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Firlakuza [10]
2 years ago
5

How do i quit branily

Mathematics
2 answers:
fiasKO [112]2 years ago
7 0

Answer:

Log out, delete your account, or make bad questions to get banned.

Step-by-step explanation:

Andre45 [30]2 years ago
5 0

Answer:

look it up

Step-by-step explanation:

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1. Determine el valor de W en las proporciones siguientes:<br> a) (12/w) = (4/3); w =
8090 [49]

Aplicando multiplicación cruzada, tiene-se que el valor de w es w = 9.

  • Cuando una proporción es dada, con una igualdade de duas proporciones, puede-se aplicar multiplicación cruzada entre ellas.

En este problema, la ecuación que relaciona las proporciones es dada por:

\frac{12}{w} = \frac{4}{3}

Aplicando multiplicación cruzada:

4w = 12(3)

4w = 36

w = \frac{36}{4}

w = 9

El valor de w es w = 9.

Un problema similar es dado en brainly.com/question/24615636

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Amelie has 385 muffins that she must package into boxes. Each box must hold 9 muffins. Amelie divides 385 by 9 and gets an answe
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2nd one: amelia has 7 muffins left after filling 42 boxes

Step-by-step explanation:

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Katie's business is going so well she wants to expand and add a shirt. She makes an isosceles triangle logo like the one below.
OleMash [197]
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3 years ago
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Which statements about residuals are true for the least-squares regression line? I. A random scattering of residuals indicates t
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Answer:

II. The sum of the residuals is always 0.

Step-by-step explanation:

A least squares regression line is a standard technique in regression analysis used to make the vertical distance obtained from the data points running to the regression line to become very minimal or as small as possible.

For any least-squares regression line, the sum of the residuals is always zero.

Basically, residuals are used to measure or determine whether or not the line of regression is a good fit or match for the data by subtracting the difference between them i.e the predicted y value and the actual y value, for the x value respectively.

Hence, the statement about residuals which is true for the least-squares regression line is that the sum of the residuals is always zero (0).

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