To determine which function best models the data in the table, we would need to:

1. Compare the table's values with those predicted by each of the given functions.
2. Look at how the values change based on the input values (usually $x$) and compare them to the changes predicted by the functions.

Steps:

• Each function provided is in the form $f(x) = b - mx$, which is a linear function with a slope $m$ and y-intercept $b$.
• We can check which of these functions provides the closest match to the values in the table by calculating the function values for different $x$-values and comparing them to the corresponding $y$-values in the table.

If you have the specific data from the table (with pairs of $x$- and $f(x)$-values), I can use that information to identify which function fits best.

Could you share the table data so we can proceed?

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Do you want more details on these steps or any other specific question?

Here are 5 relative questions to expand the topic:

1. How can we determine the slope of a linear function from data points?
2. What are the characteristics of a linear function?
3. How can we check if a function is linear based on a table of values?
4. How do we use the rate of change in real-life scenarios?
5. What other types of functions could model data, besides linear functions?

Tip: When comparing functions, always look for patterns like constant rates of change, which signal a linear relationship.