# How to Plot a Linear Regression Line in ggplot2 (With Examples)

You can use the R visualization library ggplot2 to plot a fitted linear regression model using the following basic syntax:

```ggplot(data,aes(x, y)) +
geom_point() +
geom_smooth(method='lm')
```

The following example shows how to use this syntax in practice.

### Example: Plot a Linear Regression Line in ggplot2

Suppose we fit a simple linear regression model to the following dataset:

```#create dataset
data <- data.frame(y=c(6, 7, 7, 9, 12, 13, 13, 15, 16, 19, 22, 23, 23, 25, 26),
x=c(1, 2, 2, 3, 4, 4, 5, 6, 6, 8, 9, 9, 11, 12, 12))

#fit linear regression model to dataset and view model summary
model <- lm(y~x, data=data)
summary(model)

Call:
lm(formula = y ~ x, data = data)

Residuals:
Min      1Q  Median      3Q     Max
-1.4444 -0.8013 -0.2426  0.5978  2.2363

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)  4.20041    0.56730   7.404 5.16e-06 ***
x            1.84036    0.07857  23.423 5.13e-12 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1.091 on 13 degrees of freedom
Multiple R-squared:  0.9769,	Adjusted R-squared:  0.9751
F-statistic: 548.7 on 1 and 13 DF,  p-value: 5.13e-12
```

The following code shows how to visualize the fitted linear regression model:

```library(ggplot2)

#create plot to visualize fitted linear regression model
ggplot(data,aes(x, y)) +
geom_point() +
geom_smooth(method='lm') ``` By default, ggplot2 adds standard error lines to the chart. You can disable these by using the argument se=FALSE as follows:

```library(ggplot2)

#create regression plot with no standard error lines
ggplot(data,aes(x, y)) +
geom_point() +
geom_smooth(method='lm', se=FALSE) ``` Lastly, we can customize some aspects of the chart to make it more visually appealing:

```library(ggplot2)

#create regression plot with customized style
ggplot(data,aes(x, y)) +
geom_point() +
geom_smooth(method='lm', se=FALSE, color='turquoise4') +
theme_minimal() +
labs(x='X Values', y='Y Values', title='Linear Regression Plot') +
theme(plot.title = element_text(hjust=0.5, size=20, face='bold')) ``` Refer to this post for a complete guide to the best ggplot2 themes.