Abstract
In Section 3.1 we stated that when we observe a difference between two groups or two samples, the first thing we should exclude is that this difference is simply due to the effect of variability within the population from which the two samples were taken. From this we derived the method that the use of probability allows us to reject the null hypothesis (H0) and to accept the experimental hypothesis (H1). Therefore, if we have excluded variability within the population, does this mean we have a direct demonstration of the experimental hypothesis? Unfortunately, this is not the case. Before we can conclude in favor of the experimental hypothesis, we need to be sure that the entire process (from study design to its practical implementation, in all its details) is free from bias, i.e. systematic distortions, which might have influenced the results. If a study is flawed by substantial bias, its application to clinical practice is doubtful or not possible at all.
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(2009). Study Design, Systematic Reviews and Levels of Evidence. In: Biostatistics for Radiologists. Springer, Milano. https://doi.org/10.1007/978-88-470-1133-5_9
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DOI: https://doi.org/10.1007/978-88-470-1133-5_9
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