To determine which equation is true based on the given set of ordered pairs, we need to analyze the pairs.
- (1, 0): When x = 1, f(x) = 0
- (10, 2): When x = 10, f(x) = 2
- (0, 6): When x = 0, f(x) = 6
- (3, 17): When x = 3, f(x) = 17
- (2, 1): When x = 2, f(x) = 1
From these points, we observe how the output f(x) behaves concerning the input x. To find an equation that represents this function, we can use the data points to formulate potential relationships. One common way is to check if there’s a linear relationship or a polynomial function that matches the points.
After plotting these points or calculating possible linear regression, we can try out different linear equations, checking each against the points. However, since this isn’t a typical polynomial or linear function, identifying the right equation may require trial and error or deeper algebraic methods like interpolation.
Upon checking, it appears that there’s no single linear equation that accurately describes all points, indicating these pairs may not follow a simple linear relationship. More complex equations or forms (like piecewise or quadratic) may better represent these relationships, but more calculations are needed to confirm.
Thus, without additional context or constraints, it’s challenging to state precisely which equation is true. Analysis of further statistical methods or equations is recommended for precise identification.