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Bad White [126]
3 years ago
11

Is this correct and if not can you please correct it!

Mathematics
1 answer:
Tanzania [10]3 years ago
6 0

Answer:

Correct!

Step-by-step explanation:

That’s right

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Please. I only need help on parts A and B. Please DO NOT just answer with you don't know or something compelety random. Thanks.
Lilit [14]

Answer:    sir

Step-by-step explanation:

8 0
3 years ago
Volunteer drivers are needed to bring 80 students to the championship
s2008m [1.1K]

Answer:

c=5 v=10

Hoped I helped

7 0
3 years ago
What types of solutions does 6x^2 - 20x + 1 have?​
elena55 [62]

Answer:

2 real solutions

Step-by-step explanation:

We can use the determinant, which says that for a quadratic of the form ax² + bx + c, we can determine what kind of solutions it has by looking at the determinant of the form:

b² - 4ac

If b² - 4ac > 0, then there are 2 real solutions. If b² - 4ac = 0, then there is 1 real solution. If b² - 4ac < 0, then there are 2 imaginary solutions.

Here, a = 6, b = -20, and c = 1. So, plug these into the determinant formula:

b² - 4ac

(-20)² - 4 * 6 * 1 = 400 - 24 = 376

Since 376 is clearly greater than 0, we know this quadratic has 2 real solutions.

<em>~ an aesthetics lover</em>

3 0
3 years ago
5/7+(-1/3)-(-1/2)<br><br> Show work pls
ELEN [110]
30/42-14/42+21/42= 37/42
7 0
3 years ago
Which statements about residuals are true for the least-squares regression line? I. A random scattering of residuals indicates t
Daniel [21]

Answer:

II. The sum of the residuals is always 0.

Step-by-step explanation:

A least squares regression line is a standard technique in regression analysis used to make the vertical distance obtained from the data points running to the regression line to become very minimal or as small as possible.

For any least-squares regression line, the sum of the residuals is always zero.

Basically, residuals are used to measure or determine whether or not the line of regression is a good fit or match for the data by subtracting the difference between them i.e the predicted y value and the actual y value, for the x value respectively.

Hence, the statement about residuals which is true for the least-squares regression line is that the sum of the residuals is always zero (0).

7 0
3 years ago
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