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3 years ago

What is the area of the figure? Explain the steps you take

Mathematics

1 answer:

finlep [7]3 years ago

5 0

Answer:

7.2 in² or 7.2 inches squared

Step-by-step explanation:

Area is a measure of how much space there is on a flat surface.

To find the area, just multiply the length and width of the figure.

2 × 3.6 is 7.2

When you find the area, you have to square it.

So, the answer is 7.2 in², or 7.2 inches squared

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Luden [163]

<h2>Answer = </h2><h2> $= \frac{1}{y {}^{5} x {}^{2} }$ </h2>

Step-by-step explanation:

Greetings !

simplify for variable y first

apply exponent rule

$a {}^{b} .a {}^{c} = a {}^{b +c \\ } \\ y {}^{ - 8}y {}^{5} = y {}^{ - 8 + 3}$

Add/subtract the numbers -8+3=5

$= y {}^{5}$

Apply exponent rule

$a {}^{ - b} = \frac{1}{a {}^{b} }$

Thus,

$y {}^{ - 5} = \frac{1}{y {}^{5} }$

secondly, simplify for the variable x

Apply exponent rule as we made on y

$x {}^{ - 2}$

$x {}^{ - 2} = \frac{1}{x {}^{2} }$

multiply bot the values we get

Hope it helps!

5 0

1 year ago

X^2+(5/4)x+? <br> What must be added to make a perfect square binomial

vichka [17]

25/64 is the answer to your question

5 0

3 years ago

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equat

Elenna [48]

Answer:

For this case we define the dependent variable as Y and the independent variable X. We assume that we have n observations and that means the following pairs:

$(x_1, y_1) ,....,(x_n,y_n)$

For this case we assume that we want to find a linear regression model given by:

$\hat y = \hat m x +\hat b$

Where:

$\hat m$ represent the estimated slope for the model

$\hat b$ represent the estimated intercept for the model

And for any estimation of the dependent variable $\hat y_i , i=1,...,n$ is given by this model.

The difference between the observed value of the dependnet variable and the value predicted using the estimated regression equation is known as residual, and the residual is given by this formula:

$e_i = y_i -\hat y_i , i=1,...,n$

So the best option for this case is:

d. residual

Step-by-step explanation:

For this case we define the dependent variable as Y and the independent variable X. We assume that we have n observations and that means the following pairs:

$(x_1, y_1) ,....,(x_n,y_n)$

For this case we assume that we want to find a linear regression model given by:

$\hat y = \hat m x +\hat b$

Where:

$\hat m$ represent the estimated slope for the model

$\hat b$ represent the estimated intercept for the model

And for any estimation of the dependent variable $\hat y_i , i=1,...,n$ is given by this model.

$e_i = y_i -\hat y_i , i=1,...,n$

So the best option for this case is:

d. residual

7 0

3 years ago

you have a recipe that indicates to use 2 parts of milk for every 7 parts of flour. You use 8 cups of milk. How much flour do yo

vagabundo [1.1K]

Answer:

Step-by-step explanation:

3 0

3 years ago

Sandy works at a clothing store. She makes $9 per hour plus earns 10% commission on her sales. She worked 71 hours over the

Ksivusya [100]

Step-by-step explanation:

9$ x 71 hours (rewritten) 9x 71 = 639

plus the commission

10% x 1,901$ (rewritten) .1 x 1,901 = 190.1

639 + 190.1 = 829.1

5 0

3 years ago