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.
Answer:
B is 45 A is 135
Step-by-step explanation:
45 + 135 = 180
45 x 3 = 135
135 is three times as large as 45
135 and 45 are supplementary angles
Solve for x:
1.
4x - 7 = 3
Add 7 to both sides
4x = 10
Divide both sides by 4
x = 10/4
Simplify:
x = 5/2
Answer for question 1: x = 5/2
2.
13 + 2x/3 = 15
Multiply both sides by 3
39 + 2x = 45
Subtract 39 from both sides
2x = 6
Divide both sides by 2
x = 3
Answer for question 2: x = 3
3.
10x + 7 = 15
Subtract 7 from both sides
10x = 8
Divide both sides by 10
x = 8/10
Simplify
x = 4/5
Answer for question 3: x = 4/5
Answer:
c. 32 ounces
Step-by-step explanation:
Given that:
The weight of the Spot = 12 ounces
The weight of Rascal = 9.5 ounces; &
The weight of Socks = 10.2 ounces.
To find the litters' total weight, we will sum all the given number of the puppies.
i.e. Total weight of the litter = (12 + 9.5 + 10.2) ounces
Total weight of the litter = 31.7 ounces
Total weight of the litter 
32 ounces to the correct number of significant figures.
We will start off by simplifying 4/8 to 1/2
then we will multiply the fractions because it says "of"
1/2 × 1/6=1/12
therefore the answer is C. 1/12
