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Olin [163]
3 years ago
5

0.006 0.06 0.6 6 what's next

Mathematics
2 answers:
irina [24]3 years ago
6 0
60 600 6000 60000 600000
PIT_PIT [208]3 years ago
3 0
6.0 goes next :) hope this helped
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A<br> is part of a line with one endpoint but goes on<br> forever in the other direction.
hjlf

Answer:

A ray

Step-by-step explanation:

A ray is a line segment that has only one endpoint. A ray is infinite in one direction. That means that it goes on forever in one direction.

7 0
3 years ago
There are 8 dinner rolls in a package. How many packages will be needed so that 64 people can get 2 dinner rolls?
rodikova [14]
8 per package.

64*2= 128

Now we need to divide 128 by 8 to see how many packages we will need. 

128/8= 16

Now we know that we need 16 packages so that we can feed 64 people 2 dinner rolls.

Final answer: 16 packages
4 0
3 years ago
Read 2 more answers
What is 8-4/5f&gt;-14-2f
SpyIntel [72]
8-\frac{4}{5}f>-14-2f\ \ \ \ \ |\cdot5\\\\40-4f>-70-10f\\\\-4f+10f>-70-40\\\\6f>-110\ \ \ \ \ |:6\\\\f>-\frac{110}{6}\\\\f>-\frac{55}{3}\\\\f\in(-\frac{55}{3},\infty)
5 0
3 years ago
Read 2 more answers
4. x^2+13x=-42
Mrrafil [7]
x^2+13x=-42\ \ \ |+42\\\\x^2+13x+42=0\\\\x^2+6x+7x+42=0\\\\x(x+6)+7(x+6)=0\\\\(x+6)(x+7)=0\iff x+6=0\ \vee\ x+7=0\\\\x=-6\ \vee\ x=-7

Anaswer: <span>a. x = -6 or x = -7</span>

8 0
3 years ago
g Minimizing the sum of the squared deviations around the line is called: predictor regression. mean squared error technique. le
Alex787 [66]

Minimizing the sum of the squared deviations around the line is called Least square estimation.

It is given that the sum of squares is around the line.

Least squares estimations minimize the sum of squared deviations around the estimated regression function. It is between observed data, on the one hand, and their expected values on the other. This is called least squares estimation because it gives the least value for the sum of squared errors. Finding the best estimates of the coefficients is often called “fitting” the model to the data, or sometimes “learning” or “training” the model.

To learn more about regression visit: brainly.com/question/14563186

#SPJ4

3 0
2 years ago
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