How to extract p-value and r-squared from a linear regression model in R? Explain

We can see the p-value and r-squared value using summary function

Let us explain with an example

x_data = cumsum(c(0, runif(100, -1, +1)))

y_data = cumsum(c(0, runif(100, -1, +1)))

fit = lm(y_data ~ x_data)

summary(fit)

Now summary function will show the following values

Standard error,estimates, t-values, p-values.

R-squared is calculated based on the following function

summary(fit)$r.squared

We can also use cor.test function to see the p-value and r-squared value

x_data <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1)

y_data<- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8)

mycor = cor.test(x_data,y_data)

model = lm(x_data~y_data)

# r and rsquared:

cor.test(x_data,y_data)$estimate ** 2

cor

summary(lm(x_data~y_data))$r.squared

# P.value

lmp(lm(x_data~y_data)) Chase's answer

cor.test(x_data,y_daa)$p.value