Recall the Akaike information Criterion (AIC) as well as the related Bayesian Information Criterion (BIC) from our study of Variable Selection and Model Building. Without heavy mathematical notation, explain how both the AIC and BIC emphasize goodness-of-fit of a regression model while also controlling model complexity. Why would we wish to do this (that is, to promote goodness-of-it while at the same time controlling model complexity)

Step-by-step explanation:

To check out how efficient or accurate a model is, we use the akaike information criterion or the Bayesian. If the AIC or BIC are lower, then this model would be better. They are also used to control for model complexity

Akaike information criterion = 2k-2ln where k is the number of parameter. A higher k gives a higher AIC.

In the real world complex models are discouraged and avoided since

1. They cause data to be over fitted and can capture noise and information from this data.

2. They are complex and therefore difficult to interpret

3. They consume a lot of time and computing them has several inefficiencies.

Using these two as measure of performance, we can select optimal choice of independent variable.

With forward/backward regression, we are able to put new variables in the model or remove from it. The best is the one with lowest AIC.

3. parallelogram

step-by-step explanation:

we turn each of our sides into direction vectors

ab=b-a=(3 - 7, 1 - 0) = (-4, 1)

bc=c-b=(1,6)

cd=d-c=(4,-1)

da=a-d=(-1,-6)

we see how the opposite sides have negated direction vectors; this is characteristic of a parallelogram.   we have congruent sides ab=cd and bc=da with unequal lengths because 1^2+6^2 is different from (-4)^2+1^2.   so it's not a square or a rhombus.  

we check the dot product of direction vectors of adjacent sides.   we have

ab dot bc = -4(1) + 1(6) = 2

that's not zero so the sides are not perpendicular.   we've ruled out rectangle.

the direction vectors indicate two pairs of congruent parallel sides, so we choose parallelogram over trapezoid.

f(x) is the value of the function. b is the value of the function when x equals zero or the y-coordinate of the point where the line crosses the y-axis in the coordinate plane.

step-by-step explanation:

hope this !