Answer:
Step-by-step explanation:
Given that:
where;
the top vertex = (0,0,1) and the base vertices at (0, 0, 0), (1, 0, 0), (0, 1, 0), and (1, 1, 0)
As such , the region of the bounds of the pyramid is: (0 ≤ x ≤ 1-z, 0 ≤ y ≤ 1-z, 0 ≤ z ≤ 1)
![\iiint_W (x^2+y^2) \ dx \ dy \ dz = \int ^1_0 \ dz \ ( \dfrac{(1-z)^3}{3} \ y + \dfrac {(1-z)y^3)}{3}] ^{1-x}_{0}](https://tex.z-dn.net/?f=%5Ciiint_W%20%28x%5E2%2By%5E2%29%20%5C%20dx%20%5C%20dy%20%5C%20dz%20%3D%20%5Cint%20%5E1_0%20%20%5C%20dz%20%5C%20%20%28%20%5Cdfrac%7B%281-z%29%5E3%7D%7B3%7D%20%5C%20y%20%2B%20%5Cdfrac%20%7B%281-z%29y%5E3%29%7D%7B3%7D%5D%20%5E%7B1-x%7D_%7B0%7D)
26 skate and with wunno when ask what about the gc and the park to park in
Answer:
9/10
1/2+2/5
Since these fractions have different denominators, we need to find the least common multiple of the denominators.The least common multiple of 2 and 5 is 10, so we need to multiply to make each of the denominators = 10
1/2 ∗ 5/5 = 5/10
5/2∗ 2/2= 4/10
Since these fractions have the same denominator, we can just add the numerators
5/10+ 4/10 = 9/10
When calculating correlation and regression both sets of data must be Statistical.
According to the statement
we have to find the type of data when we calculate the correlation and regression both sets.
so, The difference between these two statistical measurements is that correlation measures the degree of a relationship between two variables (x and y), whereas regression is how one variable affects another.
And when we calculate both then data sets must be a statistical data. because correlation summarizing direct relationship between two variables and regression predict or explain numeric response. So, without statistical data this is not possible to calculate correlation and regression both sets.
so, When calculating correlation and regression both sets of data must be Statistical.
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