Sentence examples for using equal numbers of from inspiring English sources
To validate that orientation bias is indeed a function of selection we calculated bias using equal numbers of integrations from early- and late-stage cohorts (i.e. 80,000 integrations).
Behavioral experiments were repeated 3 4 times for each group using equal numbers of randomly selected test fish (n = 15) each time, and the test fish were removed after the experiment.
The amount of bias increased when simulations were run with a more realistic inverse-J population structure than when using equal numbers of individuals in all stage classes (8.08%±20.70 SD vs. 5.14%±16.22 SD respectively when sampling 50 individuals when survival = 0.5; 2.33%±9.32 SD vs. 1.43%±7.67 SD when survival = 0.8; Figure 1).
The simulations were performed at conserved order parameter, using equal numbers of saturated and unsaturated lipids.
This was shown by mixed cultures using equal numbers of Colo205 cells and L929 mouse fibroblasts.
Using equal numbers of words in the two lexica facilitated comparison within and between the two languages.
To do this, the variable of equation is established by means of using equal number of landslide and non-landslide pixels.
Both the models show satisfactory results although LR model using equal number of landslide and non-landslide pixels shows slightly accurate results in total.
A first batch using equal number of samples from each technique computes order 1 approximation of the different quantities, which in turn allows us to obtain a first approximation of the α values needed for the second batch.
This indicates that by using equal number of landslide and non-landslide pixels with landslide causal factors to determine the variable of equation is the most reliable method to create a landslide susceptibility map. Figure 7 shows the landslide susceptibility map using FR model and the seventh test equation of LR model.
Fixing the sample size to create an equation in logistic regression analysis can be done in two ways, i.e., using all pixel landslide causal factors in study area and using equal number of dependent and independent variables to reduce bias in the sampling process (Ramani et al. 2011).
