Essentially, what you need to do is ensure that both sides cancel each other out to make 0 = 0
An example:
2(x + y) + 4 = (4x + 4y + 8)/2
2x + 2y + 4 = 2x + 2y + 4
0 = 0
Answer:
thus the father is 64 years and son is 37years
Step-by-step explanation:
Let father be X and son be y
X=27+Y...........(I)
X-10=2(Y-10)
putting the value of X from eqn(I)
27+Y-10=2Y-20
Y+17=2Y-20
17+20=2Y-Y
37=y
X=27+Y
X=64
Answer: B
explanation:
anything equal to or above 212 is boiling
good luck!
Answer:
<em>In statistics, linear regression is a linear approach to modelling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.</em>
