A. \( f^{\prime \prime}(x) \) changes sign from + to - B. \( f^{\prime \prime}(x) \) changes sign from - to + C. \( f^{\prime \prime}(x)>0 \) for all \( x \) D. \( f^{\prime \prime}(x)<0 \) for all \( x \)
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When the second derivative \( f^{\prime \prime}(x) \) changes sign from + to -, as in option A, it indicates that the function \( f(x) \) has a local maximum at that point. This is because the concavity of the function is shifting from concave up to concave down, creating a peak. On the other hand, when \( f^{\prime \prime}(x) \) changes sign from - to +, as in option B, it indicates a local minimum since the function is bending from concave down to concave up, forming a trough. In practical applications, these second derivative tests help analyze and optimize functions in fields like economics and engineering. For instance, in maximizing profit or minimizing costs, understanding where a function reaches its peaks or troughs can significantly influence decision-making. Avoiding common mistakes like misinterpreting inflection points or overlooking the context of the problem ensures accurate modeling and results!