Este ejemplo representa un oscilador de desplazamiento de fase realizado con un transistor JFET Canal-N, dos resistencias y una red de re-alimentación constituida por tres resistencias y tres condensadores idénticos. El condensador CS se utiliza para una configuración de drenaje común y CO permite desacoplar la salida de la red de re-alimentación. Esta red es destacada en un recuadro coloreado de fondo, que se genera usando la biblioteca de TiKZ "backgrounds"
Vo = tensión de salida.
VDD= polarización positiva en el terminal de drenaje.
Todos los componentes eléctricos y electrónicos carecen de valores o tipos.
Este esquema es una adaptación de la figura que se encuentra en la página http://www.circuitstoday.com/fet-applications.
We revisit the results of the recent Reproducibility Project: Psychology by the Open Science Collaboration. We compute Bayes factors—a quantity that can be used to express comparative evidence for an hypothesis but also for the null hypothesis—for a large subset (N = 72) of the original papers and their corresponding replication attempts. In our computation, we take into account the likely scenario that publication bias had distorted the originally published results. Overall, 75% of studies gave qualitatively similar results in terms of the amount of evidence provided. However, the evidence was often weak (i.e., Bayes factor < 10). The majority of the studies (64%) did not provide strong evidence for either the null or the alternative hypothesis in either the original or the replication, and no replication attempts provided strong evidence in favor of the null. In all cases where the original paper provided strong evidence but the replication did not (15%), the sample size in the replication was smaller than the original. Where the replication provided strong evidence but the original did not (10%), the replication sample size was larger. We conclude that the apparent failure of the Reproducibility Project to replicate many target effects can be adequately explained by overestimation of effect sizes (or overestimation of evidence against the null hypothesis) due to small sample sizes and publication bias in the psychological literature. We further conclude that traditional sample sizes are insufficient and that a more widespread adoption of Bayesian methods is desirable.