A method for analyzing a microbiological sample contained in at least one sample well, the well also containing an antimicrobial material and a growth indicator material, comprising the steps of: directing a plurality of different analyzing light wavelengths onto said microbiological sample contained in said sample well; detecting a respective resultant light intensity for the wavelengths of light emanating from said microbiological sample for each of said analyzing light wavelengths directed onto said microbiological sample; generating result values representative of each respective resultant light intensity measurement at each wavelength; calculating from said result values growth indicator values, wherein at least one of said growth indicator values represents a redox state of said microbiological sample based on the reduction of the growth indicator material causing a change of color, and wherein another of said growth indicator values represents a turbidity value of said microbiological sample, characterized in that it further comprises the steps of: providing time series data for the redox and turbidity values; smoothing said time series data for both redox and turbidity values with a local regression algorithm obtaining interpolated data to calculate metrics that describe the growth in the well; and utilizing the metrics to derive a series of variables that are further used in a generalized additive model using a sum of polynomial functions of each variable to calculate a minimum inhibitory concentration of the antimicrobial material. directing a plurality of different analyzing light wavelengths onto said microbiological sample contained in said sample well; detecting a respective resultant light intensity for the wavelengths of light emanating from said microbiological sample for each of said analyzing light wavelengths directed onto said microbiological sample; generating result values representative of each respective resultant light intensity measurement at each wavelength; calculating from said result values growth indicator values, wherein at least one of said growth indicator values represents a redox state of said microbiological sample based on the reduction of the growth indicator material causing a change of color, and wherein another of said growth indicator values represents a turbidity value of said microbiological sample, characterized in that it further comprises the steps of: providing time series data for the redox and turbidity values; smoothing said time series data for both redox and turbidity values with a local regression algorithm obtaining interpolated data to calculate metrics that describe the growth in the well; and utilizing the metrics to derive a series of variables that are further used in a generalized additive model using a sum of polynomial functions of each variable to calculate a minimum inhibitory concentration of the antimicrobial material. providing time series data for the redox and turbidity values; smoothing said time series data for both redox and turbidity values with a local regression algorithm obtaining interpolated data to calculate metrics that describe the growth in the well; and utilizing the metrics to derive a series of variables that are further used in a generalized additive model using a sum of polynomial functions of each variable to calculate a minimum inhibitory concentration of the antimicrobial material.