Basic Statistics 2010

Basic Statistics 2010 - Non-parametric Statistics Compare...

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Basic Statistics 1. Is your Dependent Variable (the one being measured) continuous or categorical ? Categorical = Chi-Square Test , 2 kinds: o Compare ratios to a theoretical expected ratio = goodness of fit o Compare one set of ratios to another set of ratios = contingency table (also called: independence test, test of association, small n = Fisher’s exact test) Continuous = go to #2 2. Is your Independent Variable (the one being compared) continuous or categorical? Categorical o Is your sample size sufficient and data normally distributed? = Parametric Statistics Compare two categories of the independent variable = t-test If more than 2 categories of the independent variable = ANOVA If more than 1 independent variable = 2 or 3 -way ANOVA If dependent variable measured repeatedly in same individuals over time = Repeated-measures ANOVA o Is your sample size small or data skewed? =
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Unformatted text preview: Non-parametric Statistics Compare two categories of the independent variable = Mann-Whitney If more than 2 categories of the independent variable = Kruskal Wallis If independent variable measured repeatedly in same individuals over time = Friedman Continuous o Linear association = Correlation (r) Is your sample size sufficient and data normally distributed (parametric)? = Pearsons correlation Is your sample size small or data skewed (non-parametric)? = Spearmans ranks o Predict how one variable determines the value of the other = Regression Analysis (r 2 ) Linear relationship = Regression equation (y=mx+b, m=slope) & significance test (slope differs from 0) Non-linear relationship = Polynomial equation Multiple variables = Multiple Regression...
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Basic Statistics 2010 - Non-parametric Statistics Compare...

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