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Home/ Questions/Q 854385
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Editorial Team
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Editorial Team
Asked: May 15, 20262026-05-15T07:54:59+00:00 2026-05-15T07:54:59+00:00

I have data with a best fit line draw. I need to draw two

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I have data with a best fit line draw. I need to draw two other lines. One needs to have double the slope and the other need to have half the slope. Later I will use the region to differentially color points outside it as per:
Conditionally colour data points outside of confidence bands in R

Example dataset:

## Dataset from http://www.apsnet.org/education/advancedplantpath/topics/RModules/doc1/04_Linear_regression.html

## Disease severity as a function of temperature

# Response variable, disease severity
diseasesev<-c(1.9,3.1,3.3,4.8,5.3,6.1,6.4,7.6,9.8,12.4)

# Predictor variable, (Centigrade)
temperature<-c(2,1,5,5,20,20,23,10,30,25)

## For convenience, the data may be formatted into a dataframe
severity <- as.data.frame(cbind(diseasesev,temperature))

## Fit a linear model for the data and summarize the output from function lm()
severity.lm <- lm(diseasesev~temperature,data=severity)

# Take a look at the data
plot(
  diseasesev~temperature,
  data=severity,
  xlab="Temperature",
  ylab="% Disease Severity",
  pch=16,
  pty="s",
  xlim=c(0,30),
  ylim=c(0,30)
)
title(main="Graph of % Disease Severity vs Temperature")
par(new=TRUE) # don't start a new plot
abline(severity.lm, col="blue")
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  1. Editorial Team
    Editorial Team
    2026-05-15T07:54:59+00:00Added an answer on May 15, 2026 at 7:54 am
    diseasesev<-c(1.9,3.1,3.3,4.8,5.3,6.1,6.4,7.6,9.8,12.4)
    
    # Predictor variable, (Centigrade)
    temperature<-c(2,1,5,5,20,20,23,10,30,25)
    
    ## For convenience, the data may be formatted into a dataframe
    severity <- as.data.frame(cbind(diseasesev,temperature))
    
    ## Fit a linear model for the data and summarize the output from function lm()
    severity.lm <- lm(diseasesev~temperature,data=severity)
    
    line1 <- severity.lm$coefficients * c(1,2)
    line2 <- severity.lm$coefficients * c(1,.5)
    
    df <- as.data.frame(severity.lm[[12]])
    df2 <- adply(df,1,function(x) cbind(line1[2]*x[[2]]+line1[1], line2[2]*x[[2]]+line2[1]))
    
    plot(
      df2[df2[,1] >= min(df2[,c(3,4)]) & df2[,1] <= max(df2[,c(3,4)]),c(2,1)],
      xlab="Temperature",
      ylab="% Disease Severity",
      pch=16,
      pty="s",
      xlim=c(0,30),
      ylim=c(0,30)
    )
    title(main="Graph of % Disease Severity vs Temperature")
    par(new=TRUE) # don't start a new plot
    abline(severity.lm, col="blue")
    abline(line1, col="cyan")
    abline(line2, col="cyan")
    points(df2[df2[,1] < min(df2[,c(3,4)]) | df2[,1] > max(df2[,c(3,4)]),c(2,1)], pch = 16, col = 'red')
    

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