-525,©CSpringer Science+Business Media, LLC 2009


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