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.
There are 70 employees who work at Stalling Printing.
Take note that the 63 employees who attended the meeting represents 90% of the total number of employees working at Stalling Printing. To get the total number of employees or the 100% number of employees, divide 63 by its percentage, 90%.
63/90% or 63 / 0.90 = 70 total number of employees.
Out of 70 employees; 63 employees attended the meeting and 7 employees did not.
Answer:
=42x2+1
Step-by-step explanation:
6x2+36x2+12x+6
=42x2+1
They increased it by $10.
It ended up costing $60.
Hope this helps.
Answer:
5400
Step-by-step explanation:
Let x represent the cost of a chair and y represent the cost of a table. We can use this to set up a system of equations:
7x=2y
6x+5y=10575
We can solve this system using substitution.
Start by rewriting the first equation in terms of x.
Substitute this into the second equation:
Multiply both sides by 7
Divide both sides by 47
This means...
Divide both sides by 7
One chair costs 450. Now, multiply this number by 12 to find the cost of 12 chairs.
12 chairs cost 5400.
