I’m not 100% sure but I think it’s y=5x+20
Answer:
Step-by-step explanation:
So there are two types of variables we need to focus on, the first is the dependent variable, the second is the independent variable ( which is the one in question). You asked about it in relation to mathematics, although even across the board, in science they both really mean the same thing. Here's an example, say you are taking a test, and the rubric for grading the test is 5 points (p) for every question (q) answered correctly. So given that information you can conclude that (p) is equal to 5 x the amount of questions you got right (p = 5q). The amount of points in this equation relies on how many questions you get right, you can't logically say that question (q) is equal to 5 points (p), because the questions don't depend on the points, the points depend on the amount of questions you get right. So that means since the points (p) depend on the # of questions you answered correctly, it is the dependent variable, there for by process of elimination you're independent variable is (q) since they don't rely on the points, the points rely on the questions. It all boils down to how well you can recognize this, and how complicated your question is, but hopefully this provided some insight.
Answer:
(1) Not conditional, 5/8
(2) Not conditional, 1/12
(3) Conditional, 1/18
Step-by-step explanation:
Fraction of cars sold
Altima = 1/2
Maxima = 1/3
Sentra = 1 - (1/2 + 1/3) = 1 - 5/6 = (6 - 5)/6 = 1/6
Fraction of cars sold with moon roof
Altima = 3/4 × 1/2 = 3/8
Maxima = 1/2 × 1/3 = 1/6
Sentra = 1/2 × 1/6 = 1/12
(1) Probability (a randomly selected car has a moon roof) = 3/8 + 1/6 + 1/12 = (9+4+2)/24 = 15/24 = 5/8
(2) Probability (a randomly selected car has a moon roof given it is Sentra) = 1/12
(3) Probability (a randomly selected car is a Maxima if it has a moon roof) = 1/3 × 1/6 = 1/18
A conditional probability uses if (as a condition) in making statements or asking questions
An unconditional probability makes statement or ask question without the use of condition (if)
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.
9514 1404 393
Answer:
Step-by-step explanation:
The outside factor multiplies each term in parentheses.
a) 2(b+c) = 2b +2c
b) 5(7h +3m) = 5×7h +5×3m = 35h +15m
c) e(f +g) = ef +eg
