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elena-14-01-66 [18.8K]
3 years ago
10

Why is a least-squares line given this name? A)It provides the smallest possible slope. B)It provides the smallest possible y-in

tercept. C)It provides the smallest possible value for r2, which is a squared value. D)It provides the smallest possible sum for the squares of the residuals. E)The power of x is 1, which is smaller than a power of 2, or squared.
Mathematics
1 answer:
Rasek [7]3 years ago
8 0

Answer: D) It provides the smallest possible sum for the squares of the residuals.

Step-by-step explanation:

The least square regression line usually employed when fitting linear regression model basically works in other to minimize the sum of square error(residual). The residual or error simply refers to the difference between the actual and predicted value for each point given. The least square regression line can take up different positions between the plotted points, once, depending in the sum of the square of the error values. Hence, the least square regression line will be positioned where the sum of squared error is minimum in other to increase prediction accuracy.

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A linear inequality to represent the algebraic expression is given as 492.46 - x ≥ 500

<h3>Linear Inequality</h3>

Linear inequalities are inequalities that involve at least one linear algebraic expression, that is, a polynomial of degree 1 is compared with another algebraic expression of degree less than or equal to 1.

In this problem, her minimum balance must not decrease beyond $500 or she will pay a fee.

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The inequality to represent this can be written as

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492.46 - x ≥ 500

The linear inequality is 492.46 - x ≥ 500

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