A regressão linear é muito utilizada em química analítica. Na prática, embora não recomendado, aceita-se a existência de uma relação linear entre quantidade de substância e a resposta instrumental medida, adotando-se o critério do coeficiente de correlação. Em livros textos são encontradas as fórmulas para o cálculo do ajuste linear, partindo-se do pressuposto de que não há erro na variável independente. Mesmo quando essa premissa não é totalmente atendida, o procedimento dos mínimos quadrados é geralmente adotado. Neste trabalho, o procedimento para a validação do modelo linear para a função calibração é descrito em detalhes, considerando-se um estudo de caso baseado em medidas para a determinação de níquel usando a técnica da espectrometria de absorção atômica chama (FAAS). Discute-se também a avaliação das incertezas relacionadas à curva de calibração. Ao considerar as incertezas de massas, volumes e resposta analítica instrumental, é observado que o fator que mais contribui à incerteza final é a incerteza da função calibração.

Least squares linear regression is widely used in analytical chemistry. In practice a linear relationship between substance content and measured value still has been assumed based on the correlation coefficient criterion, although not recommended. Textbooks provide the necessary formulas for the fitting process, based on the assumption that there is no error in the independent variable. In practice the ordinary least squares (OLS) textbook procedure is used even when the previously stated assumptions are not strictly fulfilled. In this paper, how to validate the calibration function is dealt with in detail using as an example based on measurements obtained for nickel determination by flame atomic absorption spectrometry (FAAS). Assessing uncertainties related to linear calibration curves is also discussed. Considering uncertainties of weights and volumetric equipment and instrumental analytical signal it is observed that the most important factor that contributes to the final uncertainty is the uncertainty of the calibration function.

Calculation of uncertainty of results represents the new paradigm in the area of the quality of measurements in laboratories. The guidance on the Expression of Uncertainty in Measurement of the ISO / International Organization for Standardization assumes that the analyst is being asked to give a parameter that characterizes the range of the values that could reasonably be associated with the result of the measurement. In practice, the uncertainty of the analytical result may arise from many possible sources: sampling, sample preparation, matrix effects, equipments, standards and reference materials, among others. This paper suggests a procedure for calculation of uncertainties components of an analytical result due to sample preparation (uncertainty of weights and volumetric equipment) and instrument analytical signal (calibration uncertainty). A numerical example is carefully explained based on measurements obtained for cadmium determination by flame atomic absorption spectrophotometry. Results obtained for components of total uncertainty showed that the main contribution to the analytical result was the calibration procedure.