Related Experiment Video
Updated: Mar 27, 2026

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
Published on: May 17, 2024
Multiple simultaneous predictors of gestational age. An application of Bayes' theorem
1Department of Gynecology and Obstetrics, Stanford University Medical Center, California.
Abstract:
Most obstetricians share the belief that an estimate of gestational age based on several clinical measures that agree with one another is more accurate than an estimate based on a single measurement. This paper presents a formal justification for this belief by applying Bayes' theorem to calculate the probability of a fetus being a certain gestational age by using information from several clinically established single predictors. The application of Bayes' theorem justifies the use of multiple measures of gestational age in individual ultrasound examinations and the use of serial ultrasound studies in the third trimester to more accurately estimate gestational age. The same technique could be applied to obstetric research studies that need to establish accurate gestational dating.
More Related Videos
Related Concept Videos
Probability Laws
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Punnett Squares
Punnett Squares
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...

