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.
Learn more about Linear regression here brainly.com/question/25987747
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Answer:
f(h) = 0.004s + 37
Step-by-step explanation:
The correct representation of the height of the plant is;
f(h) = 0.004s + 37
Given parameters;
Height of plant = 37cm
Rate of growth = 0.004cm/hr
Number of hours of sunlight = s
To solve this problem, the height of the plant is directly dependent on the amount of sunlight;
f(h) signifies that height is a function
The height of the plant is 37cm;
f(h) = 37
The plant grows at a rate of 0.004cm/hr; number of hours of sunlight is s;
0.004s
Therefore;
f(h) = 37 + 0.004s
Answer:
i think 150
Step-by-step explanation:
sorry if its wrong im just trying to help
Answer:
A.) r = 0.17454
Step-by-step explanation:
Got it right on my text
