diff --git a/bs/.development/ECDF.R b/bs/.development/ECDF.R
new file mode 100644
index 0000000..e4e2331
--- /dev/null
+++ b/bs/.development/ECDF.R
@@ -0,0 +1,68 @@
+# Calculation of empirical cumulative distribution function (ECDF)
+
+n <- 20
+randoms <- runif(n, 1, 10)
+how_often <- sample.int(3, n, replace = TRUE)
+sample <- numeric(sum(how_often))
+counter <- 1
+for (i in 1:n) {
+  sample[counter:(counter + how_often[i] - 1)] <- rep(randoms[i], how_often[i])
+  counter <- counter + how_often[i]
+}
+sample <- sort(sample)
+unique_sample <- unique(sample)
+total_observations <- length(sample)
+ecdf <- sapply(unique_sample, function(x) {
+  sum(sample <= x) / total_observations
+})
+ecdf
+
+df <- data.frame(x = unique_sample, y = ecdf)
+library(ggplot2)
+ggplot(data = df, aes(x = x, y = y)) +
+  geom_step() +
+  geom_label(aes(label = round(x, 2)))
+
+# If the ECDF value is F_n(5) = 0.5
+# it means 50% of the sample values are less than or equal to 5.
+# The CDF corresponds to a theoretical probability distribution (e.g. normal, exponential).
+# It is the integral of the probability density function (PDF)
+
+# PDF are the d-functions in R
+# CDF are the p-functions in R
+# The q-functions in R compute the quantiles of a distribution.
+# They are the inverse of the CDF.
+# In simple terms, the quantile tells you the value of x
+# below which a proportion p of the data lies.
+
+# Empirical quantiles
+n <- 20
+randoms <- runif(n, 1, 10)
+how_often <- sample.int(3, n, replace = TRUE)
+sample <- numeric(sum(how_often))
+counter <- 1
+for (i in 1:n) {
+  sample[counter:(counter + how_often[i] - 1)] <- rep(randoms[i], how_often[i])
+  counter <- counter + how_often[i]
+}
+sample <- sort(sample)
+n <- length(sample)
+
+ps <- seq(0, 1, 0.1)
+qq <- data.frame(
+  empirical = numeric(length(ps)),
+  theoretical = numeric(length(ps))
+)
+for (i in 1:length(ps)) {
+  # i = p * (n + 1)
+  idx <- ps[i] * (n + 1)
+  if (floor(idx) == 0) {
+    idx <- 1
+  } else if (ceiling(idx) >= n) {
+    idx <- n
+  }
+  qq$empirical[i] <- (sample[ceiling(idx)] + sample[floor(idx)] ) / 2
+  qq$theoretical[i] <- qunif(p = ps[i], min = 1, max = 10)
+}
+plot(qq$theoretical, qq$empirical)
+abline(0, 1, col = "red", lty = 2)
diff --git a/bs/.development/overview_doseresponse.R b/bs/.development/overview_doseresponse.R
deleted file mode 100644
index 86032d7..0000000
--- a/bs/.development/overview_doseresponse.R
+++ /dev/null
@@ -1,22 +0,0 @@
-df <- read.csv("bs/inst/test_data/lc50_testfile.csv", header = TRUE, sep = ";")
-head(df)
-res <- bs:::ic50(df, "abs", "conc", "names", "neg", "pos")
-resDF <- lapply(res, function(x) {
-  if (inherits(x, "errorClass")) {
-    return(NULL)
-  }
-  return(x[[1]])
-})
-resDF <- resDF[!is.null(resDF)]
-resDF <- resDF[!sapply(resDF, is.null)]
-resDF <- Reduce(rbind, resDF)
-resP <- lapply(res, function(x) {
-  if (inherits(x, "errorClass")) {
-    return(NULL)
-  }
-  return(x[[2]])
-})
-resP <- resP[!is.null(resP)]
-resP <- resP[!sapply(resP, is.null)]
-
-bs:::create_plot_pages(resP)
diff --git a/bs/.development/run_app.R b/bs/.development/run_app.R
deleted file mode 100644
index 4fca893..0000000
--- a/bs/.development/run_app.R
+++ /dev/null
@@ -1,9 +0,0 @@
-# Run in browser
-
-# setwd("/home/konrad/Documents/Biostats")
-# shinylive::export("./App", "docs", verbose = TRUE)
-# httpuv::runStaticServer("docs")
-
-Sys.setenv(RUN_MODE = "BROWSER")
-library(bs)
-run_app()
diff --git a/bs/.development/tinyplot_test.R b/bs/.development/tinyplot_test.R
deleted file mode 100644
index b20409f..0000000
--- a/bs/.development/tinyplot_test.R
+++ /dev/null
@@ -1,29 +0,0 @@
-library(tinyplot)
-library("grid")
-library("ggplotify")
-
-f <- formula(uptake ~ conc | Treatment)
-
-
-p <- as.ggplot(
-  expression(
-    tinyplot(
-      f,
-      data = CO2,
-      # facet = "by",
-      # facet.args = list(bg = "grey90"),
-      type = "boxplot",
-      palette = "dark2",
-      grid = TRUE,
-      axes = "l",
-      facet = Treatment ~ Type,
-      facet.args = list(col = "white", bg = "black"),
-      main = "CO2 uptake by conc and Treatment"
-    )
-  )
-)
-p
-
-
-p2 <- as.ggplot(expression(plot(rnorm(10))))
-p2
diff --git a/bs/.development/warningPlot.R b/bs/.development/warningPlot.R
deleted file mode 100644
index f5c27ed..0000000
--- a/bs/.development/warningPlot.R
+++ /dev/null
@@ -1,43 +0,0 @@
-library(ggplot2)
-
-df <- data.frame(
-  x = rep(c("A", "B"), each = 10),
-  y = c(1:9, Inf, 11:19, NA)
-)
-
-p <- tryCatch(
-  {
-      ggplot(df, aes(x, y)) +
-        geom_boxplot() +
-        ggtitle("Boxplot with Non-finite Values")
-  },
-  warning = function(w) {
-    message("Warning captured: Non-finite values removed from the data")
-    NULL
-  },
-  error = function(e) {
-    message("Error captured: ", e$message)
-    NULL
-  }
-)
-
-if (!is.null(p)) print(p)
-
-
-test <- tryCatch(
-  {
-    print(p)
-  },
-  warning = function(w) {
-    message("Warning captured: Non-finite values removed from the data")
-    return(w)
-  },
-  error = function(e) {
-    message("Error captured: ", e$message)
-    NULL
-  }
-)
-
-test
-
-