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3 years ago

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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Write a x (-a)x 13 x a x (-a) x 13 in power notation

miss Akunina [59]

Answer:

$a\times (-a)\times 13\times a\times (-a)\times 13$ can be written in power notation as $a^{4}\times 13^{2}$

Step-by-step explanation:

The given expression

$a\times (-a)\times 13\times a\times (-a)\times 13$

Writing a\times (-a)\times 13\times a\times (-a)\times 13 in power notation:

Let

$a\times (-a)\times 13\times a\times (-a)\times 13$

= $[13\times13][(a\times (-a)\times a\times (-a)]$

$13\times13 = 13^{2}$ , $a\times a = a^{2}$ , $(-a)\times (-a) = (-a)^{2}$

So,

$=[13^{2}][a^2\times (-a)^2]$

$(-a)^2 = a^{2}$

So,

$=[13^{2}][a^2\times a^2]$

As ∵ $a^{m} \times a^{n}=a^{m+n}$

$=[13^{2}][a^{2+2}]$

As ∵ $a^{m} \times a^{n}=a^{m+n}$

$=13^{2}\times a^{4}$

$=a^{4}\times 13^{2}$

Therefore, $a\times (-a)\times 13\times a\times (-a)\times 13$ can be written in power notation as $a^{4}\times 13^{2}$

Keywords: power notation

Learn more about power notation from brainly.com/question/2147364

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