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schepotkina [342]
3 years ago
10

Take away the parentheses using distributive property. −2(3v − 2x -1)

Mathematics
1 answer:
Alecsey [184]3 years ago
8 0
 You have to multiply -2 to all of the numbers inside the parenthesis and you will have your answer. -6v+4x+2
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Two numbers are in the ratio 2:3 and their sum id 45 then find both numbers​
iragen [17]

Let the numbers be 2x and 3x.

<u>According to the Question</u>,

⇒ 2x + 3x = 45

⇒ 5x = 45

⇒ x = 45/5

⇒ x = 9

<u>Now finding the values of both the number,</u>

⇒ 2x = 2 × 9

= 18

⇒ 3x = 3 × 9

= 27

<u>Hence, the value of both the number is 18 and 27 respectively.</u>

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3 years ago
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Write an expression for the calculation double 2 and then add 5.
Mariana [72]

The expression is (2x2)+5

8 0
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A person who weighs 120 pounds on Earth weighs 20 pounds on the Moon. How much does a 93-pound person weigh on the Moon?
Andre45 [30]
If you would like to know how much does a 93-pound person weigh on the Moon, you can calculate this using the following steps:

120 pounds on the Earth ... 20 pounds on the Moon
93 pounds on the Earth ... x pounds on the Moon = ?

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x = 20 * 93 / 120
x = 15.5 pounds on the Moon

The correct result would be 15.5 pounds on the Moon.
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3 years ago
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What is the GCF of 4x^ 2 +6x
Triss [41]

Answer:

The GCF of 4x^2 + 6x

is. (2x )

hope it helps

2x

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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.

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

7 0
3 years ago
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