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lapo4ka [179]
3 years ago
6

Does anyone know the answer???

Mathematics
1 answer:
nikitadnepr [17]3 years ago
8 0
X= -1. That’s the only one that makes sense
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How many different​ three-digit numbers can be formed using the digits 1 comma 2 comma 9 comma 6 comma 4 comma 3 comma and 8 wit
lozanna [386]

Answer:

129 468  

Step-by-step explanation:

I'm not sure if you're supposed to reuse the same numbers just in a different Three digit number. Or if you're supposed to use the number one time and one time only. But if not here's there's some numbers that you could use

He basically all You have to do Is take the numbers and turning them into three digit numbers Without repetition.

Hope this helps you!

Also it's saying that 664 is not allowed Because it they are reusing the six When there's no Extra six to use. So remind you not to use the same number twice!

3 0
4 years ago
What type of correlation is shown in the graph ? positive no correlation linear negative
mario62 [17]

Answer:

positive

Step-by-step explanation:

8 0
3 years ago
Help please Thankyou
Ivahew [28]
Area = 1/2*a*P
(a = apothem , P= Perimeter)
P = Sum of all sides
   = 12*8
   = 96
Area = 1/2*30*96 = 1440

Hope this helps!
3 0
3 years ago
Which shows the list of numbers in order from least to greatest?
maks197457 [2]

Answer:

Absolute value

Step-by-step explanation:

Please mark Brainliest

7 0
3 years ago
Read 2 more answers
Question #1:
olganol [36]

Answer:

1. The sum of the residuals is always close to zero.

2.The coefficient of determination measures how much of the variation in the y-values is explained by the regression line.

3. In the equation of the least-squares regression line, y hat is a predicted value when x is known

Step-by-step explanation:

The least square regression line is a line that makes distance from data points to the regression line to be as minimal as possible. This line is a best fit for the data points. Let's say we have a collection of numbers and a scatter plot, this line is a line that exists and best fits the data.

Therefore, the least square regression line minimizes sum of squared error to be close to zero. R² measures the extent to which variations in the value of y is explained by the regression line. In the equation of this line, y hat is a predicted value when x is known.

6 0
3 years ago
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