From 0807c5a20b813d5b70e51d359469cc99e79f3ad3 Mon Sep 17 00:00:00 2001 From: paula de leon Date: Mon, 22 Jul 2024 18:18:40 +0000 Subject: [PATCH 1/2] ejercicio 1 --- notebook/problems.ipynb | 101 +++++++++++++++++++++++++++++++++++++-- notebook/solutions.ipynb | 20 ++++---- 2 files changed, 108 insertions(+), 13 deletions(-) diff --git a/notebook/problems.ipynb b/notebook/problems.ipynb index a253f320..1d84f542 100644 --- a/notebook/problems.ipynb +++ b/notebook/problems.ipynb @@ -24,12 +24,107 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 9, "id": "34720ab6", "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "La media de los elementos con distribución normal es: -0.02575701913475372\n", + "La media de los elementos con distribución chi-cuadrado es: 3.1341815977631926\n", + "La mediana de los elementos con distribución normal es: 0.06711738230446523\n", + "La mediana de los elementos con distribución chi-cuadrado es: 2.264034231107231\n", + "La moda de los elementos con distribución normal es: 0.1504587572000871\n", + "La moda de los elementos con distribución chi-cuadrado es: 2.158281311033611\n", + "El rango de los elementos con distribución normal es: 5.282970897189165\n", + "El rango de los elementos con distribución chi-cuadrado es: 9.345939537979136\n", + "La varianza de los elementos con distribución normal es: 1.0575524438121537\n", + "La varianza de los elementos con distribución chi-cuadrado es: 6.242600009195317\n", + "La desviación típica de los elementos con distribución normal es: 1.028373688798072\n", + "La desviación típica de los elementos con distribución chi-cuadrado es: 2.4985195635006177\n", + "La oblicuidad de los elementos con distribución normal es: -0.6331162644708517\n", + "La oblicuidad de los elementos con distribución chi-cuadrado es: 0.9909054595855211\n", + "La curtosis de los elementos con distribución normal es: 0.5208785728358238\n", + "La curtosis de los elementos con distribución chi-cuadrado es: -0.10824014999966147\n" + ] + } + ], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c8390ef8", + "metadata": {}, "outputs": [], "source": [ - "# TODO" + "# TODO\n", + "import numpy as np \n", + "normal = np.random.normal(size=100)\n", + "chicua= np.random.chisquare(3,100)\n", + "\n", + "import statistics as stats\n", + "\n", + "#Media \n", + "media_normal = stats.mean(normal)\n", + "media_chi = stats.mean(chicua)\n", + "\n", + "print(f\"La media de los elementos con distribución normal es: {media_normal}\")\n", + "print(f\"La media de los elementos con distribución chi-cuadrado es: {media_chi}\")\n", + "\n", + "#Mediana\n", + "mediana_normal = stats.median(normal)\n", + "mediana_chi = stats.median(chicua)\n", + "\n", + "print(f\"La mediana de los elementos con distribución normal es: {mediana_normal}\")\n", + "print(f\"La mediana de los elementos con distribución chi-cuadrado es: {mediana_chi}\")\n", + "\n", + "#Moda \n", + "moda_normal = stats.mode(normal)\n", + "moda_chi = stats.mode(chicua)\n", + "\n", + "print(f\"La moda de los elementos con distribución normal es: {moda_normal}\")\n", + "print(f\"La moda de los elementos con distribución chi-cuadrado es: {moda_chi}\")\n", + "\n", + "#Rango\n", + "rango_normal = max(normal) - min(normal)\n", + "rango_chi = max(chicua) - min(chicua)\n", + "\n", + "print(f\"El rango de los elementos con distribución normal es: {rango_normal}\")\n", + "print(f\"El rango de los elementos con distribución chi-cuadrado es: {rango_chi}\")\n", + "\n", + "#Varianza \n", + "var_normal = stats.variance(normal)\n", + "var_chi = stats.variance(chicua)\n", + "\n", + "print(f\"La varianza de los elementos con distribución normal es: {var_normal}\")\n", + "print(f\"La varianza de los elementos con distribución chi-cuadrado es: {var_chi}\")\n", + "\n", + "#Desviación típica \n", + "dt_normal = stats.stdev(normal)\n", + "dt_chi = stats.stdev(chicua)\n", + "\n", + "print(f\"La desviación típica de los elementos con distribución normal es: {dt_normal}\")\n", + "print(f\"La desviación típica de los elementos con distribución chi-cuadrado es: {dt_chi}\")\n", + "\n", + "#Oblicuidad \n", + "from scipy.stats import skew\n", + "sk_normal = skew(normal)\n", + "sk_chi = skew(chicua)\n", + "\n", + "print(f\"La oblicuidad de los elementos con distribución normal es: {sk_normal}\")\n", + "print(f\"La oblicuidad de los elementos con distribución chi-cuadrado es: {sk_chi}\")\n", + "\n", + "#Curtosis\n", + "from scipy.stats import kurtosis\n", + "kur_normal = kurtosis(normal)\n", + "kur_chi = kurtosis(chicua)\n", + "\n", + "print(f\"La curtosis de los elementos con distribución normal es: {kur_normal}\")\n", + "print(f\"La curtosis de los elementos con distribución chi-cuadrado es: {kur_chi}\")\n", + "\n" ] }, { @@ -76,7 +171,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.12.4" } }, "nbformat": 4, diff --git a/notebook/solutions.ipynb b/notebook/solutions.ipynb index 3c9d6d5c..c3fdaaf4 100644 --- a/notebook/solutions.ipynb +++ b/notebook/solutions.ipynb @@ -18,7 +18,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 2, "id": "34720ab6", "metadata": {}, "outputs": [ @@ -93,7 +93,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 3, "id": "75ec280a", "metadata": {}, "outputs": [ @@ -123,7 +123,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 4, "id": "d7644384", "metadata": {}, "outputs": [ @@ -153,7 +153,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 5, "id": "3e8f1c6f", "metadata": {}, "outputs": [ @@ -189,7 +189,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 6, "id": "2f31b2e1", "metadata": {}, "outputs": [ @@ -219,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 7, "id": "a8b51d2f", "metadata": {}, "outputs": [ @@ -254,7 +254,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 8, "id": "2b42a0af", "metadata": {}, "outputs": [ @@ -287,7 +287,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 9, "id": "968348dd", "metadata": {}, "outputs": [ @@ -331,7 +331,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 10, "id": "d590308e", "metadata": {}, "outputs": [ @@ -402,7 +402,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.12.4" } }, "nbformat": 4, From 4e069e8a8a5bee1493203bbae69244ef987a4b2f Mon Sep 17 00:00:00 2001 From: paula de leon Date: Wed, 24 Jul 2024 17:24:57 +0000 Subject: [PATCH 2/2] terminado --- notebook/problems.ipynb | 32 +++++++++++++++++++++++++++++--- 1 file changed, 29 insertions(+), 3 deletions(-) diff --git a/notebook/problems.ipynb b/notebook/problems.ipynb index 1d84f542..78937ca0 100644 --- a/notebook/problems.ipynb +++ b/notebook/problems.ipynb @@ -143,12 +143,38 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 20, "id": "d590308e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "La desviación estándar es: 2.0\n" + ] + } + ], "source": [ - "# TODO" + "# TODO\n", + "\n", + "data = [4,2,5,8,6]\n", + "N=len(data)\n", + "import statistics as stats\n", + "\n", + "media = stats.mean(data)\n", + "\n", + "def st_dev(lista):\n", + " suma = 0\n", + " for i in lista:\n", + " suma +=(i-media)**2 \n", + " varianza = suma / N\n", + " desviacion = varianza **0.5\n", + " return desviacion\n", + "\n", + "\n", + "\n", + "print(f\"La desviación estándar es: {st_dev(data)}\")" ] } ],