Linear Regression - Understanding the Algorithm and its Applications

Running head: LINER REGRESSION
LINER REGRESSION
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LINER REGRESSION1
Liner regression
Linear regression is one of the algorithms that is popular as well as understood in the
field of machine learning. linear regression had been developed within the field of statistics
besides being studied in the form of a model for the purpose of gaining knowledge regarding
relation between input as well as output variable that are numeric in nature (Fox, 2015). This
had been further bowed by the field of machine learning. It can be described as statistical as
well as machine learning algorithm.
How it is used and how it works
The model of linear regression are utilized for the purpose of showing as well as
predicting the relation between two factors or variables. The fact which is usually used for
prediction is known as the dependent variable. The factor which is used for predicting the
value of dependent variable is known as independent variable (Austin & Steyerberg, 2015).
Regression analysis is used for the purpose of researching because it establishes the fact that
a particular correlation exists among numerous variables. A particular line within the linear
regression which fits numerous data points properly might not represent anything regarding
the cause as well as effect relationship. In a linear regression every observation has 2 values.
Initial value is for variable that is dependent in nature and anther is for independent one
(Chiarini & Brunetti, 2019). In case of simple liner regression when the user has one output,
the user could use statistics for estimating numerous coefficients. This needs the user to
calculate various statistical properties from data like means, deviations, standard, covariance
and correlations. The data should be available for traversing as well as calculating the
statistics.
In case of ordinary least squares, the user makes use of numerous processes that help
in reducing the overall sum of the squared residuals. In case of more than one inputs, the user