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Select one of two methods for classifying cases, either updating cluster centers iteratively or classifying only.
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Tests to Predict Numerical Outcomes and Identify Groups: Explore – Confidence intervals for means M-estimators identification of outliers plotting of findings.Nonparametric tests – Chi-square, Binomial, Runs, one-sample, two independent samples, k-independent samples, two related samples, k-related samples.Correlation – Test for bivariate or partial correlation, or for distances indicating similarity or dissimilarity between measures.
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ANOVA and ANCOVA – Conduct contrast, range and post hoc tests analyze fixed-effects and random-effects measures group descriptive statistics choose your model based on four types of the sum-of-squares procedure perform lack-of-fit tests choose balanced or unbalanced design and analyze covariance with up to 10 methods.Compare means – Choose whether to use harmonic or geometric means test linearity compare via independent sample statistics, paired sample statistics or one-sample t test.Descriptive ratio statistics – Coefficient of dispersion, coefficient of variation, price-related differential and average absolute deviance.Descriptives – Central tendency, dispersion, distribution and Z scores.Frequencies – Counts, percentages, valid and cumulative percentages central tendency, dispersion, distribution and percentile values.Crosstabulations – Counts, percentages, residuals, marginals, tests of independence, test of linear association, measure of linear association, ordinal data measures, nominal by interval measures, measure of agreement, relative risk estimates for case control and cohort studies.