Final Answer:
The correct answer is B) Correlation coefficient measures the strength of a linear relationship.
Step-by-step explanation:
Generating a quadratic equation from chart data involves identifying a pattern or trend that suggests a quadratic relationship. However, the correlation coefficient specifically measures the strength and direction of a linear relationship between two variables. It does not provide information about quadratic relationships. Therefore, option B is the accurate statement.
Quadratic equations represent parabolic relationships, and generating them typically involves identifying the coefficients that best fit the data. This process may include using regression analysis or curve fitting techniques. On the other hand, the correlation coefficient, often denoted as r, ranges from -1 to 1 and quantifies the linear relationship between variables. A value of 1 indicates a perfect positive linear correlation, -1 indicates a perfect negative linear correlation, and 0 indicates no linear correlation.
In summary, while quadratic equations can be generated from chart data to represent nonlinear relationships, the correlation coefficient is specifically designed for assessing linear relationships. It is essential to choose the appropriate statistical tool based on the nature of the relationship observed in the data.