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26 Jun 2015
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Linear Regression With R

Understanding Linear regression with R

Linear Regression deals with gathering the output of a dependent variable by evaluating how the independent variable is behaving under similar circumstances. Linear regression is based on the straight line equation which is y = mx+c. Here, y is the dependent variable and x is the independent variable.

Linear Regression is based on Ordinary Least Square Regression. It is important to know the following types of variables:

Dependent Variable – A Dependent Variable is the variable to be predicted or explained in a regression model. This variable is assumed to be functionally related to the independent variable.

Independent Variable – An Independent Variable is the variable related to the dependent variable in a regression equation. The independent variable is used in a regression model to estimate the value of the dependent variable.

Business Analytics with ‘R’ at Edureka will prepare you to perform analytics and build models for real world data science problems. It is the world’s most powerful programming language for statistical computing and graphics making it a must know language for the aspiring Data Scientists. ‘R’ wins strongly on Statistical Capability, Graphical capability, Cost and rich set of packages. This video explains how to implement linear regression using R.

 

Linear regression with R-Edureka
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Linear Regression With R | Edureka




This course is designed for professionals who aspire to learn ‘R’ language for Analytics. The course starts from the very basics like: Introduction to R programming, how to import various formats of Data, manipulate it, etc. to advanced topics like: Data Mining Technique, performing Predictive Analysis to find optimum results based on past data, Data Visualisation using R Commander, Deducer, etc.
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