Ideally good questions are those that pose the problem by providing a reproducible example. Anyway, I have approached this problem in two steps;
Step 1: Determine the linear regression model;
fit1 <- lm(Sepal.Length ~ Petal.Width, data = iris)
Step 2: Plot the model;
library (ggplot2)
ggplot(fit1$model, aes_string(x = names(fit1$model)[2], y = names(fit1$model)[1])) +
geom_point() +
stat_smooth(method = "lm", col = "red") +
labs(title = paste("Adj R2 = ",signif(summary(fit1)$adj.r.squared, 5),
"Intercept =",signif(fit1$coef[[1]],5 ),
" Slope =",signif(fit1$coef[[2]], 5),
" P =",signif(summary(fit1)$coef[2,4], 5)))
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