Answer:
9:01
2:36
3:40
Step-by-step explanation:
Answer:
Bias is the difference between the average prediction of our model and the correct value which we are trying to predict and variance is the variability of model prediction for a given data p[oint or a value which tells us the spread of our data the variance perform very well on training data but has high error rates on test data on the other hand if our model has small training sets then it's going to have smaller variance & & high bias and its contribute more to the overall error than bias. If our model is too simple and has very few parameters then it may have high bias and low variable. As the model go this is conceptually trivial and is much simpler than what people commonly envision when they think of modelling but it helps us to clearly illustrate the difference bewteen bias & variance.
i dont have time to do all of it (sorry)
but this is how you do the point and slope questions:
use the equation: y-y1 = m(x - x1)
y1 is the y point you are given
x1 is the x point you are given
m is your slope
substitute all of those in from the question
the first one is:
y --4 = -5/6(x-8)
-- turns into a plus so the answer would be
y+4 = -5/6(x-8)
2x+4x-4=2+4x
2x+4x-4x=2+4
2x=6
x=3
25-x=15-3x-10
3x-x= 15-10-25
2x= -20
x= -10
4x=2x+2x+5x-5x
2x+2x+5x-5x-4x
0 . no solution
Answer would definitely be A
