Predicted and experimental values for vital capacity can differ due to various factors, including individual variations in lung anatomy, health conditions, and environmental influences. The predicted values are typically based on population averages and do not account for unique personal factors such as age, sex, height, weight, and fitness level. Additionally, measurement errors during the experimental assessment, such as improper technique or equipment calibration, can further contribute to discrepancies between the two values.
mostly, how good your theory is. Remember, experimental values are from reality.
Absolutely not. Experimental is practical and theoretically anything is possible.
A rectangle has no value - experimental or otherwise. Its area has a value, its perimeter, its aspect have values.
The source code to calculate the mean square error in matlab is this function: MSE = mean((desired - mean).^2). This indicates that you have the desired signal and the actual signal to work with.
The mean sum of squares due to error: this is the sum of the squares of the differences between the observed values and the predicted values divided by the number of observations.
Experimental values may differ from literature values in chemistry due to errors in measurement techniques, equipment calibration, sample purity, or human error in performing experiments. Additionally, variation in experimental conditions, such as temperature, pressure, or reaction time, can also contribute to discrepancies between experimental and literature values.
mostly, how good your theory is. Remember, experimental values are from reality.
These are the experimental values.
These are the experimental values.
Absolutely not. Experimental is practical and theoretically anything is possible.
experimental control
A rectangle has no value - experimental or otherwise. Its area has a value, its perimeter, its aspect have values.
No
Weighted residuals in particle size analysis refer to the differences between the actual measurements of particle sizes and the predicted values from a mathematical model, adjusted by applying a weight to each residual based on its importance or significance. Weighted residuals are used to evaluate the accuracy and fit of a particle size distribution model to experimental data, with the goal of minimizing the overall error between predicted and measured values.
A variable whose values are independent of changes in the values of other variables. The factor you are testing.
The differences in values of stresses and strains between experimental and theoretical results can arise from several factors. Experimental conditions may include imperfections, material inhomogeneities, and environmental influences not accounted for in theoretical models. Additionally, assumptions made in theoretical calculations, such as idealized material behavior or simplified boundary conditions, can lead to discrepancies. Furthermore, measurement errors and limitations in experimental techniques can also contribute to the observed differences.
The total squared error between the predicted y values and the actual y values