The coefficient describes the size and direction of the relationship between a term in the model and the response variable. The absolute value of the coefficient indicates the relative strength of each factor. To minimize multicollinearity among the terms, the coefficients are all in coded units.
The number of coefficients Minitab calculates for a factor is the number of levels minus one. If a factor has 3 levels, Minitab provides 2 coefficients, which correspond to factor levels 1 and 2. If a factor has 2 levels, Minitab provides 1 coefficient, which corresponds to factor level 1. Minitab includes the values or text that correspond to the level.
In Taguchi designs, the magnitude of the factor coefficient usually mirrors the factor rank in the response table. Depending on your analysis, the response can be a signal-to-noise ratio, the mean for a static design, the slope for a dynamic design, or a standard deviation.
The size of the effect is usually a good way to assess the practical significance of the effect that a term has on the response variable. The size of the effect does not indicate whether a term is statistically significant because the calculations for significance also consider the variation in the response data. To determine statistical significance, examine the p-value for the term.