Basic curves with ggplot

Here is a list of basic curves drawn with ggplot2.

the graphic:

```{r}
#| warning: false
#| error: false
library(tidyverse)
```

Normal Distribution

We can draw the normal curve changing the stat_function of the graphic:

```{r}
#| warning: false
#| error: false

normal_curve_plot <- 
  ggplot(tibble(x = c(-5, 5)), 
         aes(x = x)) +
  stat_function(fun = dnorm, color = "darkred") +
  theme_minimal()
normal_curve_plot
```

Student Distribution

For the student distribution we need to define the function and the degree of freedom (df):

```{r}
#| warning: false
#| error: false

t_curve_plot <- 
  ggplot(tibble(x = c(-5, 5)), 
         aes(x = x)) +
  stat_function(fun = dt, args = list(df = 3), color = "steelblue") +
  theme_minimal()
t_curve_plot
```

F Distribution

For the F distribution we need to define the function and the 2 degree of freedom parameters (df1 and df2):

```{r}
#| warning: false
#| error: false

f_curve_plot <- 
  ggplot(tibble(x = c(-5, 5)), 
         aes(x = x)) +
  stat_function(fun = df, args = list(df1 = 2, df2 = 50), color = "gray") +
  theme_minimal()
f_curve_plot
```

Chi-Squared Distribution

For the chi-squared distribution we need to define the function, the degree of freedom (df), and the non-centrality parameter (ncp):

```{r}
#| warning: false
#| error: false

chi_curve_plot <- 
  ggplot(tibble(x = c(-5, 5)), 
         aes(x = x)) +
  stat_function(fun = dchisq, args = list(df = 3, ncp = 0), color = "darkorange") +
  theme_minimal()
chi_curve_plot
```

All together

All together now.

```{r}
#| warning: false
#| error: false

all_curve_plot <- 
  ggplot(tibble(x = c(-5, 5)), 
         aes(x = x)) +
  stat_function(fun = dchisq, args = list(df = 3, ncp = 0), color = "darkorange") +
  stat_function(fun = df, args = list(df1 = 2, df2 = 50), color = "gray") +
    stat_function(fun = dt, args = list(df = 3), color = "steelblue") +
  stat_function(fun = dnorm, color = "darkred") +
  theme_minimal()
all_curve_plot
```