removing unnecessary newlines with shorter axis labels

Author: trevorcampbell

source/inference.Rmd

@@ -514,30 +514,30 @@ sample_estimates_500 <- rep_sample_n(airbnb, size = 500, reps = 20000) |>
 ## Sampling distribution n = 20
 sampling_distribution_20 <- ggplot(sample_estimates_20, aes(x = sample_mean)) +
   geom_histogram(fill = "dodgerblue3", color = "lightgrey") +
-  labs(x = "Sample mean price per night\n(dollars)", y = "Count") +
+  labs(x = "Sample mean price per night (dollars)", y = "Count") +
   ggtitle("n = 20") 
 
 ## Sampling distribution n = 50
 sampling_distribution_50 <- ggplot(sample_estimates_50, aes(x = sample_mean)) +
   geom_histogram(fill = "dodgerblue3", color = "lightgrey") +
   ylab("Count") +
-  xlab("Sample mean price per night\n(dollars)") +
+  xlab("Sample mean price per night (dollars)") +
   ggtitle("n = 50") +
   xlim(min_x(sampling_distribution_20), max_x(sampling_distribution_20))
 
 ## Sampling distribution n = 100
 sampling_distribution_100 <- ggplot(sample_estimates_100, aes(x = sample_mean)) +
   geom_histogram(fill = "dodgerblue3", color = "lightgrey") +
   ylab("Count") +
-  xlab("Sample mean price per night\n(dollars)") +
+  xlab("Sample mean price per night (dollars)") +
   ggtitle("n = 100") +
   xlim(min_x(sampling_distribution_20), max_x(sampling_distribution_20))
 
 ## Sampling distribution n = 500
 sampling_distribution_500 <- ggplot(sample_estimates_500, aes(x = sample_mean)) +
   geom_histogram(fill = "dodgerblue3", color = "lightgrey") +
   ylab("Count") +
-  xlab("Sample mean price per night\n(dollars)") +
+  xlab("Sample mean price per night (dollars)") +
   ggtitle("n = 500") +
   xlim(min_x(sampling_distribution_20), max_x(sampling_distribution_20))
 ```
@@ -881,7 +881,7 @@ tail(boot20000_means)
 
 boot_est_dist <- ggplot(boot20000_means, aes(x = mean)) +
   geom_histogram(fill = "dodgerblue3", color = "lightgrey") +
-  labs(x = "Sample mean price per night \n (dollars)", y = "Count") +
+  labs(x = "Sample mean price per night (dollars)", y = "Count") +
   theme(text = element_text(size = 12))
 
 boot_est_dist
@@ -900,7 +900,7 @@ sample_estimates <- samples |>
 sampling_dist <- ggplot(sample_estimates, aes(x = sample_mean)) +
   geom_histogram(fill = "dodgerblue3", color = "lightgrey") +
   ylab("Count") +
-  xlab("Sample mean price per night \n (dollars)")  
+  xlab("Sample mean price per night (dollars)")  
 
 annotated_sampling_dist <- sampling_dist +  
   xlim(min_x(sampling_dist), max_x(sampling_dist)) +