The linear regression method seeks to predict values of a(n) dependent variable based on values of a(n) independent variable.
According to the statement
we have to explain the linear regression method and explain the way by which this method is used to predict the values.
So, For this purpose we know that the
Linear regression is the most basic and commonly used predictive analysis. Regression estimates are used to describe data and to explain the relationship.
And
Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable.
from these definitions it is clear that the there is a presence of two types of variables which are dependent and independent variables.
So, The linear regression method seeks to predict values of a(n) dependent variable based on values of a(n) independent variable.
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Answer:
Step-by-step explanation:
- First, lets get rid of the fraction. I did this by multiplying both sides by
.
- We want to isolate
on one side of this equation. Let's put any values with on one side of the equation, and normal integers on the other.
- Divide both sides by
.
- If your teacher wants you to leave your final answer as an improper fraction, your final answer is this. If they want it to be a mixed number or decimal, your final answer will be:
Answer:x=13
BMC=75 degrees
Step-by-step explanation:
（x+2）+（5x+10）=90 degrees
so 6x+12=90
x=13
5x+10=5x13+10=75 degrees
Use the difference of squares factorization - that for any numbers a and b, (a-b)(a+b)=a^2-b^2.
We have:
(x^2+1)(x^2-1)=x^4-1
In addition:
(x-1)(x+1)=x^2-1, so we have:
(x^2+1)(x+1)(x-1)
As our complete factorization.
