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Artemon [7]
3 years ago
5

5 (10k + 1) + 2 (2 + 8k)

Mathematics
2 answers:
Eddi Din [679]3 years ago
6 0

Answer:

66k+9

Step-by-step explanation:

Simplify: 50k+5+4+16k

Combine like-terms: 66k+9

Hope this helps

Fittoniya [83]3 years ago
5 0

Answer:

66+5k

Step-by-step explanation:

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Step-by-step explanation:

Regression analysis is used to infer about the relationship between two or more variables.

The line of best fit is a straight line representing the regression equation on a scatter plot. The may pass through either some point or all points or none of the points.

<u>Method 1:</u>

Using regression analysis the line of best fit is: y=\alpha +\beta x+e

Here <em>α </em>= intercept, <em>β</em> = slope and <em>e</em> = error.

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\alpha =\bar y-\beta \bar x

Here<em> </em>\bar y and \bar x are mean of the <em>y</em> and <em>x</em> values respectively.

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The formula to compute the slope is:

\beta =\frac{\sum (x-\bar x)(y - \bar y)}{\sum (x=\bar x)^{2}}

And the formula to compute the error is:

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<u>Method 2:</u>

The regression line can be determined using the descriptive statistics mean, standard deviation and correlation.

The equation of the line of best fit is:

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\sigma_{x} and \sigma_{y} are standard deviation of <em>x</em> and <em>y</em> respectively.

\sigma_{x}=\frac{1}{n}\sum (x-\bar x)^{2} \\\sigma_{y}=\frac{1}{n}\sum (y-\bar y)^{2}

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