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在一定范围内,浓度 C 与吸光值 A 成正比。在数学上它们的图象是一条直线。可是经验告诉我们,由于误差的存在,表示 C 与 A 关系的试验点实际上并不严格地分布在一条直线上。在标准曲线法中,是凭眼睛的估计,画出一条与各试验点最为接近的直线来作图的。这当然很难讲是精确的。然而,利用数理统计中的一元线性回归分析能较好地解决这个作直线的问题。在数学上,一条直线可写成方程y=a+bx最接近各试验点的直线我们称为回归直线,而代表回归直线的方程叫做回归直线方程。
Within a certain range, the concentration C is proportional to the absorbance A Mathematically, their image is a straight line. However, experience tells us that due to the existence of errors, the test points indicating the relationship between C and A are not strictly in a straight line. In the standard curve method, it is based on the estimation of the eye, drawing a line closest to each test point for mapping. Of course it’s hard to tell exactly. However, the use of mathematical statistics in the linear regression analysis can be a better solution to this problem as a straight line. Mathematically, a straight line can be written as the equation y = a + bx. The line closest to each test point is called the regression line, and the equation representing the regression line is called the regression line equation.