Techniques for analyzing populations - parametric methods

X Variable(s): continuous
Y Variable(s): continuous

  1 X 2 X n X
1 Y
  • One-way, univariate, least squares analysis (i.e. Regression)
  • Two-way, univariate, least squares analysis (i.e. Regression)
  • Multiple linear regression analysis
  • Multi-way, univariate, least squares analysis (i.e. Regression)
  • Multiple linear regression analysis
2 Y
  • One-way, multivariate, least squares analysis (i.e. Multivariate Regression)
  • Two-way, multivariate, least squares analysis (i.e. Multivariate Regression)
  • Canonical Correlation
  • Multi-way, multivariate, least squares analysis (i.e. Multivariate Regression)
  • Canonical Correlation
n Y
  • One-way, multivariate, least squares analysis (i.e. Multivariate Regression)
  • Two-way, multivariate, least squares analysis (i.e. Multivariate Regression)
  • Canonical Correlation
  • Multi-way, multivariate, least squares analysis (i.e. Multivariate Regression)
  • Canonical Correlation

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