goodness of fit tests to a normal goodness of fit tests to a normal

Behind the scenes

Shapiro-Wilk and Kolmogorov-Smirnov tests are the most commonly used contrast tests to check the goodness of fit to a normal distribution of our data. Its implementation is described step by step and its equivalence in graphical methods such as the theoretical quantile graph and the cumulative density function graph.
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goodness of fit tests to a normal goodness of fit tests to a normal

The vanishing hitchhiker

The p curve focuses on the significant p values of the primary studies of a meta-analysis and allows us to estimate, in addition to publication bias, whether there may be a real effect after the study, what its magnitude is, and whether there is suspicion of improper practices by researchers to obtain statistically significant values.
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goodness of fit tests to a normal goodness of fit tests to a normal

The tree and the labyrinth

A decision tree is a machine learning model that is used to estimate a target variable based on several input variables. This target variable can be either numerical (regression trees) or nominal (classification trees). The methodology for constructing decision trees for regression and classification is described, as well as their interpretation.
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goodness of fit tests to a normal goodness of fit tests to a normal

The polysemy of Q

Cochran's Q is a widely used measure to detect heterogeneity between primary studies in a meta-analysis. Its statistical properties and hypothesis testing are reviewed. Finally, other measures calculated from this value are described, such as the I2 statistic and the H2 statistic, frequently used to quantify the intensity of heterogeneity between studies.
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