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’m pretty sure it has potential energy. Because a charge battery can be charged. So it can have energy
I am unsure about the very last problem but I can help with the first two
1) (y+1)+4
If we combine the numbers 1 and 4, we get +5 and can isolate the numbers from the variable.
This would give us

2) (6*r)*7
remember that we do not have to explicitly state 6*r
Instead, we can write it as 6r
this helps us get rid of the parentheses
now we can write it as

I hope this helps!:)
QUESTION 1
The given expression is

The greatest common factor is
.
We factor to obtain;

QUESTION 2
The given quadratic equation is

We split the middle term to obtain

Factor by grouping;


Use zero product property;


QUESTION 3
The given system of equation is


If we multiply
by 3, we obtain;

If we multiply
by 4 we obtain;

Adding the last two equations will give us;

The y-variable is eliminated.
Answer:Multiply 3x+4y=−8
by 3. Multiply 7x−3y=6 by 4. Add the resulting equations together.