M = mass
p = density
v = volume
Yes, to find m it would be m = pv.
To find v that would be m/p.
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.
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3,6,12...
this is a geometric sequence with a common ratio of 2. That means u multiply each term by 2 to find the next term.
start with 3
3 * 2 = 6
6 * 2 = 12
12 * 2 = 24...this would be ur next term
so ur answer is : multiply by 2
Answer:
Step-by-step explanation:
lets have one side =a
P=3a+a+(17+a)=52
P=5a+17=52
5a=52-17
5a=35
a=7
second side=21
third side=24
Answer:
y=3x+4
idk what it has to be equivalent to...I just put it in y-intercept form
Step-by-step explanation:
