{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Statystyka i Analiza danych\n",
    "# Laboratorium 6 - Wykresy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pomocnicze funkcje do rysowania wykresów"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_crit  <- function(t, crit, df = 0) {\n",
    "    dist  <- function(x, df) {\n",
    "        if (df == 0)\n",
    "            dnorm(x)\n",
    "        else \n",
    "            dt(x, df)\n",
    "    }\n",
    "    x_max  <- max(3, abs(t))\n",
    "    x  <- seq(-x_max, x_max, 0.1)\n",
    "    y  <- dist(x, df)\n",
    "    plot(x, y, type=\"l\", main=paste(crit, \" \"))\n",
    "    abline(v = t, col=\"blue\", lty=2)\n",
    "    for (c in crit) {\n",
    "        if (c > 0) {\n",
    "            x_c  <- c(c, c, x[x > c], max(x))\n",
    "            y_c  <- c(0, dist(c, df), y[x > c], 0) \n",
    "        } else {\n",
    "            x_c  <- c(min(x), x[x < c], c, c)\n",
    "            y_c  <- c(0, y[x < c], dist(c, df), 0)             \n",
    "        }\n",
    "        polygon(x_c, y_c, border=NA, col=\"firebrick1\")\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_norm  <- function(z, alpha, type = \"ne\") {\n",
    "    if (type == \"ne\") {\n",
    "        z_crit  <- qnorm(alpha/2, lower.tail = FALSE)\n",
    "        plot_crit(z, c(-z_crit, z_crit))\n",
    "    } else {\n",
    "        z_crit  <- qnorm(alpha, lower.tail = FALSE)\n",
    "        plot_crit(z, ifelse(type == \"gt\", z_crit, -z_crit))\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_t  <- function(t, alpha, df, type = \"ne\") {\n",
    "    if (type == \"ne\") {\n",
    "        t_crit  <- qt(alpha/2, df, lower.tail = FALSE)\n",
    "        plot_crit(t, c(-t_crit, t_crit))\n",
    "    } else {\n",
    "        t_crit  <- qt(alpha, df, lower.tail = FALSE)\n",
    "        plot_crit(t, ifelse(type == \"gt\", t_crit, -t_crit))\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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JRj1TlWMRghGSKkPAjJECHlQUh+JFl1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\nAEICBBASIICQAAGEBAggJEAAIQEC/geqNDr7GwhXdwAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"-1.76131013577489  \""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_t(-1.07, 0.05, 14, \"lt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3KI1OFlHDCWB5NTHx0iHfAyDRjNo9Fpzw6Rfu2GwR5pPg9np7yGEOnJLBDJP4+H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\nib0J9cnJ8wAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_norm(-1.07, 0.05, \"ne\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}