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ELEN [110]
3 years ago
10

Solve using the quadratic formula: (Standard form 1st!) 2x^2-2x=24

Mathematics
1 answer:
Flura [38]3 years ago
5 0

Answer:

4, -3

Step-by-step explanation:

The quadratic formula is \frac{-b+-\sqrt{b^2-4ac} }{2a}.

When using the formula for both the negative and positive value of the sqrt, you will get:

x = 4, -3

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NEED ASAP!! ILL GIVE YOU 30 points!!
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Answer:

X+Y is greater then or equal to 8

Step-by-step explanation:

In total she wants to sell <u>at le</u><u>ast</u> 8 items which implies shes willing to sell more (so greater or equal to) then it's adding X+Y bc those are the items that she is selling

5 0
3 years ago
In a math class with 23 students, a test was given the same day that an assignment
ddd [48]

Answer:

8

Step-by-step explanation:

23 students -15 students =8students

3 0
3 years ago
If f^-1(x) is the inverse of f(x), which statement must be true?
k0ka [10]
F(f-1x)   will be equal to x

take a simple example 

f(x) = 2x

so x = f(x) / 2

 f-1(x) = x/2

f(f-1x) =  2 ( x/2)  = 2 * x/2 = x
5 0
2 years ago
Read 2 more answers
I need help answering this question. Any ideas on what it could be?
Lesechka [4]
Is this for a test/exam?
4 0
2 years ago
. The estimate regression equation for a model involving two independent variables and 10 observations follows.y = 29.1270 + 0.5
beks73 [17]

Answer:

b) y = 289.815 when x_1 = 180 \text{ and } x_2 = 310

Step-by-step explanation:

We are given the following information in the question:

y = 29.1270 + 0.5906x_1 + 0.4980x_2

where y is the dependent variable,

x_1, x_2 are the independent variable.

The multiple regression equation is of the form:

y = b_0 + b_1x_1 + b_2x_2

where,

b_0: is the intercept of the equation and is the value of dependent variable when all the independent variable are zero.

b_1: It is the slope coefficient of the independent variable x_1.

b_2: It is the slope coefficient of the independent variable x_2.

  • The regression coefficient in multiple regression is the slope of the linear relationship between the dependent and the part of a predictor variable that is independent of all other predictor variables.

Comparing the equations, we get:

b_1 = 0.5906\\b_2 = 0.4980

  • This means holding x_2 constant, a change of one in x_1 is associated with a change of 0.5906 in the dependent variable.
  • This means holding x_1 constant, a change of 1 in x_2 is associated with a change of 0.4980 in the dependent variable.

b) We have to estimate the value of y

y = 29.1270 + 0.5906(180) + 0.4980(310) = 289.815

3 0
2 years ago
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