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xz_007 [3.2K]
4 years ago
5

What is the range of 82, 135, 53, 44, 79, 36, 20, 56? 99 105 115

Mathematics
2 answers:
Mashcka [7]4 years ago
8 0
115 take the lowest number and the highest number and subtract so 135-20
leonid [27]4 years ago
5 0

Answer:

The range is 115

Step-by-step explanation: To find the range of a data set you subtract the lowest value from the highest value. In this case that would be 135 minus 20 which gives you a range of 115.

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kvasek [131]

Answer:

There is no correlation between price and amount of milk bought.

Step-by-step explanation:

''change in price does not imply that people will buy more or less milk."

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5 0
3 years ago
Here's the deal. I give you a question, you give me an answer. I give you points and Brainliest if possible. You use the points
olga55 [171]

Answer:

f(x) = -(x-3)^2 + 4

Step-by-step explanation:

(h; k) are the coordinates of the vertex.

On the graph are (3, 4), therefore we have:

f(x) = a(x-3)^2 + 4

We have the x- intercept (1,0) -> x=1; y=0.

Substitute them into the equation:

0 = a(1 - 3)^2 + 4

0 = a(-2)^2 + 4

4a + 4 = 0 | -4

4a = -4   |-4

a = -1

So, we have the answer:

f(x) = -(x-3)^2 + 4

5 0
3 years ago
Pedmas
baherus [9]

Answer:

Step-by-step explanation:

You do what's in the innermost brackets first, unless you have an unknown variable.

6 0
3 years ago
(0,5) (3,4) into an equation
kati45 [8]

Answer:

5-4 over/fraction of -3

Step-by-step explanation:

k that should be right just think of it as you're finding the slope of a line on a graph k

8 0
3 years ago
Regarding the violation of multicollinearity, which of the following description is wrong?
MA_775_DIABLO [31]

Complete question is;

Regarding the violation of multicollinearity, which of the following description is wrong?

a. It changes the intercept of the regression line.

b. It changes the sign of the slope.

c. It changes the slope of the regression line.

d. It changes the value of F-tests.

e. It changes the value of T-tests

Answer:

a. It changes the intercept of the regression line

Step-by-step explanation:

Multicollinearity is a term used in multiple regression analysis to show a high correlation between independent variables of a study.

Since it deals with independent variables correlation, it means it must be found before getting the regression equation.

Now, looking at the options, the one that doesn't relate with multicollinearity is option A because the intercept of the regression line is the value of y that is predicted when x is 0. Meanwhile, multicollinearity from definition above does in no way change the intercept of the regression line because it doesn't predict the y-value when x is zero.

7 0
3 years ago
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