Logistic regression is a pretty flexible method. It can readily use
as independent variables categorical variables. Most software that use
Logistic regression should let you use categorical vari...
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The graph at right shows three ROC curves representing excellent, good, and worthless tests
plotted on the same graph. The accuracy of the test depends on how well the test separates
the group b...
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definition of F-score - Wikipedia
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Feature Scaling, Normalization, Standardization, Transformation, code in python, differences, when to use, simple feature scaling, min max, z score, log
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Handling missing values in support vector machine classifiers
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he Least Squares method of estimationof parameters of linear (regression) models performs well provided that the residuals (disturbances or errors) are well behaved (preferably normally or ne...
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Cohen's d is an effect size used to indicate the standardised difference between two means. It can be used, for example, to accompany reporting of t-test and ANOVA&n...
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If you have a random variable following a standard normal distribution, then we would expect its mean to be 0 so this is perfectly possible....
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Grouping Data - SPSS Tutorials - LibGuides at Kent State University
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Logistic Regression (Binary)...
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The phrase “data not shown” peppers scientific manuscripts, referring to findings that are relevant enough to be mentioned but not to be depicted in a figure...
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Quantifying heterogeneity in a meta‐analysis...
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This video explains how to calculate a priori and post hoc power calculations for correlations and t-tests using G*Power. G*Power download: http://www.gpower...
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When you perform a large number of statistical tests, some will have P values less than 0.05 purely by chance, even if all your null hypotheses are really true. The Bonferroni correction is ...
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Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variab...
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