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timurjin [86]
3 years ago
6

The least squares regression line minimizes the sum of the:

Mathematics
1 answer:
lorasvet [3.4K]3 years ago
3 0

Answer:

d) Squared differences between actual and predicted Y values.

Step-by-step explanation:

Regression is called "least squares" regression line. The line takes the form = a + b*X where a and b are both constants. Value of Y and X is specific value of independent variable.Such formula could be used to generate values of given value X.

For example,

suppose a = 10 and b = 7. If X is 10, then  predicted value for Y of 45 (from 10 + 5*7). It turns out that with any two variables X and Y. In other words, there exists one formula that will produce the best, or most accurate predictions for Y given X. Any other equation would not fit as well and would predict Y with more error. That equation is called the least squares regression equation.

It minimize the squared difference between actual and predicted value.

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Solve x2 = 12x - 15 by completing the square. Which is the solution set of the equation?
Novosadov [1.4K]

Answer:

(6-√21,  6+√21)

Step-by-step explanation:

x^2 - 12x = -15

(x - 6)^2 - 36 = -15

(x - 6)^2 = 21

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3 years ago
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USPshnik [31]

Step-by-step explanation:

6\sqrt3\cdot\dfrac{\sqrt3}{3}=\dfrac{(6\sqrt3)(\sqrt3)}{3}\\\\\text{use the associative property}\ (a\times b)\times c=a\times(b\times c)\\\\=\dfrac{(6)(\sqrt3\cdot\sqrt3)}{3}\\\\\text{use}\ \sqrt{a}\cdot\sqrt{a}=a\\\\=\dfrac{(6)(\not3)}{\not3}\qquad\text{cancel 3}\\\\=6

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3 years ago
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finlep [7]

Answer:

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Step-by-step explanation:

Open at -4 and closed at 5 on number line so the inequality should be

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