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OlgaM077 [116]
4 years ago
5

What is the scale factor from figure a to figure b

Mathematics
1 answer:
GaryK [48]4 years ago
8 0

Answer:

lol bro it's your exam

Step-by-step explanation:

I can give u hint:

for example,if you know the width of the shape,

divide one width by the other to find the scale factor

I hope it will help you.

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The sum of the measures of three
Iteru [2.4K]

Answer:

A

Step-by-step explanation:

Equation

2x + 3x + 8 + 7x - 2 = 90        

Solution

Combine like terms on the left

12x + 6 = 90                    Subtract 6 on both sides

12x = 90 - 6

12x = 84                         Divide by 12

x = 84/12

x = 7

8 0
3 years ago
How do I find the derivative of 2(f(x)+g(x))?
kramer
\bf 2[f(x)+g(x)]\implies 2f(x)+2g(x)\implies 2\cfrac{df}{dx}+2\cfrac{dg}{dx}\\\\
-------------------------------\\\\
\cfrac{1}{2}\left[ f(x)\cdot g(x)  \right]\implies \cfrac{1}{2}\left[ \stackrel{product~rule}{\cfrac{df}{dx}\cdot g(x)+f(x)\cdot \cfrac{dg}{dx}} \right]
\\\\\\
\cfrac{1}{2}\cdot \cfrac{df}{dx}\cdot g(x)+\cfrac{1}{2}\cdot \cfrac{dg}{dx}f(x)
8 0
4 years ago
Read 2 more answers
Find the percentage of $133.60 of $167.00
TiliK225 [7]

Answer:

  • 80%

Step-by-step explanation:

<u>Find the percentage of $133.60 of $167.00:</u>

  • 133.6/167*100% = 80%
4 0
3 years ago
Please help!!!!!!! For ten points
ziro4ka [17]

Answer:

A is the answer

Step-by-step explanation:

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.

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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