diff --git a/DESCRIPTION b/DESCRIPTION
index 5ed5b90..4833aa6 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,12 +1,12 @@
 Package: vistributions
 Type: Package
 Title: Visualize Probability Distributions
-Version: 0.1.1.9000
+Version: 0.1.2
 Authors@R: person("Aravind", "Hebbali", email = "hebbali.aravind@gmail.com", role = c("aut", "cre"))
 Description: Visualize and compute percentiles/probabilities of normal, t, f, chi square 
     and binomial distributions.
 Depends:
-    R(>= 3.1)
+    R(>= 3.2)
 Imports:
     ggplot2,
     magrittr,
@@ -23,6 +23,5 @@ License: MIT + file LICENSE
 URL: https://github.com/rsquaredacademy/vistributions, https://vistributions.rsquaredacademy.com
 BugReports: https://github.com/rsquaredacademy/vistributions/issues
 Encoding: UTF-8
-LazyData: true
 RoxygenNote: 7.1.1
 VignetteBuilder: knitr
diff --git a/NAMESPACE b/NAMESPACE
index c1a8f6b..88bbf71 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -16,7 +16,7 @@ export(vdist_normal_prob)
 export(vdist_t_perc)
 export(vdist_t_plot)
 export(vdist_t_prob)
-importFrom(magrittr,"%>%")
-importFrom(utils,install.packages)
-importFrom(utils,menu)
-importFrom(utils,packageVersion)
+import(ggplot2)
+import(magrittr)
+import(stats)
+import(utils)
diff --git a/NEWS.md b/NEWS.md
index 908b31f..ed97213 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,7 @@
+# vistributions 0.1.2
+
+This is a patch release to fix CRAN note about lazy data.
+
 # vistributions 0.1.1
 
 This is a patch release to fix bugs in the app.
diff --git a/R/vdist-binomial.R b/R/vdist-binomial.R
index 7fbaf2d..aec0b1b 100644
--- a/R/vdist-binomial.R
+++ b/R/vdist-binomial.R
@@ -42,19 +42,19 @@ vdist_binom_plot <- function(n = 10, p = 0.3, print_plot = TRUE) {
 	xn   <- n / 40
 	bm   <- round(n * p, 2)
 	bsd  <- round(sqrt((1 - p) * bm) , 2)
-	data <- stats::dbinom(x, n, p)
+	data <- dbinom(x, n, p)
 
 	plot_data <- data.frame(n = seq(0, n), df = data)
 
 	pp <-
-		ggplot2::ggplot(plot_data) +
-		ggplot2::geom_col(ggplot2::aes(x = n, y = df), fill = "blue") +
-		ggplot2::ylab("Probability") + ggplot2::xlab("No. of success") +
-		ggplot2::ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
+		ggplot(plot_data) +
+		geom_col(aes(x = n, y = df), fill = "blue") +
+		ylab("Probability") + xlab("No. of success") +
+		ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
 										 subtitle = paste("Mean =", bm, ", Std. Dev. =", bsd)) +
-		ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-									 plot.subtitle = ggplot2::element_text(hjust = 0.5)) +
-		ggplot2::scale_x_continuous(breaks = seq(0, n))
+		theme(plot.title = element_text(hjust = 0.5),
+									 plot.subtitle = element_text(hjust = 0.5)) +
+		scale_x_continuous(breaks = seq(0, n))
 
 	if (print_plot) {
 		print(pp)
@@ -95,49 +95,49 @@ vdist_binom_prob <- function(n = 10, p = 0.3, s = 4,
 	bsd <- round(sqrt((1 - p) * bm), 2)
 
 	if (method == "lower") {
-		k    <- round(stats::pbinom(s, n, p), 3)
-		cols <- ifelse(cumsum(round(stats::dbinom(x, n, p), 3)) <= k, "#0000CD", "#6495ED")
+		k    <- round(pbinom(s, n, p), 3)
+		cols <- ifelse(cumsum(round(dbinom(x, n, p), 3)) <= k, "#0000CD", "#6495ED")
 	} else if (method == "upper") {
-		k    <- round(1 - stats::pbinom((s - 1), n, p), 3)
-		cols <- ifelse(cumsum(round(stats::dbinom(x, n, p), 3)) >= k, "#0000CD", "#6495ED")
+		k    <- round(1 - pbinom((s - 1), n, p), 3)
+		cols <- ifelse(cumsum(round(dbinom(x, n, p), 3)) >= k, "#0000CD", "#6495ED")
 	} else if (method == "exact") {
-		k    <- stats::pbinom(s, n, p) - stats::pbinom((s - 1), n, p)
-		cols <- ifelse(round(stats::dbinom(x, n, p), 5) == round(k, 5), "#0000CD", "#6495ED")
+		k    <- pbinom(s, n, p) - pbinom((s - 1), n, p)
+		cols <- ifelse(round(dbinom(x, n, p), 5) == round(k, 5), "#0000CD", "#6495ED")
 	} else {
-		k1   <- stats::pbinom((s[1] - 1), n, p)
-		k2   <- stats::pbinom(s[2], n, p)
-		k    <- stats::pbinom(s[2], n, p) - stats::pbinom((s[1] - 1), n, p)
-		cols <- ifelse((round(cumsum(stats::dbinom(x, n, p)), 6) > round(k1, 6) &
-											round(cumsum(stats::dbinom(x, n, p)), 6) <= round(k2, 6)), "#0000CD", "#6495ED")
+		k1   <- pbinom((s[1] - 1), n, p)
+		k2   <- pbinom(s[2], n, p)
+		k    <- pbinom(s[2], n, p) - pbinom((s[1] - 1), n, p)
+		cols <- ifelse((round(cumsum(dbinom(x, n, p)), 6) > round(k1, 6) &
+											round(cumsum(dbinom(x, n, p)), 6) <= round(k2, 6)), "#0000CD", "#6495ED")
 	}
 
-	data      <- stats::dbinom(x, n, p)
+	data      <- dbinom(x, n, p)
 	plot_data <- data.frame(n = seq(0, n), df = data)
 
 	pp <-
-		ggplot2::ggplot(plot_data) +
-		ggplot2::geom_col(ggplot2::aes(x = n, y = df), fill = cols) +
-		ggplot2::ylab("Probability") +
-		ggplot2::xlab(paste("No. of success\n", "Mean =", bm, ", Std. Dev. =", bsd)) +
-		ggplot2::scale_x_continuous(breaks = seq(0, n)) +
-		ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-									 plot.subtitle = ggplot2::element_text(hjust = 0.5))
+		ggplot(plot_data) +
+		geom_col(aes(x = n, y = df), fill = cols) +
+		ylab("Probability") +
+		xlab(paste("No. of success\n", "Mean =", bm, ", Std. Dev. =", bsd)) +
+		scale_x_continuous(breaks = seq(0, n)) +
+		theme(plot.title = element_text(hjust = 0.5),
+									 plot.subtitle = element_text(hjust = 0.5))
 
 	if (method == "lower") {
 		pp +
-			ggplot2::ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
+			ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
 											 subtitle = paste("P(X) <=", s, "=", round(k, 3)))
 	} else if (method == "upper") {
 		pp +
-			ggplot2::ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
+			ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
 											 subtitle = paste("P(X) >=", s, "=", round(k, 3)))
 	} else if (method == "exact") {
 		pp +
-			ggplot2::ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
+			ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
 											 subtitle = paste("P(X) =", s, "=", round(k, 3)))
 	} else {
 		pp +
-			ggplot2::ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
+			ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
 											 subtitle = paste0("P(", s[1], " <= X <= ", s[2], ")", " = ", round(k, 3)))
 	}
 
@@ -166,33 +166,33 @@ vdist_binom_perc <- function(n = 10, p = 0.5, tp = 0.05, type = c("lower", "uppe
 	x      <- seq(0, n, 1)
 
 	if (method == "lower") {
-		k    <- round(stats::qbinom(tp, n, p), 3)
-		cols <- ifelse(cumsum(stats::dbinom(x, n, p)) <= stats::pbinom(k, n, p), "#0000CD", "#6495ED")
+		k    <- round(qbinom(tp, n, p), 3)
+		cols <- ifelse(cumsum(dbinom(x, n, p)) <= pbinom(k, n, p), "#0000CD", "#6495ED")
 	} else {
-		k    <- round(stats::qbinom(tp, n, p, lower.tail = F), 3)
-		cols <- ifelse(cumsum(stats::dbinom(x, n, p)) > stats::pbinom((k + 1), n, p), "#0000CD", "#6495ED")
+		k    <- round(qbinom(tp, n, p, lower.tail = F), 3)
+		cols <- ifelse(cumsum(dbinom(x, n, p)) > pbinom((k + 1), n, p), "#0000CD", "#6495ED")
 	}
 
-	data      <- stats::dbinom(x, n, p)
+	data      <- dbinom(x, n, p)
 	plot_data <- data.frame(n = seq(0, n), df = data)
 
 	pp <-
-		ggplot2::ggplot(plot_data) +
-		ggplot2::geom_col(ggplot2::aes(x = n, y = df), fill = cols) +
-		ggplot2::ylab("Probability") + ggplot2::xlab("No. of success") +
-		ggplot2::scale_x_continuous(breaks = seq(0, n)) +
-		ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-									 plot.subtitle = ggplot2::element_text(hjust = 0.5))
+		ggplot(plot_data) +
+		geom_col(aes(x = n, y = df), fill = cols) +
+		ylab("Probability") + xlab("No. of success") +
+		scale_x_continuous(breaks = seq(0, n)) +
+		theme(plot.title = element_text(hjust = 0.5),
+									 plot.subtitle = element_text(hjust = 0.5))
 
 
 	if (method == "lower") {
 		pp +
-			ggplot2::ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
+			ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
 				subtitle = paste0("P(X <= ", k, ") <= ", tp, ", but P(X <= ", (k + 1),
 				") > ", tp))
 	} else {
 		pp +
-			ggplot2::ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
+			ggtitle(label = paste("Binomial Distribution: n =", n, ", p =", p),
 				subtitle = paste0("P(X >= ", (k + 1), ") <= ", tp, ", but P(X >= ", k,
 				") > ", tp))
 	}
diff --git a/R/vdist-chisquare.R b/R/vdist-chisquare.R
index caaa2fd..bf1ffd6 100644
--- a/R/vdist-chisquare.R
+++ b/R/vdist-chisquare.R
@@ -41,30 +41,30 @@ vdist_chisquare_plot <- function(df = 3, normal = FALSE,
 	chim  <- round(df, 3)
 	chisd <- round(sqrt(2 * df), 3)
 	x     <- seq(0, xaxis_range, 0.01)
-	data  <- stats::dchisq(x, df)
+	data  <- dchisq(x, df)
 
 	plot_data  <- data.frame(x = x, chi = data)
 	poly_data  <- data.frame(y = c(0, seq(0, 25, 0.01), 25),
-	                         z = c(0, stats::dchisq(seq(0, 25, 0.01), df), 0))
+	                         z = c(0, dchisq(seq(0, 25, 0.01), df), 0))
 	point_data <- data.frame(x = chim, y = min(data))
-	nline_data <- data.frame(x = x, y = stats::dnorm(x, chim, chisd))
+	nline_data <- data.frame(x = x, y = dnorm(x, chim, chisd))
 
 
 	pp <-
-	  ggplot2::ggplot(plot_data) +
-	  ggplot2::geom_line(ggplot2::aes(x, chi), color = '#4682B4', size = 2) +
-	  ggplot2::ggtitle(label    = "Chi Square Distribution",
+	  ggplot(plot_data) +
+	  geom_line(aes(x, chi), color = '#4682B4', size = 2) +
+	  ggtitle(label    = "Chi Square Distribution",
 	                   subtitle = paste("df =", df)) +
-	  ggplot2::ylab('') +
-	  ggplot2::xlab(paste("Mean =", chim, " Std Dev. =", chisd)) +
-	  ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-	                 plot.subtitle = ggplot2::element_text(hjust = 0.5)) +
-	  ggplot2::scale_x_continuous(breaks = seq(0, xaxis_range, 2)) +
-	  ggplot2::geom_polygon(data    = poly_data,
-	                        mapping = ggplot2::aes(x = y, y = z),
+	  ylab('') +
+	  xlab(paste("Mean =", chim, " Std Dev. =", chisd)) +
+	  theme(plot.title = element_text(hjust = 0.5),
+	                 plot.subtitle = element_text(hjust = 0.5)) +
+	  scale_x_continuous(breaks = seq(0, xaxis_range, 2)) +
+	  geom_polygon(data    = poly_data,
+	                        mapping = aes(x = y, y = z),
 	                        fill    = '#4682B4') +
-	  ggplot2::geom_point(data    = point_data,
-	                      mapping = ggplot2::aes(x = x, y = y),
+	  geom_point(data    = point_data,
+	                      mapping = aes(x = x, y = y),
 	                      shape   = 4,
 	                      color   = 'red',
 	                      size    = 3)
@@ -73,7 +73,7 @@ vdist_chisquare_plot <- function(df = 3, normal = FALSE,
 	if (normal) {
 	  pp <-
 	  	pp +
-	    ggplot2::geom_line(data = nline_data, mapping = ggplot2::aes(x = x, y = y),
+	    geom_line(data = nline_data, mapping = aes(x = x, y = y),
 	      color = '#FF4500')
 	}
 
@@ -104,13 +104,13 @@ vdist_chisquare_perc <- function(probs = 0.95, df = 3,
 	ln     <- length(l)
 
 	if (method == "lower") {
-	  pp  <- round(stats::qchisq(probs, df), 3)
+	  pp  <- round(qchisq(probs, df), 3)
 	  lc  <- c(l[1], pp, l[ln])
 	  col <- c("#0000CD", "#6495ED")
 	  l1  <- c(1, 2)
 	  l2  <- c(2, 3)
 	} else {
-	  pp  <- round(stats::qchisq(probs, df, lower.tail = F), 3)
+	  pp  <- round(qchisq(probs, df, lower.tail = F), 3)
 	  lc  <- c(l[1], pp, l[ln])
 	  col <- c("#6495ED", "#0000CD")
 	  l1  <- c(1, 2)
@@ -118,49 +118,49 @@ vdist_chisquare_perc <- function(probs = 0.95, df = 3,
 	}
 	xm <- vdist_xmm(chim, chisd)
 
-	plot_data <- data.frame(x = l, y = stats::dchisq(l, df))
+	plot_data <- data.frame(x = l, y = dchisq(l, df))
 	gplot <-
-	  ggplot2::ggplot(plot_data) +
-	  ggplot2::geom_line(ggplot2::aes(x = x, y = y), color = "blue") +
-	  ggplot2::xlab(paste("Mean =", chim, " Std Dev. =", chisd)) +
-	  ggplot2::ylab('') +
-	  ggplot2::theme(plot.title    = ggplot2::element_text(hjust = 0.5),
-	                 plot.subtitle = ggplot2::element_text(hjust = 0.5))
+	  ggplot(plot_data) +
+	  geom_line(aes(x = x, y = y), color = "blue") +
+	  xlab(paste("Mean =", chim, " Std Dev. =", chisd)) +
+	  ylab('') +
+	  theme(plot.title    = element_text(hjust = 0.5),
+	                 plot.subtitle = element_text(hjust = 0.5))
 
 
 	if (method == "lower") {
 	  gplot <-
 	    gplot +
-	    ggplot2::ggtitle(label    = paste("Chi Square Distribution: df =", df),
+	    ggtitle(label    = paste("Chi Square Distribution: df =", df),
 	                     subtitle = paste0("P(X < ", pp, ") = ", probs * 100, "%")) +
-	    ggplot2::annotate("text",
+	    annotate("text",
 	                      label   = paste0(probs * 100, "%"),
 	                      x       = pp - chisd,
-	                      y       = max(stats::dchisq(l, df)) + 0.02,
+	                      y       = max(dchisq(l, df)) + 0.02,
 	                      color   = "#0000CD",
 	                      size    = 3) +
-	    ggplot2::annotate("text",
+	    annotate("text",
 	                      label   = paste0((1 - probs) * 100, "%"),
 	                      x       = pp + chisd,
-	                      y       = max(stats::dchisq(l, df)) + 0.02,
+	                      y       = max(dchisq(l, df)) + 0.02,
 	                      color   = "#6495ED",
 	                      size    = 3)
 
 	} else {
 	  gplot <-
 	  	gplot +
-	    ggplot2::ggtitle(label    = paste("Chi Square Distribution: df =", df),
+	    ggtitle(label    = paste("Chi Square Distribution: df =", df),
 	                     subtitle = paste0("P(X > ", pp, ") = ", probs * 100, "%")) +
-	    ggplot2::annotate("text",
+	    annotate("text",
 	                      label   = paste0((1 - probs) * 100, "%"),
 	                      x       = pp - chisd,
-	                      y       = max(stats::dchisq(l, df)) + 0.02,
+	                      y       = max(dchisq(l, df)) + 0.02,
 	                      color   = "#6495ED",
 	                      size    = 3) +
-	    ggplot2::annotate("text",
+	    annotate("text",
 	                      label   = paste0(probs * 100, "%"),
 	                      x       = pp + chisd,
-	                      y       = max(stats::dchisq(l, df)) + 0.02,
+	                      y       = max(dchisq(l, df)) + 0.02,
 	                      color   = "#0000CD",
 	                      size    = 3)
 	}
@@ -169,25 +169,25 @@ vdist_chisquare_perc <- function(probs = 0.95, df = 3,
 	  pol_data <- vdist_pol_chi(lc[l1[i]], lc[l2[i]], df)
 	  gplot <-
 	    gplot +
-	    ggplot2::geom_polygon(data    = pol_data,
-	                          mapping = ggplot2::aes(x = x, y = y),
+	    geom_polygon(data    = pol_data,
+	                          mapping = aes(x = x, y = y),
 	                          fill    = col[i])
 	}
 
-	point_data <- data.frame(x = pp, y = min(stats::dchisq(l, df)))
+	point_data <- data.frame(x = pp, y = min(dchisq(l, df)))
 
 	gplot <-
 	  gplot +
-	  ggplot2::geom_vline(xintercept = pp,
+	  geom_vline(xintercept = pp,
 	                      linetype   = 2,
 	                      size       = 1) +
-	  ggplot2::geom_point(data       = point_data,
-	                      mapping    = ggplot2::aes(x = x, y = y),
+	  geom_point(data       = point_data,
+	                      mapping    = aes(x = x, y = y),
 	                      shape      = 4,
 	                      color      = 'red',
 	                      size       = 3) +
-	  ggplot2::scale_y_continuous(breaks = NULL) +
-	  ggplot2::scale_x_continuous(breaks = seq(0, xm[2], by = 5))
+	  scale_y_continuous(breaks = NULL) +
+	  scale_x_continuous(breaks = seq(0, xm[2], by = 5))
 
 	if (print_plot) {
 	  print(gplot)
@@ -219,51 +219,51 @@ vdist_chisquare_prob <- function(perc = 13, df = 11, type = c("lower", "upper"),
   ln <- length(l)
 
   if (method == "lower") {
-    pp  <- round(stats::pchisq(perc, df), 3)
+    pp  <- round(pchisq(perc, df), 3)
     lc  <- c(l[1], perc, l[ln])
     col <- c("#0000CD", "#6495ED")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   } else {
-    pp  <- round(stats::pchisq(perc, df, lower.tail = F), 3)
+    pp  <- round(pchisq(perc, df, lower.tail = F), 3)
     lc  <- c(l[1], perc, l[ln])
     col <- c("#6495ED", "#0000CD")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   }
 
-  plot_data <- data.frame(x = l, y = stats::dchisq(l, df))
+  plot_data <- data.frame(x = l, y = dchisq(l, df))
 	gplot <-
-	  ggplot2::ggplot(plot_data) +
-	  ggplot2::geom_line(ggplot2::aes(x = x, y = y), color = "blue") +
-	  ggplot2::xlab(paste("Mean =", chim, " Std Dev. =", chisd)) +
-	  ggplot2::ylab('') +
-	  ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-	                 plot.subtitle = ggplot2::element_text(hjust = 0.5))
+	  ggplot(plot_data) +
+	  geom_line(aes(x = x, y = y), color = "blue") +
+	  xlab(paste("Mean =", chim, " Std Dev. =", chisd)) +
+	  ylab('') +
+	  theme(plot.title = element_text(hjust = 0.5),
+	                 plot.subtitle = element_text(hjust = 0.5))
 
 
   if (method == "lower") {
 	  gplot <-
 	    gplot +
-	    ggplot2::ggtitle(label = paste("Chi Square Distribution: df =", df),
+	    ggtitle(label = paste("Chi Square Distribution: df =", df),
 	      subtitle = paste0("P(X < ", perc, ") = ", pp * 100, "%")) +
-	    ggplot2::annotate("text", label = paste0(pp * 100, "%"),
-	      x = perc - chisd, y = max(stats::dchisq(l, df)) + 0.02, color = "#0000CD",
+	    annotate("text", label = paste0(pp * 100, "%"),
+	      x = perc - chisd, y = max(dchisq(l, df)) + 0.02, color = "#0000CD",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0((1 - pp) * 100, "%"),
-	      x = perc + chisd, y = max(stats::dchisq(l, df)) + 0.02, color = "#6495ED",
+	    annotate("text", label = paste0((1 - pp) * 100, "%"),
+	      x = perc + chisd, y = max(dchisq(l, df)) + 0.02, color = "#6495ED",
 	      size = 3)
 
 	} else {
 	  gplot <-
 	  	gplot +
-	    ggplot2::ggtitle(label = paste("Chi Square Distribution: df =", df),
+	    ggtitle(label = paste("Chi Square Distribution: df =", df),
 	      subtitle = paste0("P(X > ", perc, ") = ", pp * 100, "%")) +
-	    ggplot2::annotate("text", label = paste0((1 - pp) * 100, "%"),
-	      x = perc - chisd, y = max(stats::dchisq(l, df)) + 0.02, color = "#6495ED",
+	    annotate("text", label = paste0((1 - pp) * 100, "%"),
+	      x = perc - chisd, y = max(dchisq(l, df)) + 0.02, color = "#6495ED",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0(pp * 100, "%"),
-	      x = perc + chisd, y = max(stats::dchisq(l, df)) + 0.02, color = "#0000CD",
+	    annotate("text", label = paste0(pp * 100, "%"),
+	      x = perc + chisd, y = max(dchisq(l, df)) + 0.02, color = "#0000CD",
 	      size = 3)
 	}
 
@@ -272,26 +272,26 @@ vdist_chisquare_prob <- function(perc = 13, df = 11, type = c("lower", "upper"),
 	  pol_data <- vdist_pol_chi(lc[l1[i]], lc[l2[i]], df)
 	  gplot <-
 	    gplot +
-	    ggplot2::geom_polygon(data    = pol_data,
-	                          mapping = ggplot2::aes(x = x, y = y),
+	    geom_polygon(data    = pol_data,
+	                          mapping = aes(x = x, y = y),
 	                          fill    = col[i])
 	}
 
 	point_data <- data.frame(x = perc,
-	                         y = min(stats::dchisq(l, df)))
+	                         y = min(dchisq(l, df)))
 
 	gplot <-
 	  gplot +
-	  ggplot2::geom_vline(xintercept = perc,
+	  geom_vline(xintercept = perc,
 	                      linetype   = 2,
 	                      size       = 1) +
-	  ggplot2::geom_point(data       = point_data,
-	                      mapping    = ggplot2::aes(x = x, y = y),
+	  geom_point(data       = point_data,
+	                      mapping    = aes(x = x, y = y),
 	                      shape      = 4,
 	                      color      = 'red',
 	                      size       = 3) +
-	  ggplot2::scale_y_continuous(breaks = NULL) +
-	  ggplot2::scale_x_continuous(breaks = seq(0, l[ln], by = 5))
+	  scale_y_continuous(breaks = NULL) +
+	  scale_x_continuous(breaks = seq(0, l[ln], by = 5))
 
 	if (print_plot) {
 	  print(gplot)
@@ -305,21 +305,18 @@ vdist_chisquare_prob <- function(perc = 13, df = 11, type = c("lower", "upper"),
 vdist_chiseql <- function(mean, sd) {
   lmin <- mean - (5 * sd)
   lmax <- mean + (5 * sd)
-  l    <- seq(lmin, lmax, 0.01)
-  return(l)
+  seq(lmin, lmax, 0.01)
 }
 
 
 vdist_xmm <- function(mean, sd) {
   xmin <- mean - (5 * sd)
   xmax <- mean + (5 * sd)
-  out  <- c(xmin, xmax)
-  return(out)
+  c(xmin, xmax)
 }
 
 vdist_pol_chi <- function(l1, l2, df) {
   x   <- c(l1, seq(l1, l2, 0.01), l2)
-  y   <- c(0, stats::dchisq(seq(l1, l2, 0.01), df), 0)
-  out <- data.frame(x = x, y = y)
-  return(out)
+  y   <- c(0, dchisq(seq(l1, l2, 0.01), df), 0)
+  data.frame(x = x, y = y)
 }
diff --git a/R/vdist-f.R b/R/vdist-f.R
index f2bba79..5c79450 100644
--- a/R/vdist-f.R
+++ b/R/vdist-f.R
@@ -44,31 +44,31 @@ vdist_f_plot <- function(num_df = 4, den_df = 30, normal = FALSE,
   x      <- seq(0, 4, 0.01)
   nx     <- seq(-2, 4, 0.01)
 
-  plot_data  <- data.frame(x = x, y = stats::df(x, num_df, den_df))
+  plot_data  <- data.frame(x = x, y = df(x, num_df, den_df))
   poly_data  <- data.frame(y = c(0, seq(0, 4, 0.01), 4),
-    z = c(0, stats::df(seq(0, 4, 0.01), num_df, den_df), 0))
+    z = c(0, df(seq(0, 4, 0.01), num_df, den_df), 0))
   point_data <- data.frame(x = fm, y = 0)
-  nline_data <- data.frame(x = nx, y = stats::dnorm(nx, fm, fsd))
+  nline_data <- data.frame(x = nx, y = dnorm(nx, fm, fsd))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(ggplot2::aes(x = x, y = y), color = "blue") +
-    ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = y, y = z),
+    ggplot(plot_data) +
+    geom_line(aes(x = x, y = y), color = "blue") +
+    geom_polygon(data = poly_data, mapping = aes(x = y, y = z),
       fill = '#4682B4') +
-    ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x, y = y),
+    geom_point(data = point_data, mapping = aes(x = x, y = y),
       shape = 4, color = 'red', size = 3) +
-    ggplot2::xlab(paste("Mean =", fm, " Std Dev. =", fsd)) + ggplot2::ylab('') +
-    ggplot2::ggtitle(label = 'f Distribution',
+    xlab(paste("Mean =", fm, " Std Dev. =", fsd)) + ylab('') +
+    ggtitle(label = 'f Distribution',
       subtitle = paste("Num df =", num_df, "  Den df =", den_df)) +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5)) +
-    ggplot2::scale_x_continuous(breaks = c(-2:4)) +
-    ggplot2::scale_y_continuous(breaks = NULL)
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5)) +
+    scale_x_continuous(breaks = c(-2:4)) +
+    scale_y_continuous(breaks = NULL)
 
   if (normal) {
     gplot <-
       gplot +
-      ggplot2::geom_line(data = nline_data, mapping = ggplot2::aes(x = x, y = y),
+      geom_line(data = nline_data, mapping = aes(x = x, y = y),
         color = '#FF4500')
   }
 
@@ -100,52 +100,52 @@ vdist_f_perc <- function(probs = 0.95, num_df = 3, den_df = 30,
   ln     <- length(l)
 
   if (method == "lower") {
-    pp  <- round(stats::qf(probs, num_df, den_df), 3)
+    pp  <- round(qf(probs, num_df, den_df), 3)
     lc  <- c(l[1], pp, l[ln])
     col <- c("#0000CD", "#6495ED")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   } else {
-    pp  <- round(stats::qf(probs, num_df, den_df, lower.tail = F), 3)
+    pp  <- round(qf(probs, num_df, den_df, lower.tail = F), 3)
     lc  <- c(l[1], pp, l[ln])
     col <- c("#6495ED", "#0000CD")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   }
 
-  plot_data <- data.frame(x = l, y = stats::df(l, num_df, den_df))
+  plot_data <- data.frame(x = l, y = df(l, num_df, den_df))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(data = plot_data, mapping = ggplot2::aes(x = x, y = y),
-      color = 'blue') + ggplot2::xlab(paste("Mean =", fm, " Std Dev. =", fsd)) +
-    ggplot2::ylab('') +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
+    ggplot(plot_data) +
+    geom_line(data = plot_data, mapping = aes(x = x, y = y),
+      color = 'blue') + xlab(paste("Mean =", fm, " Std Dev. =", fsd)) +
+    ylab('') +
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5))
 
 
   if (method == "lower") {
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = 'f Distribution',
+      ggtitle(label = 'f Distribution',
         subtitle = paste0("P(X < ", pp, ") = ", probs * 100, "%")) +
-      ggplot2::annotate("text", label = paste0(probs * 100, "%"),
-        x = pp - 0.2, y = max(stats::df(l, num_df, den_df)) + 0.02, color = "#0000CD",
+      annotate("text", label = paste0(probs * 100, "%"),
+        x = pp - 0.2, y = max(df(l, num_df, den_df)) + 0.02, color = "#0000CD",
         size = 3) +
-      ggplot2::annotate("text", label = paste0((1 - probs) * 100, "%"),
-        x = pp + 0.2, y = max(stats::df(l, num_df, den_df)) + 0.02, color = "#6495ED",
+      annotate("text", label = paste0((1 - probs) * 100, "%"),
+        x = pp + 0.2, y = max(df(l, num_df, den_df)) + 0.02, color = "#6495ED",
         size = 3)
 
   } else {
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = 'f Distribution',
+      ggtitle(label = 'f Distribution',
         subtitle = paste0("P(X > ", pp, ") = ", probs * 100, "%")) +
-      ggplot2::annotate("text", label = paste0((1 - probs) * 100, "%"),
-        x = pp - 0.2, y = max(stats::df(l, num_df, den_df)) + 0.02, color = "#6495ED",
+      annotate("text", label = paste0((1 - probs) * 100, "%"),
+        x = pp - 0.2, y = max(df(l, num_df, den_df)) + 0.02, color = "#6495ED",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(probs * 100, "%"),
-        x = pp + 0.2, y = max(stats::df(l, num_df, den_df)) + 0.02, color = "#0000CD",
+      annotate("text", label = paste0(probs * 100, "%"),
+        x = pp + 0.2, y = max(df(l, num_df, den_df)) + 0.02, color = "#0000CD",
         size = 3)
   }
 
@@ -153,7 +153,7 @@ vdist_f_perc <- function(probs = 0.95, num_df = 3, den_df = 30,
     poly_data <- vdist_pol_f(lc[l1[i]], lc[l2[i]], num_df, den_df)
     gplot <-
       gplot +
-      ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = x, y = y),
+      geom_polygon(data = poly_data, mapping = aes(x = x, y = y),
         fill = col[i])
   }
 
@@ -165,15 +165,15 @@ vdist_f_perc <- function(probs = 0.95, num_df = 3, den_df = 30,
 
     gplot <-
       gplot +
-      ggplot2::geom_vline(xintercept = pp[i], linetype = 2, size = 1) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x, y = y),
+      geom_vline(xintercept = pp[i], linetype = 2, size = 1) +
+      geom_point(data = point_data, mapping = aes(x = x, y = y),
       shape = 4, color = 'red', size = 3)
   }
 
   gplot <-
     gplot +
-      ggplot2::scale_y_continuous(breaks = NULL) +
-      ggplot2::scale_x_continuous(breaks = 0:5)
+      scale_y_continuous(breaks = NULL) +
+      scale_x_continuous(breaks = 0:5)
 
   if (print_plot) {
     print(gplot)
@@ -207,51 +207,51 @@ vdist_f_prob <- function(perc = 2.35, num_df = 5, den_df = 32, type = c("lower",
   ln <- length(l)
 
   if (method == "lower") {
-    pp  <- round(stats::pf(perc, num_df, den_df), 3)
+    pp  <- round(pf(perc, num_df, den_df), 3)
     lc  <- c(l[1], perc, l[ln])
     col <- c("#0000CD", "#6495ED")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   } else {
-    pp  <- round(stats::pf(perc, num_df, den_df, lower.tail = F), 3)
+    pp  <- round(pf(perc, num_df, den_df, lower.tail = F), 3)
     lc  <- c(l[1], perc, l[ln])
     col <- c("#6495ED", "#0000CD")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   }
 
-  plot_data <- data.frame(x = l, y = stats::df(l, num_df, den_df))
+  plot_data <- data.frame(x = l, y = df(l, num_df, den_df))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(data = plot_data, mapping = ggplot2::aes(x = x, y = y),
-      color = 'blue') + ggplot2::xlab(paste("Mean =", fm, " Std Dev. =", fsd)) +
-    ggplot2::ylab('') +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
+    ggplot(plot_data) +
+    geom_line(data = plot_data, mapping = aes(x = x, y = y),
+      color = 'blue') + xlab(paste("Mean =", fm, " Std Dev. =", fsd)) +
+    ylab('') +
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5))
 
   if (method == "lower") {
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = 'f Distribution',
+      ggtitle(label = 'f Distribution',
         subtitle = paste0("P(X < ", perc, ") = ", pp * 100, "%")) +
-      ggplot2::annotate("text", label = paste0(pp * 100, "%"),
-        x = perc - fsd, y = max(stats::df(l, num_df, den_df)) + 0.04, color = "#0000CD",
+      annotate("text", label = paste0(pp * 100, "%"),
+        x = perc - fsd, y = max(df(l, num_df, den_df)) + 0.04, color = "#0000CD",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(round((1 - pp) * 100, 2), "%"),
-        x = perc + fsd, y = max(stats::df(l, num_df, den_df)) + 0.02, color = "#6495ED",
+      annotate("text", label = paste0(round((1 - pp) * 100, 2), "%"),
+        x = perc + fsd, y = max(df(l, num_df, den_df)) + 0.02, color = "#6495ED",
         size = 3)
 
   } else {
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = 'f Distribution',
+      ggtitle(label = 'f Distribution',
         subtitle = paste0("P(X > ", perc, ") = ", pp * 100, "%")) +
-      ggplot2::annotate("text", label = paste0(round((1 - pp) * 100, 2), "%"),
-        x = perc - fsd, y = max(stats::df(l, num_df, den_df)) + 0.04, color = "#6495ED",
+      annotate("text", label = paste0(round((1 - pp) * 100, 2), "%"),
+        x = perc - fsd, y = max(df(l, num_df, den_df)) + 0.04, color = "#6495ED",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(pp * 100, "%"),
-        x = perc + fsd, y = max(stats::df(l, num_df, den_df)) + 0.04, color = "#0000CD",
+      annotate("text", label = paste0(pp * 100, "%"),
+        x = perc + fsd, y = max(df(l, num_df, den_df)) + 0.04, color = "#0000CD",
         size = 3)
   }
 
@@ -259,7 +259,7 @@ vdist_f_prob <- function(perc = 2.35, num_df = 5, den_df = 32, type = c("lower",
     poly_data <- vdist_pol_f(lc[l1[i]], lc[l2[i]], num_df, den_df)
     gplot <-
       gplot +
-      ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = x, y = y),
+      geom_polygon(data = poly_data, mapping = aes(x = x, y = y),
         fill = col[i])
   }
 
@@ -271,15 +271,15 @@ vdist_f_prob <- function(perc = 2.35, num_df = 5, den_df = 32, type = c("lower",
 
     gplot <-
       gplot +
-      ggplot2::geom_vline(xintercept = perc[i], linetype = 2, size = 1) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x, y = y),
+      geom_vline(xintercept = perc[i], linetype = 2, size = 1) +
+      geom_point(data = point_data, mapping = aes(x = x, y = y),
       shape = 4, color = 'red', size = 3)
   }
 
   gplot <-
     gplot +
-      ggplot2::scale_y_continuous(breaks = NULL) +
-      ggplot2::scale_x_continuous(breaks = 0:max(l))
+      scale_y_continuous(breaks = NULL) +
+      scale_x_continuous(breaks = 0:max(l))
 
   if (print_plot) {
     print(gplot)
@@ -293,6 +293,5 @@ vdist_f_prob <- function(perc = 2.35, num_df = 5, den_df = 32, type = c("lower",
 vdist_pol_f <- function(l1, l2, num_df, den_df) {
   x    <- c(l1, seq(l1, l2, 0.01), l2)
   y    <- c(0, df(seq(l1, l2, 0.01), num_df, den_df), 0)
-  data <- data.frame(x = x, y = y)
-  return(data)
+  data.frame(x = x, y = y)
 }
diff --git a/R/vdist-normal.R b/R/vdist-normal.R
index aa02be2..6373fc6 100644
--- a/R/vdist-normal.R
+++ b/R/vdist-normal.R
@@ -43,16 +43,16 @@ vdist_normal_plot <- function(mean = 0, sd = 1, print_plot = TRUE) {
   l2  <- c(5, 3, 2, 6, 7)
   xm  <- vdist_xmm(mean, sd)
   
-  plot_data <- data.frame(x = x, y = stats::dnorm(x, mean, sd))
+  plot_data <- data.frame(x = x, y = dnorm(x, mean, sd))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(ggplot2::aes(x = x, y = y)) +
-    ggplot2::xlab('') + ggplot2::ylab('') +
-    ggplot2::ggtitle(label = "Normal Distribution",
+    ggplot(plot_data) +
+    geom_line(aes(x = x, y = y)) +
+    xlab('') + ylab('') +
+    ggtitle(label = "Normal Distribution",
       subtitle = paste("Mean:", mean, "     Standard Deviation:", sd)) +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5))
 
   ll <- l[3:9]
 
@@ -60,7 +60,7 @@ vdist_normal_plot <- function(mean = 0, sd = 1, print_plot = TRUE) {
     poly_data <- vdist_pol_cord(ll[l1[i]], ll[l2[i]], mean, sd)
     gplot <-
       gplot +
-      ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = x, y = y), fill = col[i])
+      geom_polygon(data = poly_data, mapping = aes(x = x, y = y), fill = col[i])
   }
 
   if (print_plot) {
@@ -90,21 +90,21 @@ vdist_normal_perc <- function(probs = 0.95, mean = 0, sd = 1,
   ln     <- length(l)
 
   if (method == "lower") {
-    pp  <- round(stats::qnorm(probs, mean, sd), 3)
+    pp  <- round(qnorm(probs, mean, sd), 3)
     lc  <- c(l[1], pp, l[ln])
     col <- c("#0000CD", "#6495ED")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   } else if (method == "upper") {
-    pp  <- round(stats::qnorm(probs, mean, sd, lower.tail = F), 3)
+    pp  <- round(qnorm(probs, mean, sd, lower.tail = F), 3)
     lc  <- c(l[1], pp, l[ln])
     col <- c("#6495ED", "#0000CD")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   } else {
     alpha <- (1 - probs) / 2
-    pp1 <- round(stats::qnorm(alpha, mean, sd), 3)
-    pp2 <- round(stats::qnorm(alpha, mean, sd, lower.tail = F), 3)
+    pp1 <- round(qnorm(alpha, mean, sd), 3)
+    pp2 <- round(qnorm(alpha, mean, sd, lower.tail = F), 3)
     pp  <- c(pp1, pp2)
     lc  <- c(l[1], pp1, pp2, l[ln])
     col <- c("#6495ED", "#0000CD", "#6495ED")
@@ -113,51 +113,51 @@ vdist_normal_perc <- function(probs = 0.95, mean = 0, sd = 1,
   }
 
   xm <- vdist_xmm(mean, sd)
-  plot_data <- data.frame(x = x, y = stats::dnorm(x, mean, sd))
+  plot_data <- data.frame(x = x, y = dnorm(x, mean, sd))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(ggplot2::aes(x = x, y = y)) +
-    ggplot2::xlab(paste("Mean:", mean, " Standard Deviation:", sd)) + ggplot2::ylab('') +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
+    ggplot(plot_data) +
+    geom_line(aes(x = x, y = y)) +
+    xlab(paste("Mean:", mean, " Standard Deviation:", sd)) + ylab('') +
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5))
 
   if (method == "lower") {
 	  gplot <-
 	    gplot +
-	    ggplot2::ggtitle(label = "Normal Distribution",
+	    ggtitle(label = "Normal Distribution",
 	      subtitle = paste0("P(X < ", pp, ") = ", probs * 100, "%")) +
-	    ggplot2::annotate("text", label = paste0(probs * 100, "%"),
-	      x = pp - sd, y = max(stats::dnorm(x, mean, sd)) + 0.025, color = "#0000CD",
+	    annotate("text", label = paste0(probs * 100, "%"),
+	      x = pp - sd, y = max(dnorm(x, mean, sd)) + 0.025, color = "#0000CD",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0((1 - probs) * 100, "%"),
-	      x = pp + sd, y = max(stats::dnorm(x, mean, sd)) + 0.025, color = "#6495ED",
+	    annotate("text", label = paste0((1 - probs) * 100, "%"),
+	      x = pp + sd, y = max(dnorm(x, mean, sd)) + 0.025, color = "#6495ED",
 	      size = 3)
 
 	} else if (method == "upper") {
 	  gplot <-
 	  	gplot +
-	    ggplot2::ggtitle(label = "Normal Distribution",
+	    ggtitle(label = "Normal Distribution",
 	      subtitle = paste0("P(X > ", pp, ") = ", probs * 100, "%")) +
-	    ggplot2::annotate("text", label = paste0((1 - probs) * 100, "%"),
-	      x = pp - sd, y = max(stats::dnorm(x, mean, sd)) + 0.025, color = "#6495ED",
+	    annotate("text", label = paste0((1 - probs) * 100, "%"),
+	      x = pp - sd, y = max(dnorm(x, mean, sd)) + 0.025, color = "#6495ED",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0(probs * 100, "%"),
-	      x = pp + sd, y = max(stats::dnorm(x, mean, sd)) + 0.025, color = "#0000CD",
+	    annotate("text", label = paste0(probs * 100, "%"),
+	      x = pp + sd, y = max(dnorm(x, mean, sd)) + 0.025, color = "#0000CD",
 	      size = 3)
 	} else {
 		gplot <-
 	  	gplot +
-	    ggplot2::ggtitle(label = "Normal Distribution",
+	    ggtitle(label = "Normal Distribution",
 	      subtitle = paste0("P(", pp[1], " < X < ", pp[2], ") = ", probs * 100, "%")) +
-	    ggplot2::annotate("text", label = paste0(probs * 100, "%"),
-	      x = mean, y = max(stats::dnorm(x, mean, sd)) + 0.025, color = "#0000CD",
+	    annotate("text", label = paste0(probs * 100, "%"),
+	      x = mean, y = max(dnorm(x, mean, sd)) + 0.025, color = "#0000CD",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0(alpha * 100, "%"),
-	      x = pp[1] - sd, y = max(stats::dnorm(x, mean, sd)) + 0.025, color = "#6495ED",
+	    annotate("text", label = paste0(alpha * 100, "%"),
+	      x = pp[1] - sd, y = max(dnorm(x, mean, sd)) + 0.025, color = "#6495ED",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0(alpha * 100, "%"),
-	      x = pp[2] + sd, y = max(stats::dnorm(x, mean, sd)) + 0.025, color = "#6495ED",
+	    annotate("text", label = paste0(alpha * 100, "%"),
+	      x = pp[2] + sd, y = max(dnorm(x, mean, sd)) + 0.025, color = "#6495ED",
 	      size = 3)
 	}
 
@@ -165,7 +165,7 @@ vdist_normal_perc <- function(probs = 0.95, mean = 0, sd = 1,
 		poly_data <- vdist_pol_cord(lc[l1[i]], lc[l2[i]], mean, sd)
 		gplot <-
 		  gplot +
-		  ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = x, y = y), fill = col[i])
+		  geom_polygon(data = poly_data, mapping = aes(x = x, y = y), fill = col[i])
   }
 
   pln <- length(pp)
@@ -176,15 +176,15 @@ vdist_normal_perc <- function(probs = 0.95, mean = 0, sd = 1,
 
   	gplot <-
   	  gplot +
-  	  ggplot2::geom_vline(xintercept = pp[i], linetype = 2, size = 1) +
-  	  ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x, y = y),
+  	  geom_vline(xintercept = pp[i], linetype = 2, size = 1) +
+  	  geom_point(data = point_data, mapping = aes(x = x, y = y),
 	    shape = 4, color = 'red', size = 3)
   }
 
   gplot <-
     gplot +
-	 	 	ggplot2::scale_y_continuous(breaks = NULL) +
-	  	ggplot2::scale_x_continuous(breaks = l)
+	 	 	scale_y_continuous(breaks = NULL) +
+	  	scale_x_continuous(breaks = l)
 
   if (print_plot) {
     print(gplot)
@@ -226,20 +226,20 @@ vdist_normal_prob <- function(perc = 3, mean = 0, sd = 1,
   ln <- length(l)
 
   if (method == "lower") {
-    pp  <- round(stats::pnorm(perc, mean, sd), 3)
+    pp  <- round(pnorm(perc, mean, sd), 3)
     lc  <- c(l[1], perc, l[ln])
     col <- c("#0000CD", "#6495ED")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   } else if (method == "upper") {
-    pp  <- round(stats::pnorm(perc, mean, sd, lower.tail = F), 3)
+    pp  <- round(pnorm(perc, mean, sd, lower.tail = F), 3)
     lc  <- c(l[1], perc, l[ln])
     col <- c("#6495ED", "#0000CD")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   } else {
-    pp1 <- round(stats::pnorm(perc[1], mean, sd), 3)
-    pp2 <- round(stats::pnorm(perc[2], mean, sd, lower.tail = F), 3)
+    pp1 <- round(pnorm(perc[1], mean, sd), 3)
+    pp2 <- round(pnorm(perc[2], mean, sd, lower.tail = F), 3)
     pp  <- c(pp1, pp2)
     lc  <- c(l[1], perc[1], perc[2], l[ln])
     col <- c("#6495ED", "#0000CD", "#6495ED")
@@ -248,51 +248,51 @@ vdist_normal_prob <- function(perc = 3, mean = 0, sd = 1,
   }
 
   xm <- vdist_xmmp(mean, sd, el)
-  plot_data <- data.frame(x = x, y = stats::dnorm(x, mean, sd))
+  plot_data <- data.frame(x = x, y = dnorm(x, mean, sd))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(ggplot2::aes(x = x, y = y)) +
-    ggplot2::xlab(paste("Mean:", mean, " Standard Deviation:", sd)) + ggplot2::ylab('') +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
+    ggplot(plot_data) +
+    geom_line(aes(x = x, y = y)) +
+    xlab(paste("Mean:", mean, " Standard Deviation:", sd)) + ylab('') +
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5))
 
   if (method == "lower") {
 	  gplot <-
 	    gplot +
-	    ggplot2::ggtitle(label = "Normal Distribution",
+	    ggtitle(label = "Normal Distribution",
 	      subtitle = paste0("P(X < ", perc, ") = ", pp * 100, "%")) +
-	    ggplot2::annotate("text", label = paste0(pp * 100, "%"),
-	      x = perc - sd, y = max(stats::dnorm(x, mean, sd)) + 0.07, color = "#0000CD",
+	    annotate("text", label = paste0(pp * 100, "%"),
+	      x = perc - sd, y = max(dnorm(x, mean, sd)) + 0.07, color = "#0000CD",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0((1 - pp) * 100, "%"),
-	      x = perc + sd, y = max(stats::dnorm(x, mean, sd)) + 0.07, color = "#6495ED",
+	    annotate("text", label = paste0((1 - pp) * 100, "%"),
+	      x = perc + sd, y = max(dnorm(x, mean, sd)) + 0.07, color = "#6495ED",
 	      size = 3)
 
 	} else if (method == "upper") {
 	  gplot <-
 	  	gplot +
-	    ggplot2::ggtitle(label = "Normal Distribution",
+	    ggtitle(label = "Normal Distribution",
 	      subtitle = paste0("P(X > ", perc, ") = ", pp * 100, "%")) +
-	    ggplot2::annotate("text", label = paste0((1 - pp) * 100, "%"),
-	      x = perc - sd, y = max(stats::dnorm(x, mean, sd)) + 0.07, color = "#6495ED",
+	    annotate("text", label = paste0((1 - pp) * 100, "%"),
+	      x = perc - sd, y = max(dnorm(x, mean, sd)) + 0.07, color = "#6495ED",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0(pp * 100, "%"),
-	      x = perc + sd, y = max(stats::dnorm(x, mean, sd)) + 0.07, color = "#0000CD",
+	    annotate("text", label = paste0(pp * 100, "%"),
+	      x = perc + sd, y = max(dnorm(x, mean, sd)) + 0.07, color = "#0000CD",
 	      size = 3)
 	} else {
 		gplot <-
 	  	gplot +
-	    ggplot2::ggtitle(label = "Normal Distribution",
+	    ggtitle(label = "Normal Distribution",
 	      subtitle = paste0("P(", perc[1], " < X < ", perc[2], ") = ", (1 - (pp1 + pp2)) * 100, "%")) +
-	    ggplot2::annotate("text", label = paste0((1 - (pp1 + pp2)) * 100, "%"),
-	      x = mean(perc), y = max(stats::dnorm(x, mean, sd)) + 0.07, color = "#0000CD",
+	    annotate("text", label = paste0((1 - (pp1 + pp2)) * 100, "%"),
+	      x = mean(perc), y = max(dnorm(x, mean, sd)) + 0.07, color = "#0000CD",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0(pp[1] * 100, "%"),
-	      x = perc[1] - sd, y = max(stats::dnorm(x, mean, sd)) + 0.07, color = "#6495ED",
+	    annotate("text", label = paste0(pp[1] * 100, "%"),
+	      x = perc[1] - sd, y = max(dnorm(x, mean, sd)) + 0.07, color = "#6495ED",
 	      size = 3) +
-	    ggplot2::annotate("text", label = paste0(pp[2] * 100, "%"),
-	      x = perc[2] + sd, y = max(stats::dnorm(x, mean, sd)) + 0.07, color = "#6495ED",
+	    annotate("text", label = paste0(pp[2] * 100, "%"),
+	      x = perc[2] + sd, y = max(dnorm(x, mean, sd)) + 0.07, color = "#6495ED",
 	      size = 3)
 	}
 
@@ -300,7 +300,7 @@ vdist_normal_prob <- function(perc = 3, mean = 0, sd = 1,
 		poly_data <- vdist_pol_cord(lc[l1[i]], lc[l2[i]], mean, sd)
 		gplot <-
 		  gplot +
-		  ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = x, y = y), fill = col[i])
+		  geom_polygon(data = poly_data, mapping = aes(x = x, y = y), fill = col[i])
   }
 
   pln <- length(pp)
@@ -311,15 +311,15 @@ vdist_normal_prob <- function(perc = 3, mean = 0, sd = 1,
 
   	gplot <-
   	  gplot +
-  	  ggplot2::geom_vline(xintercept = perc[i], linetype = 2, size = 1) +
-  	  ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x, y = y),
+  	  geom_vline(xintercept = perc[i], linetype = 2, size = 1) +
+  	  geom_point(data = point_data, mapping = aes(x = x, y = y),
 	    shape = 4, color = 'red', size = 3)
   }
 
   gplot <-
     gplot +
-	 	 	ggplot2::scale_y_continuous(breaks = NULL) +
-	  	ggplot2::scale_x_continuous(breaks = l)
+	 	 	scale_y_continuous(breaks = NULL) +
+	  	scale_x_continuous(breaks = l)
 
   if (print_plot) {
     print(gplot)
@@ -332,30 +332,26 @@ vdist_normal_prob <- function(perc = 3, mean = 0, sd = 1,
 vdist_xax <- function(mean) {
   xl <- mean - 3
   xu <- mean + 3
-  x <- seq(xl, xu, 0.01)
-  return(x)
+  seq(xl, xu, 0.01)
 }
 
 
 vdist_seql <- function(mean, sd) {
   lmin <- mean - (5 * sd)
   lmax <- mean + (5 * sd)
-  l <- seq(lmin, lmax, sd)
-  return(l)
+  seq(lmin, lmax, sd)
 }
 
 vdist_pol_cord <- function(l1, l2, mean, sd) {
   x <- c(l1, seq(l1, l2, 0.01), l2)
-  y <- c(0, stats::dnorm(seq(l1, l2, 0.01), mean, sd), 0)
-  data <- data.frame(x = x, y = y)
-  return(data)
+  y <- c(0, dnorm(seq(l1, l2, 0.01), mean, sd), 0)
+  data.frame(x = x, y = y)
 }
 
 vdist_xaxp <- function(mean, el) {
   xl <- mean - el
   xu <- mean + el
-  x <- seq(xl, xu, 0.01)
-  return(x)
+  seq(xl, xu, 0.01)
 }
 
 
@@ -368,8 +364,7 @@ vdist_seqlp <- function(mean, sd, el) {
     lmax <- mean + (4 * sd)
   }
 
-  l <- seq(lmin, lmax, sd)
-  return(l)
+  seq(lmin, lmax, sd)
 }
 
 vdist_xmmp <- function(mean, sd, el) {
@@ -381,6 +376,5 @@ vdist_xmmp <- function(mean, sd, el) {
     xmax <- mean + (4 * sd)
   }
 
-  out <- c(xmin, xmax)
-  return(out)
+  c(xmin, xmax)
 }
diff --git a/R/vdist-t.R b/R/vdist-t.R
index 709a282..3007e5b 100644
--- a/R/vdist-t.R
+++ b/R/vdist-t.R
@@ -42,21 +42,21 @@ vdist_t_plot <- function(df = 3, print_plot = TRUE) {
   df <- as.integer(df)
   x  <- seq(-4, 4, 0.01)
 
-  plot_data <- data.frame(x = x, y = stats::dt(x, df))
+  plot_data <- data.frame(x = x, y = dt(x, df))
   poly_data <- data.frame(y = c(-4, seq(-4, 4, 0.01), 4),
-    z = c(0, stats::dt(seq(-4, 4, 0.01), df), 0))
+    z = c(0, dt(seq(-4, 4, 0.01), df), 0))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(ggplot2::aes(x = x, y = y), color = 'blue') +
-    ggplot2::ggtitle(label = 't Distribution', subtitle = paste("df =", df)) +
-    ggplot2::xlab('') + ggplot2::ylab('') +
-    ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = y, y = z),
+    ggplot(plot_data) +
+    geom_line(aes(x = x, y = y), color = 'blue') +
+    ggtitle(label = 't Distribution', subtitle = paste("df =", df)) +
+    xlab('') + ylab('') +
+    geom_polygon(data = poly_data, mapping = aes(x = y, y = z),
       fill = '#4682B4') +
-    ggplot2::scale_y_continuous(breaks = NULL) +
-    ggplot2::scale_x_continuous(breaks = -4:4) +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
+    scale_y_continuous(breaks = NULL) +
+    scale_x_continuous(breaks = -4:4) +
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5))
 
   if (print_plot) {
     print(gplot)
@@ -83,21 +83,21 @@ vdist_t_perc <- function(probs = 0.95, df = 4,
   ln      <- length(l)
 
   if (method == "lower") {
-    pp    <- round(stats::qt(probs, df), 3)
+    pp    <- round(qt(probs, df), 3)
     lc    <- c(l[1], pp, l[ln])
     col   <- c("#0000CD", "#6495ED")
     l1    <- c(1, 2)
     l2    <- c(2, 3)
   } else if (method == "upper") {
-    pp    <- round(stats::qt(probs, df, lower.tail = F), 3)
+    pp    <- round(qt(probs, df, lower.tail = F), 3)
     lc    <- c(l[1], pp, l[ln])
     col   <- c("#6495ED", "#0000CD")
     l1    <- c(1, 2)
     l2    <- c(2, 3)
   } else {
     alpha <- (1 - probs) / 2
-    pp1   <- round(stats::qt(alpha, df), 3)
-    pp2   <- round(stats::qt(alpha, df, lower.tail = F), 3)
+    pp1   <- round(qt(alpha, df), 3)
+    pp2   <- round(qt(alpha, df, lower.tail = F), 3)
     pp    <- c(pp1, pp2)
     lc    <- c(l[1], pp1, pp2, l[ln])
     col   <- c("#6495ED", "#0000CD", "#6495ED")
@@ -105,51 +105,51 @@ vdist_t_perc <- function(probs = 0.95, df = 4,
     l2    <- c(2, 3, 4)
   }
 
-  plot_data <- data.frame(x = l, y = stats::dt(l, df))
+  plot_data <- data.frame(x = l, y = dt(l, df))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(ggplot2::aes(x = x, y = y), color = 'blue') +
-    ggplot2::xlab(paste("df =", df)) + ggplot2::ylab('') +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5))
+    ggplot(plot_data) +
+    geom_line(aes(x = x, y = y), color = 'blue') +
+    xlab(paste("df =", df)) + ylab('') +
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5))
 
   if (method == "lower") {
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = "t Distribution",
+      ggtitle(label = "t Distribution",
         subtitle = paste0("P(X < ", pp, ") = ", probs * 100, "%")) +
-      ggplot2::annotate("text", label = paste0(probs * 100, "%"),
-        x = pp - 0.3, y = max(stats::dt(l, df)) + 0.025, color = "#0000CD",
+      annotate("text", label = paste0(probs * 100, "%"),
+        x = pp - 0.3, y = max(dt(l, df)) + 0.025, color = "#0000CD",
         size = 3) +
-      ggplot2::annotate("text", label = paste0((1 - probs) * 100, "%"),
-        x = pp + 0.3, y = max(stats::dt(l, df)) + 0.025, color = "#6495ED",
+      annotate("text", label = paste0((1 - probs) * 100, "%"),
+        x = pp + 0.3, y = max(dt(l, df)) + 0.025, color = "#6495ED",
         size = 3)
 
   } else if (method == "upper") {
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = "t Distribution",
+      ggtitle(label = "t Distribution",
         subtitle = paste0("P(X > ", pp, ") = ", probs * 100, "%")) +
-      ggplot2::annotate("text", label = paste0((1 - probs) * 100, "%"),
-        x = pp - 0.3, y = max(stats::dt(l, df)) + 0.025, color = "#6495ED",
+      annotate("text", label = paste0((1 - probs) * 100, "%"),
+        x = pp - 0.3, y = max(dt(l, df)) + 0.025, color = "#6495ED",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(probs * 100, "%"),
-        x = pp + 0.3, y = max(stats::dt(l, df)) + 0.025, color = "#0000CD",
+      annotate("text", label = paste0(probs * 100, "%"),
+        x = pp + 0.3, y = max(dt(l, df)) + 0.025, color = "#0000CD",
         size = 3)
   } else {
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = "t Distribution",
+      ggtitle(label = "t Distribution",
         subtitle = paste0("P(", pp[1], " < X < ", pp[2], ") = ", probs * 100, "%")) +
-      ggplot2::annotate("text", label = paste0(probs * 100, "%"),
-        x = mean(l), y = max(stats::dt(l, df)) + 0.025, color = "#0000CD",
+      annotate("text", label = paste0(probs * 100, "%"),
+        x = mean(l), y = max(dt(l, df)) + 0.025, color = "#0000CD",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(alpha * 100, "%"),
-        x = pp[1] - 0.3, y = max(stats::dt(l, df)) + 0.025, color = "#6495ED",
+      annotate("text", label = paste0(alpha * 100, "%"),
+        x = pp[1] - 0.3, y = max(dt(l, df)) + 0.025, color = "#6495ED",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(alpha * 100, "%"),
-        x = pp[2] + 0.3, y = max(stats::dt(l, df)) + 0.025, color = "#6495ED",
+      annotate("text", label = paste0(alpha * 100, "%"),
+        x = pp[2] + 0.3, y = max(dt(l, df)) + 0.025, color = "#6495ED",
         size = 3)
   }
 
@@ -157,7 +157,7 @@ vdist_t_perc <- function(probs = 0.95, df = 4,
     poly_data <- vdist_pol_t(lc[l1[i]], lc[l2[i]], df)
     gplot <-
       gplot +
-      ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = x, y = y), fill = col[i])
+      geom_polygon(data = poly_data, mapping = aes(x = x, y = y), fill = col[i])
   }
 
   pln <- length(pp)
@@ -168,15 +168,15 @@ vdist_t_perc <- function(probs = 0.95, df = 4,
 
     gplot <-
       gplot +
-      ggplot2::geom_vline(xintercept = pp[i], linetype = 2, size = 1) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x, y = y),
+      geom_vline(xintercept = pp[i], linetype = 2, size = 1) +
+      geom_point(data = point_data, mapping = aes(x = x, y = y),
       shape = 4, color = 'red', size = 3)
   }
 
   gplot <-
     gplot +
-      ggplot2::scale_y_continuous(breaks = NULL) +
-      ggplot2::scale_x_continuous(breaks = -5:5)
+      scale_y_continuous(breaks = NULL) +
+      scale_x_continuous(breaks = -5:5)
 
   if (print_plot) {
     print(gplot)
@@ -208,13 +208,13 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
   ln <- length(l)
 
   if (method == "lower") {
-    pp  <- round(stats::pt(perc, df), 3)
+    pp  <- round(pt(perc, df), 3)
     lc  <- c(l[1], perc, l[ln])
     col <- c("#0000CD", "#6495ED")
     l1  <- c(1, 2)
     l2  <- c(2, 3)
   } else if (method == "upper") {
-    pp  <- round(stats::pt(perc, df, lower.tail = F), 3)
+    pp  <- round(pt(perc, df, lower.tail = F), 3)
     lc  <- c(l[1], perc, l[ln])
     col <- c("#6495ED", "#0000CD")
     l1  <- c(1, 2)
@@ -224,8 +224,8 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
       perc <- -perc
     }
 
-    pp1 <- round(stats::pt(-perc, df), 3)
-    pp2 <- round(stats::pt(perc, df, lower.tail = F), 3)
+    pp1 <- round(pt(-perc, df), 3)
+    pp2 <- round(pt(perc, df, lower.tail = F), 3)
     pp  <- c(pp1, pp2)
     lc  <- c(l[1], -perc, perc, l[ln])
     col <- c("#6495ED", "#0000CD", "#6495ED")
@@ -236,8 +236,8 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
       perc <- -perc
     }
 
-    pp1 <- round(stats::pt(-perc, df), 3)
-    pp2 <- round(stats::pt(perc, df, lower.tail = F), 3)
+    pp1 <- round(pt(-perc, df), 3)
+    pp2 <- round(pt(perc, df, lower.tail = F), 3)
     pp  <- c(pp1, pp2)
     lc  <- c(l[1], -perc, perc, l[ln])
     col <- c("#0000CD", "#6495ED", "#0000CD")
@@ -245,22 +245,22 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
     l2  <- c(2, 3, 4)
   }
 
-  plot_data <- data.frame(x = l, y = stats::dt(l, df))
+  plot_data <- data.frame(x = l, y = dt(l, df))
 
   gplot <-
-    ggplot2::ggplot(plot_data) +
-    ggplot2::geom_line(ggplot2::aes(x = x, y = y), color = 'blue') +
-    ggplot2::xlab(paste("df =", df)) + ggplot2::ylab('') +
-    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
-                   plot.subtitle = ggplot2::element_text(hjust = 0.5)) +
-    ggplot2::scale_x_continuous(breaks = min(l):max(l)) +
-    ggplot2::scale_y_continuous(breaks = NULL)
+    ggplot(plot_data) +
+    geom_line(aes(x = x, y = y), color = 'blue') +
+    xlab(paste("df =", df)) + ylab('') +
+    theme(plot.title = element_text(hjust = 0.5),
+                   plot.subtitle = element_text(hjust = 0.5)) +
+    scale_x_continuous(breaks = min(l):max(l)) +
+    scale_y_continuous(breaks = NULL)
 
   for (i in seq_len(length(l1))) {
     poly_data <- vdist_pol_t(lc[l1[i]], lc[l2[i]], df)
     gplot <-
       gplot +
-      ggplot2::geom_polygon(data = poly_data, mapping = ggplot2::aes(x = x, y = y), fill = col[i])
+      geom_polygon(data = poly_data, mapping = aes(x = x, y = y), fill = col[i])
   }
 
 
@@ -270,16 +270,16 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
 
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = "t Distribution",
+      ggtitle(label = "t Distribution",
         subtitle = paste0("P(X < ", perc, ") = ", pp * 100, "%")) +
-      ggplot2::annotate("text", label = paste0(pp * 100, "%"),
-        x = perc - 1, y = max(stats::dt(l, df)) + 0.07, color = "#0000CD",
+      annotate("text", label = paste0(pp * 100, "%"),
+        x = perc - 1, y = max(dt(l, df)) + 0.07, color = "#0000CD",
         size = 3) +
-      ggplot2::annotate("text", label = paste0((1 - pp) * 100, "%"),
-        x = perc + 1, y = max(stats::dt(l, df)) + 0.07, color = "#6495ED",
+      annotate("text", label = paste0((1 - pp) * 100, "%"),
+        x = perc + 1, y = max(dt(l, df)) + 0.07, color = "#6495ED",
         size = 3) +
-      ggplot2::geom_vline(xintercept = perc, linetype = 2, size = 1) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x, y = y),
+      geom_vline(xintercept = perc, linetype = 2, size = 1) +
+      geom_point(data = point_data, mapping = aes(x = x, y = y),
       shape = 4, color = 'red', size = 3)
 
   } else if (method == "upper") {
@@ -288,16 +288,16 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
 
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = "t Distribution",
+      ggtitle(label = "t Distribution",
         subtitle = paste0("P(X > ", perc, ") = ", pp * 100, "%")) +
-      ggplot2::annotate("text", label = paste0((1 - pp) * 100, "%"),
-        x = perc - 1, y = max(stats::dt(l, df)) + 0.07, color = "#0000CD",
+      annotate("text", label = paste0((1 - pp) * 100, "%"),
+        x = perc - 1, y = max(dt(l, df)) + 0.07, color = "#0000CD",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(pp * 100, "%"),
-        x = perc + 1, y = max(stats::dt(l, df)) + 0.07, color = "#6495ED",
+      annotate("text", label = paste0(pp * 100, "%"),
+        x = perc + 1, y = max(dt(l, df)) + 0.07, color = "#6495ED",
         size = 3) +
-      ggplot2::geom_vline(xintercept = perc, linetype = 2, size = 1) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x, y = y),
+      geom_vline(xintercept = perc, linetype = 2, size = 1) +
+      geom_point(data = point_data, mapping = aes(x = x, y = y),
       shape = 4, color = 'red', size = 3)
 
   } else if (method == "interval") {
@@ -306,21 +306,21 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
 
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = "t Distribution",
+      ggtitle(label = "t Distribution",
         subtitle = paste0("P(", -perc, " < X < ", perc, ") = ", (1 - (pp1 + pp2)) * 100, "%")) +
-      ggplot2::annotate("text", label = paste0((1 - (pp1 + pp2)) * 100, "%"),
-        x = 0, y = max(stats::dt(l, df)) + 0.07, color = "#0000CD", size = 3) +
-      ggplot2::annotate("text", label = paste0(pp[1] * 100, "%"),
-        x = perc + 1, y = max(stats::dt(l, df)) + 0.07, color = "#6495ED",
+      annotate("text", label = paste0((1 - (pp1 + pp2)) * 100, "%"),
+        x = 0, y = max(dt(l, df)) + 0.07, color = "#0000CD", size = 3) +
+      annotate("text", label = paste0(pp[1] * 100, "%"),
+        x = perc + 1, y = max(dt(l, df)) + 0.07, color = "#6495ED",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(pp[2] * 100, "%"),
-        x = -perc - 1, y = max(stats::dt(l, df)) + 0.07, color = "#6495ED",
+      annotate("text", label = paste0(pp[2] * 100, "%"),
+        x = -perc - 1, y = max(dt(l, df)) + 0.07, color = "#6495ED",
         size = 3) +
-      ggplot2::geom_vline(xintercept = perc, linetype = 2, size = 1) +
-      ggplot2::geom_vline(xintercept = -perc, linetype = 2, size = 1) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x1, y = y),
+      geom_vline(xintercept = perc, linetype = 2, size = 1) +
+      geom_vline(xintercept = -perc, linetype = 2, size = 1) +
+      geom_point(data = point_data, mapping = aes(x = x1, y = y),
       shape = 4, color = 'red', size = 3) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x2, y = y),
+      geom_point(data = point_data, mapping = aes(x = x2, y = y),
       shape = 4, color = 'red', size = 3)
   } else {
 
@@ -328,21 +328,21 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
 
     gplot <-
       gplot +
-      ggplot2::ggtitle(label = "t Distribution",
+      ggtitle(label = "t Distribution",
         subtitle = paste0("P(|X| > ", perc, ") = ", (pp1 + pp2) * 100, "%")) +
-      ggplot2::annotate("text", label = paste0((1 - (pp1 + pp2)) * 100, "%"),
-        x = 0, y = max(stats::dt(l, df)) + 0.07, color = "#0000CD", size = 3) +
-      ggplot2::annotate("text", label = paste0(pp[1] * 100, "%"),
-        x = perc + 1, y = max(stats::dt(l, df)) + 0.07, color = "#6495ED",
+      annotate("text", label = paste0((1 - (pp1 + pp2)) * 100, "%"),
+        x = 0, y = max(dt(l, df)) + 0.07, color = "#0000CD", size = 3) +
+      annotate("text", label = paste0(pp[1] * 100, "%"),
+        x = perc + 1, y = max(dt(l, df)) + 0.07, color = "#6495ED",
         size = 3) +
-      ggplot2::annotate("text", label = paste0(pp[2] * 100, "%"),
-        x = -perc - 1, y = max(stats::dt(l, df)) + 0.07, color = "#6495ED",
+      annotate("text", label = paste0(pp[2] * 100, "%"),
+        x = -perc - 1, y = max(dt(l, df)) + 0.07, color = "#6495ED",
         size = 3) +
-      ggplot2::geom_vline(xintercept = perc, linetype = 2, size = 1) +
-      ggplot2::geom_vline(xintercept = -perc, linetype = 2, size = 1) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x1, y = y),
+      geom_vline(xintercept = perc, linetype = 2, size = 1) +
+      geom_vline(xintercept = -perc, linetype = 2, size = 1) +
+      geom_point(data = point_data, mapping = aes(x = x1, y = y),
       shape = 4, color = 'red', size = 3) +
-      ggplot2::geom_point(data = point_data, mapping = ggplot2::aes(x = x2, y = y),
+      geom_point(data = point_data, mapping = aes(x = x2, y = y),
       shape = 4, color = 'red', size = 3)
   }
 
@@ -357,7 +357,6 @@ vdist_t_prob <- function(perc = 1.6, df = 7,
 
 vdist_pol_t <- function(l1, l2, df) {
   x    <- c(l1, seq(l1, l2, 0.01), l2)
-  y    <- c(0, stats::dt(seq(l1, l2, 0.01), df), 0)
-  data <- data.frame(x = x, y = y)
-  return(data)
+  y    <- c(0, dt(seq(l1, l2, 0.01), df), 0)
+  data.frame(x = x, y = y)
 }
diff --git a/R/vdist-utils.R b/R/vdist-utils.R
index 54a7522..6531732 100644
--- a/R/vdist-utils.R
+++ b/R/vdist-utils.R
@@ -1,7 +1,8 @@
-#' @importFrom utils packageVersion menu install.packages
+#' @import utils 
+#' @import ggplot2
 check_suggests <- function(pkg) {
 
-  pkg_flag <- tryCatch(utils::packageVersion(pkg), error = function(e) NA)
+  pkg_flag <- tryCatch(packageVersion(pkg), error = function(e) NA)
 
   if (is.na(pkg_flag)) {
 
@@ -9,8 +10,8 @@ check_suggests <- function(pkg) {
 
     if (interactive()) {
       message(msg, "\nWould you like to install it?")
-      if (utils::menu(c("Yes", "No")) == 1) {
-        utils::install.packages(pkg)
+      if (menu(c("Yes", "No")) == 1) {
+        install.packages(pkg)
       } else {
         stop(msg, call. = FALSE)
       }
diff --git a/R/vistributions.R b/R/vistributions.R
index 633a791..6ca6f7e 100644
--- a/R/vistributions.R
+++ b/R/vistributions.R
@@ -8,7 +8,7 @@ NULL
 
 ## quiets concerns of R CMD check re: the .'s that appear in pipelines
 if (getRversion() >= "2.15.1") {
-  utils::globalVariables(c(
+  globalVariables(c(
     ".", "df", "chi", "x", "y", "z", "x1", "x2"
   ))
 }
diff --git a/R/zzz.R b/R/zzz.R
index d148d35..ae9f404 100644
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -1,16 +1,17 @@
-#' @importFrom magrittr %>%
+#' @import magrittr 
+#' @import stats
 .onAttach <- function(...) {
 
-  if (!interactive() || stats::runif(1) > 0.1) return()
+  if (!interactive() || runif(1) > 0.1) return()
 
-  pkgs <- utils::available.packages()
+  pkgs <- available.packages()
   
   cran_version <- 
     pkgs %>%
-    magrittr::extract("vistributions", "Version") %>%
+    extract("vistributions", "Version") %>%
     package_version()
 
-  local_version <- utils::packageVersion("vistributions")
+  local_version <- packageVersion("vistributions")
   behind_cran <- cran_version > local_version
 
   tips <- c(
@@ -26,8 +27,8 @@
     if (behind_cran) {
       msg <- "A new version of vistributions is available with bug fixes and new features."
       packageStartupMessage(msg, "\nWould you like to install it?")
-      if (utils::menu(c("Yes", "No")) == 1) {
-        utils::update.packages("vistributions")
+      if (menu(c("Yes", "No")) == 1) {
+        update.packages("vistributions")
       } 
     } else {
       packageStartupMessage(paste(strwrap(tip), collapse = "\n"))
diff --git a/README.Rmd b/README.Rmd
index 946a131..082d154 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -19,7 +19,7 @@ knitr::opts_chunk$set(
 <!-- badges: start -->
 [![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/vistributions)](https://cran.r-project.org/package=vistributions) [![cran checks](https://cranchecks.info/badges/summary/vistributions)](https://cran.r-project.org/web/checks/check_results_vistributions.html) 
 [![R build status](https://github.com/rsquaredacademy/vistributions/workflows/R-CMD-check/badge.svg)](https://github.com/rsquaredacademy/vistributions/actions)
-[![Coverage Status](https://img.shields.io/codecov/c/github/rsquaredacademy/vistributions/master.svg)](https://codecov.io/github/rsquaredacademy/vistributions?branch=master) [![status](https://tinyverse.netlify.com/badge/vistributions)](https://CRAN.R-project.org/package=vistributions) [![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing) [![](https://cranlogs.r-pkg.org/badges/grand-total/vistributions)](https://cran.r-project.org/package=vistributions) 
+[![Coverage Status](https://img.shields.io/codecov/c/github/rsquaredacademy/vistributions/master.svg)](https://codecov.io/github/rsquaredacademy/vistributions?branch=master) [![status](https://tinyverse.netlify.com/badge/vistributions)](https://CRAN.R-project.org/package=vistributions) [![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html) [![](https://cranlogs.r-pkg.org/badges/grand-total/vistributions)](https://cran.r-project.org/package=vistributions) 
 <!-- badges: end -->
 
 ## Installation
@@ -35,7 +35,7 @@ devtools::install_github("rsquaredacademy/vistributions")
 
 ## Articles
 
-- [Explore Distributions](https://vistributions.rsquaredacademy.com/articles/introduction_to_vistributions.html)
+- [Explore Distributions](https://vistributions.rsquaredacademy.com/articles/introduction-to-vistributions.html)
 
 ## Usage
 
@@ -61,7 +61,3 @@ vdist_normal_prob(c(-1.74, 1.83), type = 'both')
 If you encounter a bug, please file a minimal reproducible example using 
 [reprex](https://reprex.tidyverse.org/index.html) on github. For questions 
 and clarifications, use [StackOverflow](https://stackoverflow.com/).
-
-## Community Guidelines
-
-Please note that the 'vistributions' project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By contributing to this project, you agree to abide by its terms.
diff --git a/README.md b/README.md
index 491a81d..fc0b87e 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,8 @@ status](https://github.com/rsquaredacademy/vistributions/workflows/R-CMD-check/b
 [![Coverage
 Status](https://img.shields.io/codecov/c/github/rsquaredacademy/vistributions/master.svg)](https://codecov.io/github/rsquaredacademy/vistributions?branch=master)
 [![status](https://tinyverse.netlify.com/badge/vistributions)](https://CRAN.R-project.org/package=vistributions)
-[![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
+[![Lifecycle:
+stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html)
 [![](https://cranlogs.r-pkg.org/badges/grand-total/vistributions)](https://cran.r-project.org/package=vistributions)
 <!-- badges: end -->
 
@@ -32,8 +33,8 @@ devtools::install_github("rsquaredacademy/vistributions")
 
 ## Articles
 
-  - [Explore
-    Distributions](https://vistributions.rsquaredacademy.com/articles/introduction_to_vistributions.html)
+-   [Explore
+    Distributions](https://vistributions.rsquaredacademy.com/articles/introduction-to-vistributions.html)
 
 ## Usage
 
@@ -47,7 +48,6 @@ vdist_normal_plot()
 <img src="man/figures/README-normal-1.png" width="100%" />
 
 ``` r
-
 # visualize quantiles out of given probability
 vdist_normal_perc(0.95, mean = 2, sd = 1.36, type = 'both')
 ```
@@ -55,7 +55,6 @@ vdist_normal_perc(0.95, mean = 2, sd = 1.36, type = 'both')
 <img src="man/figures/README-normal-2.png" width="100%" />
 
 ``` r
-
 # visualize probability from a given quantile
 vdist_normal_prob(c(-1.74, 1.83), type = 'both')
 ```
@@ -68,9 +67,3 @@ If you encounter a bug, please file a minimal reproducible example using
 [reprex](https://reprex.tidyverse.org/index.html) on github. For
 questions and clarifications, use
 [StackOverflow](https://stackoverflow.com/).
-
-## Community Guidelines
-
-Please note that the ‘vistributions’ project is released with a
-[Contributor Code of Conduct](CODE_OF_CONDUCT.md). By contributing to
-this project, you agree to abide by its terms.
diff --git a/_pkgdown.yml b/_pkgdown.yml
index a07ac6b..5bde5f8 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -7,6 +7,7 @@ authors:
 templates:
   params:
     bootswatch: cosmo
+    ganalytics: UA-57270671-33
     docsearch:
       api_key:
       index_name: vistributions
diff --git a/cran-comments.md b/cran-comments.md
index 4b837cb..9325a47 100644
--- a/cran-comments.md
+++ b/cran-comments.md
@@ -1,6 +1,6 @@
 ## Test environments
-* local Windows 10, R 3.5.2
-* ubuntu 14.04 (on travis-ci), R 3.4.4, R 3.5.2, R devel
+* local Windows 10 install, R 4.0.4
+* ubuntu 14.04 (on GitHub Actions), R 4.1.0, R-devel
 * win-builder (devel and release)
 
 ## R CMD check results