6. Linear Regression

6. Linear Regression

• It is a type of predictive analysis
• Use linear equation to predict one variable from knowledge of other variables.
• Simple linear regression considers a single regressor variable X and a single response variable Y
• P-value has to less than 0.05 to ensure that the variable is significant

6.1 Linear Regression in Excel

• Data -> Data Analysis -> Regression
• If x = 85, y is 78.12
  • y = ax + b = 0.777(85) + 12.06 = 78.12
• Referring to the diagram below for summary output of excel:

6.2 Linear Regression in R-Programming

• x <- c(77,50,71,72,81,94,96,99,67)
• y <- c(82,66,78,34,47,85,99,99,68)
• fit <- lm(y~x)
• fit$coefficient
• OR summary(fit)

(Intercept) x

12.0623211 0.7771416

• y = 0.7771416x + 12.0623211
• Therefore when x is 85, y = 78.12
  • y = 0.7771416(85) + 12.0623211