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Kryger [21]
3 years ago
13

Use the information given to answer the question.

Mathematics
1 answer:
poizon [28]3 years ago
7 0

Answer:

What is the question? _______

You might be interested in
The sum of a number and 3:
fenix001 [56]

Answer:

x+3?

Step-by-step explanation:

honestly, there is not alot of information present here. so when a hear "a number" i think variable.... which would be set up as x+3

6 0
3 years ago
What value of x makes the equation true? 3x+21=8x-4
poizon [28]

Answer:

x=5  

Step-by-step explanation:

3 times 5= 15

15+21= 36

8 times 5 = 40

40-4=36

4 0
3 years ago
Read 2 more answers
Identify the scale factor
konstantin123 [22]
12 / 4 = 3.

Therefor, 3:1.
8 0
3 years ago
I need answers to both of the questions Please help
jolli1 [7]

Answer:

131 minutes, an = 15 + (n - 1)(4)

Step-by-step explanation:

each time she is increasing by 4 minutes

we can write this equation like this since we have the difference and the first part:

an = 15 + (n - 1)(4)

note

"an" (or ace of n)'s n is in subscript and is written just like a superscript but on the bottom

we can plug in this equation to find ace of 30 (a30)

15 + (30 - 1)(4)

15 + 29*4

116 + 15

a30 = 131

4 0
3 years ago
Read 2 more answers
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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