Why are unbiased estimators preferred over biased estimators? A. Unbiased estimators behave with reliable results, where as biased estimators are inconsistent.
B. Unbiased estimators require a greater sample size which gives greater accuracy over biased estimators.
C. Unbiased estimators retain original distribution of the same, where as biased estimators follow a normal distribution
D. Unbiased estimators follow the normal distribution, where as biased estimators follow original distribution.

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so firstly, we need to isolate the y variables to be able to solve these inequalities. firstly, add 0.5x on both sides of the first inequality and subtract 1.5x on both sides of the second inequality:

now since the slope is positive for the first inequality, this means that the line going upwards belongs to the first inequality, and the line going downwards belongs to the second inequality.

next, since y ≥ in the first inequality, this means that the shaded region will be above the first inequality's line, thus shading regions a and b.

next, since y ≤ in the second inequality, this means that the shaded region is going to be below this line, thus shading regions a and c.

since both lines shade region a, this means that region a is the solution.

step-by-step explanation:

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the surface area is 124cm²

step-by-step explanation:

length: 4cm

width: 9cm

height:   2cm