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:
yes jess does have enough for her sandbox
Step-by-step explanation:
I did this test to and jess does indeed have enough for the sandbox
percent ---------------- quantity
Acid type I 60.00% ---------------- x liters
acid type II 30.00% ------ 60 - x liters
Mixture 40.00% ---------------- 60
Total 60 liters
60.00% x + 30.00% ( 60 - x ) = 40.00% * 60
60 x + 30 ( 60 - x ) = 2400
60 x + 1800 - 30 x = 2400
60 x - 30 x = 2400 - -1800
30 x = 600
/ 30
x = 20 liters 60.00% Acid type I
40 liters 30.00% acid type II
brainliest plzz
Answer:
42 games
Step-by-step explanation:
From the ratio, we can deduce that;
For every 3 games A won, B won 1
Thus, if B won 10, then A has won 3(10) = 30
From the second part;
For every 1 game won by C, B won 5
since B won 10, then C won 10/5 = 2
So the total number of games won is;
A + B + C
= 2 + 30 + 10 = 42 games
Answer:
True
Step-by-step explanation:
