diff --git a/notebook/problems.ipynb b/notebook/problems.ipynb index a253f320..a5ac3433 100644 --- a/notebook/problems.ipynb +++ b/notebook/problems.ipynb @@ -27,9 +27,109 @@ "execution_count": 1, "id": "34720ab6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Normal vector: [-0.14 2.06 0.28 1.33 -0.15 -0.07 0.76 0.83 -0.11 -2.37 -0.17 0.69\n", + " 0.02 0.46 0.27 -1.44 0.88 -0.58 -0.5 0.59 -0.73 0.26 -0.86 -0.19\n", + " -0.37 -0.46 -0.82 -0.05 0.12 0.93 -0.57 0.05 2.21 0.39 0.48 0.43\n", + " -1.7 -0.24 -2.14 0.86 1.7 -0.53 1.76 -1.12 -1.19 0.55 -0.82 -0.5\n", + " 1.09 -0.97 -0.28 -0.12 0.38 0.73 -0.1 -1.2 1.01 2.88 0.82 0.56\n", + " -0.38 -0.25 -1.39 0.62 -0.14 1.29 -1.04 1.36 -0.31 -0.61 -0.48 -0.61\n", + " -2.09 0.64 0.77 1.28 0.71 0.66 -1.68 0.18 -1.13 -0.28 1.4 0.03\n", + " -2.61 -1. -0.57 -0.23 0.94 0.84 0.81 0.23 -0.3 -0.36 0.43 0.93\n", + " 1.55 0.09 0.29 1.49]\n", + "\n", + " Chi square vector: [0.68 4.59 6.88 8. 0.75 3.57 2.09 2.69 3.27 0.74 4.13 3.75 5.86 0.75\n", + " 5.25 5.22 4.24 2.33 2.63 1.13 1.72 0.32 1.82 0.49 1.57 0.54 3.13 0.7\n", + " 6.19 2.07 0.85 0.43 4.24 4.89 2.1 1.44 1.5 0.85 5.31 1.87 1.95 1.\n", + " 2.2 1.63 1.43 1.81 3.34 5.18 0.74 0.67 0.81 2.43 1.89 0.82 4.39 3.41\n", + " 1.3 2.76 1.61 1.81 1.53 4.34 1.95 0.49 7.05 3.21 6.3 2.58 3.76 0.23\n", + " 2.36 5.88 4.16 0.42 6.48 1.27 4.36 1.55 2.1 3.53 1.82 0.14 1.64 1.95\n", + " 1.37 3.26 2.03 0.5 0.19 2.76 1.44 6.12 1.1 5.01 3.53 1.1 4.53 7.01\n", + " 1.69 4.27] \n", + "Normal mean: 0.05970000000000001\n", + "\n", + "Chi mean: 2.6677\n", + "\n", + "Normal median: 0.025\n", + " Chi Square median: 2.05\n", + "\n", + "Normal mode: -0.14 \n", + " Chi Square mode: 1.95\n", + "\n", + "Normal range: 2.7399999999999998 \n", + "Chi range: 7.86\n", + "\n", + " Normal variance is: 0.9918029393939394 and normal standard desviation 0.9958930361208173\n", + "\n", + "Chi Square vaciance is: 3.629947181818182 and chi standard desviation 1.9052420270973927\n", + "\n", + "Normal skewness: -0.11747207959176492 Chi Skewness 0.8022466752368267\n", + "\n", + " Normal kurtosis: 0.3342063860928839 Chi Kurtosis -0.2580203698679746\n" + ] + } + ], "source": [ - "# TODO" + "import numpy as np\n", + "\n", + "np.random.seed(99)\n", + "\n", + "normal = np.random.normal(size=100)\n", + "chi_square = np.random.chisquare(3, 100)\n", + "normal_rounded = np.round(normal, decimals=2)\n", + "chi_square_rounded = np.round(chi_square, decimals=2)\n", + "\n", + "print(f\"\\nNormal vector: {normal_rounded}\\n\\n Chi square vector: {chi_square_rounded} \")\n", + "\n", + "#_______________MEASURES_____________________________________________________________\n", + "\n", + "import statistics as stats\n", + "\n", + "#MEAN\n", + "print(f\"Normal mean: {stats.mean(normal_rounded)}\")\n", + "print(f\"\\nChi mean: {stats.mean(chi_square_rounded)}\")\n", + "\n", + "#MEDIAN\n", + "print(f\"\\nNormal median: {stats.median(normal_rounded)}\\n Chi Square median: {stats.median(chi_square_rounded)}\")\n", + "\n", + "#MODE\n", + "print(f\"\\nNormal mode: {stats.mode(normal_rounded)} \\n Chi Square mode: {stats.mode(chi_square_rounded)}\")\n", + "\n", + "#_________________MEASURES OF DISPERSION_________________________________\n", + "\n", + "#RANGE\n", + "normal_range = max(normal_rounded)-min(chi_square_rounded)\n", + "chi_range = max(chi_square_rounded)-min(chi_square_rounded)\n", + "print(f\"\\nNormal range: {normal_range} \\nChi range: {chi_range}\")\n", + "\n", + "#STANDARD DESVIATION AND VARIANCE______________\n", + "normal_var = stats.variance(normal_rounded)\n", + "chi_var = stats.variance(chi_square_rounded)\n", + "normal_sd = stats.stdev(normal_rounded)\n", + "chi_sd = stats.stdev(chi_square_rounded)\n", + "print(f\"\\n Normal variance is: {normal_var} and normal standard desviation {normal_sd}\")\n", + "print(f\"\\nChi Square vaciance is: {chi_var} and chi standard desviation {chi_sd}\")\n", + "\n", + "#SHAPE MEASURES____________\n", + "\n", + "#SKEWNESS\n", + "from scipy.stats import skew,kurtosis \n", + "\n", + "normal_skew = skew(normal_rounded)\n", + "chi_skew = skew(chi_square_rounded)\n", + "print(f\"\\nNormal skewness: {normal_skew} Chi Skewness {chi_skew}\")\n", + "\n", + "#KURTOSIS \n", + "normal_kurt = kurtosis(normal_rounded)\n", + "chi_kurt = kurtosis(chi_square_rounded)\n", + "print(f\"\\n Normal kurtosis: {normal_kurt} Chi Kurtosis {chi_kurt}\")\n", + "\n", + "\n" ] }, { @@ -48,12 +148,55 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "d590308e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data: [4, 2, 5, 8, 6]\n", + "the standard deviation for these data is: 2.23606797749979\n" + ] + } + ], "source": [ - "# TODO" + "import math\n", + "import sys\n", + "\n", + "data = [4, 2, 5, 8, 6]\n", + "\n", + "def standard_deviation(data):\n", + " n = len(data)\n", + "\n", + " if (n <= 1):\n", + " return 0.0\n", + "\n", + " mean, sd = average(data), 0.0\n", + "\n", + " for d in data:\n", + " sd += (float(d) - mean) ** 2\n", + " sd = math.sqrt(sd / float(n - 1))\n", + "\n", + " return sd\n", + "\n", + "def average(data):\n", + " n, mean = len(data), 0.0\n", + "\n", + " if (n <= 1):\n", + " return data[0]\n", + "\n", + " for d in data:\n", + " mean = mean + float(d)\n", + "\n", + " mean = mean / float(n)\n", + " return mean\n", + "\n", + "\n", + "data = [4, 2, 5, 8, 6]\n", + "print(f\"Data: {data}\")\n", + "print(f\"the standard deviation for these data is: {standard_deviation(data)}\")" ] } ],