Final answer:
The statement is false; a complete 2nd-order model can include a variety of terms and interactions beyond the one quantitative predictor, its quadratic term, and one qualitative predictor with two levels and their interactions.
Step-by-step explanation:
The statement that a complete 2nd-order model always includes one quantitative predictor and its quadratic term, one qualitative predictor with two levels, and the interactions between these elements is false. While this could describe a specific type of 2nd-order polynomial model used in regression analysis, the term "complete 2nd-order model" is not restricted to this particular set-up.
In general, a 2nd-order model could include additional terms and interactions depending on the context of the problem and the number of predictors involved. For example, it could include more qualitative predictors or more quadratic terms if there are additional quantitative predictors.
The central point is that a complete 2nd-order model could vary based on the complexity of the mathematical relationships under study and the specific application, such as determining how two or more numerical variables are related (e.g., pressure versus number of moles, or n versus temperature).