Linear Regression with R – Part 2 | Data Awareness Programme

ByHariharan Rajendran

In this post, let me explain how to use R programming for linear regression.

I am taking the same dataset in R to produce the linear regression.

Run the below codes.

Year<- c(2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010)

SalesAmount<-c(1450,1486,1560,1200,1205,1100,1150,1750,1650,1500,1900)

#linear regression

result<-lm(SalesAmount~Year)

#display coefficient

result

# new value for year 2011

year2011 <- data.frame(Year=2011)

year2011

#predict the sales amount.

predict (result,year2011)

About the Author

Hariharan Rajendran author

Hariharan Rajendran is a Microsoft Certified Trainer and Lead BI Solutions Consultant with 8+ years of experience in Database, BI and Azure platforms. Hariharan is also an active community leader, speaker & organizer and leads the Microsoft PUG (Power BI User Group – Chennai), SQLPASS Power BI Local Group – Chennai and an active speaker in SQL Server Chennai User Group and also a leader in Data Awareness Program worldwide events. Hariharan also frequently blogs (www.dataap.org/blog), provides virtual training (on ad-hoc basis) on Microsoft Azure, Database Administration, Power BI and database development to worldwide clients/audience.

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Linear Regression with R – Part 2