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p values , r squared value and regression equation on ggplot : R programming

#ggplot2 #rprogramming #annotationonplot #p-value, # r-squaredvalue #datavisualisation #scatterplot #smoothline This video describes how to add p value, r-squared value and regression equation on ggplot2 plot. Scatter plot with p values, r-squared value and equation of linear regression model Data conc=c(0 ,0, 0,10,10,10,20,20,20,30,30,30,40,40,40,50,50,50, 60,60,60,70,70,70,80,80,80,90,90,90, 100, 100 ,100) OD = c(0.00,0.00,0.00,0.05,0.03,0.05,0.10,0.13,0.11,0.17, 0.15,0.15,0.23,0.23,0.22,0.28,0.29,0.27,0.41,0.46, 0.39,0.50,0.49,0.45,0.53,0.54,0.53,0.64,0.65,0.60, 0.74,0.69,0.73) df=data.frame(conc,OD) lmod= lm(OD~conc,df) summary(lmod) library(ggplot2) ggplot(df,aes(conc,OD))+ geom_point()+ geom_smooth(method="lm",se=0)+ theme_classic()+ annotate("text",x=c(50,50,50),y=c(0.7,0.65,0.6), label=c("p-value: 2.2e-16", "Adjusted R-squared: 0.9839", "OD=0.0073*conc-0.038")) 00:00 Data 00:40 scatter plot 02:50 linear regression model 04:40 adding text annotation 06:20 p-value on plot 06:40 R-squared value on plot 07:27 regression equation on plot 08:27 multi-labels in one annotation