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Multiple regression statistical analysis was performed to interpret interaction effects of the variables.
A nonlinear model was used to estimate the effects of the variables on growth parameters.
Effects of the variables and their interactions on Nannochloropsis sp. cultivation, lipid and eicosapentaenoic acid productivity are successfully revealed.
The effects of the variables of factorial design (pre-treatment and physical state) were significant at 95% level.
Multiple regression analysis was used to create models describing the effects of the variables on the three coating properties.
The experimental results were analysed statistically and the main effects of the variables were computed and analysed.
A statistical analysis was carried out to explore the effects of the variables on the composition of bacterial biomass and PCR amplification yields.
An experimental design was also developed to determine the effects of the variables and their interactions that are directly involved in the decomposition reaction.
A comparison is established between three different ways to test the significance of the effects of the variables involved on the response signal.
Analysis of variance (ANOVA) was used to determine the effects of the variables on sulphur and ash reduction from the coal.
A central composite rotatable design (CCRD) and response surface methodology (RSM) were used to evaluate the effects of the variables by the differential pulse voltammetry (DPV) method.
More suggestions(15)
effects of the values
effects of the attributes
effects of the measures
impacts of the variables
effects of the alternatives
outcomes of the variables
effects of the years
effects of the derivatives
effects of the factors
effects of the determinants
effects of the fluctuations
effects of the characteristics
impact of the variables
effects of the variance
effects of the varying
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CEO of Professional Science Editing for Scientists @ prosciediting.com