Advanced Statistics - Biology 6030

Bowling Green State University, Fall 2017

Techniques for analyzing populations - parametric methods

X Variable(s): ordinal, nominal
Y Variable(s): continuous

  1 X 2 X n X
1 Y
  • One-way, univariate, least squares analysis (i.e. ANOVA)
  • Two-way, univariate, least squares analysis (i.e. ANOVA)
  • Multi-way, univariate, least squares analysis (i.e. ANOVA)
2 Y
  • One-way, multivariate, least squares analysis (i.e. MANOVA)
  • Discriminant function analysis
  • Two-way, multivariate, least squares analysis (i.e. MANOVA)
  • Multi-way, multivariate, least squares analysis (i.e. MANOVA)
n Y
  • One-way, multivariate, least squares analysis (i.e. MANOVA)
  • Discriminant function analysis
  • Two-way, multivariate, least squares analysis (i.e. MANOVA)
  • Multi-way, multivariate, least squares analysis (i.e. MANOVA)

Sample statistic: F-statistic

Mathematical Entity used to calculate Sample statistic: Variance/Covariance Matrix

Asumptions: Homogeneity of variance, homogeneity of variance/covariance matrix; to a lesser degree - Normality

Use: Transformations

Notes: for non-parametric versions recode data as ranks


last modified: 4/21/10
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