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Summary of statistical concepts

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This article presents most of the statistical concepts used at nova.

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Methodological considerations
1. P-value In hypothesis testing, the p-value is the probability that the data would occur if the null hypothesis were true. A very small p-value means that such an observed outcome would be very…
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- Summary of statistical concepts
Quantitative validation methods
Patient level data Here we present the measures used when handling patient-level data in the context of validation: 1. Pearson correlation test See Pearson correlation test in the Hypothesis testing…
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- Summary of statistical concepts
Survival analysis
This section introduces the survival analysis concept and the most popular techniques related to this subject - they are detailed in the following: 0. Survival analysis Survival analysis corresponds…
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Hypothesis testing
This section provides an overview of a set of statistical tests frequently used at nova - they are detailed in the following: 1. Parametric tests Parametric tests are those that make assumptions…
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- Summary of statistical concepts
Feature selection
This section aims to provide an insight into several feature selection techniques - they are described in the following: 1. Random Forest The random forest is a supervised machine learning algorithm…
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- Summary of statistical concepts
Statistical modeling
This section aims to describe the most popular statistical modeling approaches and techniques - they are detailed in the following: 1. Regression Regression models describe and attempt to show the…
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- Summary of statistical concepts

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This article presents most of the statistical concepts used at nova.

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