Concept:
The greatest rate of increase of a scalar function occurs in the direction of the gradient vector.
For a scalar function \(f(x,y,z)\),
\[
\nabla f=
\left(
\frac{\partial f}{\partial x},
\frac{\partial f}{\partial y},
\frac{\partial f}{\partial z}
\right)
\]
The magnitude of the gradient gives the maximum directional derivative:
\[
D_{\max}f=|\nabla f|
\]
Hence we first compute the gradient and then evaluate its magnitude at the given point.
Step 1: Writing the given function.
We are given:
\[
f=xy^2z^3
\]
We now calculate all first-order partial derivatives carefully.
Step 2: Finding \( \dfrac{\partial f}{\partial x} \).
Treating \(y\) and \(z\) as constants:
\[
\frac{\partial f}{\partial x}=y^2z^3
\]
Substitute:
\[
y=-1,\quad z=-2
\]
Then:
\[
=(-1)^2(-2)^3
\]
\[
=1(-8)
\]
\[
=-8
\]
Step 3: Finding \( \dfrac{\partial f}{\partial y} \).
Differentiate with respect to \(y\):
\[
\frac{\partial f}{\partial y}=2xyz^3
\]
Substitute the point:
\[
2(0)(-1)(-8)=0
\]
Thus:
\[
\frac{\partial f}{\partial y}=0
\]
Step 4: Finding \( \dfrac{\partial f}{\partial z} \).
Differentiate with respect to \(z\):
\[
\frac{\partial f}{\partial z}=3xy^2z^2
\]
Substitute the point:
\[
3(0)(1)(4)=0
\]
Hence:
\[
\frac{\partial f}{\partial z}=0
\]
Step 5: Constructing the gradient vector.
Therefore:
\[
\nabla f(0,-1,-2)=(-8,0,0)
\]
Step 6: Finding the magnitude of the gradient.
The magnitude is:
\[
|\nabla f|
=
\sqrt{(-8)^2+0^2+0^2}
\]
\[
=
\sqrt{64}
\]
\[
=8
\]
Hence the greatest rate of increase is:
\[
\boxed{8}
\]
Therefore the correct answer is:
\[
\boxed{(2)\;8}
\]