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In Mathematics / College | 2025-07-04

Devon wants to write an equation for a line that passes through 2 of the data points he has collected. The points are $(8,5)$ and $(-12,-9)$. He writes the equation $7x - 10y = 3$. Is this a good model? Explain your reasoning.

Asked by mychaelaa7

Answer (2)

The equation 7 x − 10 y = 3 is not a good model for the points ( 8 , 5 ) and ( − 12 , − 9 ) because neither point satisfies the equation. Substituting both points yields a result of 6 instead of 3. Therefore, the equation does not represent the relationship between these data points correctly.
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Answered by Anonymous | 2025-07-04

Substitute the point ( 8 , 5 ) into the equation 7 x − 10 y = 3 and get 7 ( 8 ) − 10 ( 5 ) = 6 , which is not equal to 3.
Substitute the point ( − 12 , − 9 ) into the equation 7 x − 10 y = 3 and get 7 ( − 12 ) − 10 ( − 9 ) = 6 , which is not equal to 3.
Since neither point satisfies the equation, the equation is not a good model.
The equation is not a good model: No ​

Explanation

Problem Analysis We need to determine if the equation 7 x − 10 y = 3 is a good model for the points ( 8 , 5 ) and ( − 12 , − 9 ) . To do this, we will substitute each point into the equation and see if the equation holds true.

Checking Point (8, 5) First, let's check the point ( 8 , 5 ) . We substitute x = 8 and y = 5 into the equation 7 x − 10 y = 3 :
7 ( 8 ) − 10 ( 5 ) = 56 − 50 = 6 Since 6 e q 3 , the point ( 8 , 5 ) does not satisfy the equation.

Checking Point (-12, -9) Next, let's check the point ( − 12 , − 9 ) . We substitute x = − 12 and y = − 9 into the equation 7 x − 10 y = 3 :
7 ( − 12 ) − 10 ( − 9 ) = − 84 + 90 = 6 Since 6 e q 3 , the point ( − 12 , − 9 ) does not satisfy the equation either.

Conclusion Since neither of the points ( 8 , 5 ) and ( − 12 , − 9 ) satisfy the equation 7 x − 10 y = 3 , the equation is not a good model for the given data points.


Examples
In data analysis, it's crucial to validate models against known data points. For instance, if you're predicting sales based on marketing spend, you'd check if your model accurately reflects past sales data. If the model deviates significantly from actual data, like in this problem, it indicates the model needs refinement or a different approach altogether. This ensures that predictions are reliable and useful for decision-making.

Answered by GinnyAnswer | 2025-07-04