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3 years ago

I forgot how to do this. Can someone tell me how?

Mathematics

2 answers:

Lisa [10]3 years ago

8 0

Hello there!

8 = |5 - x|

Then flip it

|-x + 5| = 8

Then solve for the absolute value

We know either -x + 5 = 8 or -x+5 = -8

Let's solve the first possibility,which is -x + 5 = 8

-x + 5 = 8

-x= 8 - 5

-x = 3
Remember that we cannot leave the variable with a negative sign. To turn it into a positive sign, we need to divide both sides by -1

-x/-1 = 3/-1

x= -3

Now let's solve the second possibility which is -x+ 5 = -8

-x + 5 = -8

-x = -8 - 5

-x = -13

again, we cannot leave it with the negative sign so we gonna do the same thing which is divide both sides by -1

-x/-1 = -13/-1

x = 13

Thus, the answer is x= -3 or x = 13

The correct answer is option D

Best of luck with your studies!

Katyanochek1 [597]3 years ago

7 0

Hey there, CrisisOnCats!

Absolute value is when any value that's inside the box, positive or negative, will always come out as positive.
For this one, you solve it as a normal equation, solving for x.
So, 8 = 5 - x
8-5 = 5-5 - x
3 = -x
x = -3
One value can be -3
To find the other value, just find any value that's equal to 8 when added or subtracted from 5, negative or positive.
We have 13 in this case.
5 - 13 is equals to -8 but since it's absolute value, it would be positive 8.
So, the answer is D

Thank you for using Brainly.
See you soon!

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3 years ago

Factorise: 5(2^n)+2^n+2

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Step-by-step explanation:

coefficient of the first term:

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coefficient of the last term:

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Alternative method:

Treat the given expression as a quadratic set equal to zero, with the form

a n 2 + b n + c

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3 years ago

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Answer:

Step-by-step explanation:

Hello!

Given the data for the variables:

Y: Selling price of a house on the shore of Tawas Bay

X₁: Number of bathrooms of a house on the shore of Tawas Bay.

X₂: Square feet of a house on the shore of Tawas Bay.

X₃: Number of bedrooms of a house on the shore of Tawas Bay.

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a. Using software I've entered the raw data and estimated the regression coefficients:

^α= a= -5531.01

Represents the mean selling price of the houses when 0 bathrooms, 0 square feet and 0 bedrooms.

^β₁= b₁= -1386.21

Represents the modification of the mean selling price of the houses when the number of bathrooms increases in one unit and the square feet and number of bedrooms remain unchanged.

^β₂= b₂= 60.28

Represents the modification of the mean selling price of the houses when the square feet increase in one unit and the number of bathrooms and bedrooms remain unchanged.

^ β₃= b₃= 54797.08

Represents the modification of the mean selling price of the houses when the number of bedrooms increase in one unit and the number of bathrooms and square feet of the houses remain unchanged.

^Y= -5531.01 -1386.21X₁ + 60.28X₂ + 54797.08X₃

R²= 0.55

R²Aj= 0.49

The coefficient of determination gives you an idea of how much of the variability of the dependent variable (Y) is due to the explanatory variables. Each time you add another explanatory variable to the regression the coefficient increases regarding of real contribution of the new variable. This could lead to thinking (wrongly) that the new variables are good to explain the dependent variable.

The adjusted coefficient of determination is a correction made to the raw coefficient of determination to have a more unbiased estimation of the effect the independent variables have over the dependent variable.

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d) and f)

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