Skip to content

deiscriptive stats exercises #16

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
isabellegaldau wants to merge 2 commits into
base: main
Choose a base branch
from
Open

deiscriptive stats exercises #16

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
b34f6bf
Initial commit
isabellegaldau Dec 2, 2023
b5fb719
Pending changes exported from your codespace
isabellegaldau Dec 2, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
112 changes: 106 additions & 6 deletions notebook/problems.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -30,12 +30,87 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 11,
"id": "34720ab6",
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Normal Distribution:\n",
"Mean: -0.028619142236640034\n",
"Median: -0.017270072330735627\n",
"Mode: ModeResult(mode=-1.789772257755604, count=1)\n",
"Standard Deviation: 0.8504782461047726\n",
"Variance: 0.7233132470974502\n",
"Range: 4.1504060137771885\n",
"Kurtosis: -0.22984275091294082\n",
"Skewness: 0.1876392566353732\n",
"Chi-Square Distribution (degrees of freedom = 3):\n",
"Mean: 3.0351302359457906\n",
"Median: 2.396361773406997\n",
"Mode: ModeResult(mode=0.0826946028144708, count=1)\n",
"Standard Deviation: 2.3641911718270654\n",
"Varaince: 5.589399896945032\n",
"Range: 12.234950149104789\n",
"Kurtosis: 2.078076991312349\n",
"Skewness: 1.3992822141563568\n"
]
}
],
"source": [
"# TODO"
"# TODO\n",
"import numpy as np\n",
"from scipy.stats import kurtosis, skew, mode\n",
"\n",
"np.random.seed(88)\n",
"\n",
"normal_distribution = np.random.normal(0, 1, 100)\n",
"chi_square_distribution = np.random.chisquare(3, 100)\n",
"\n",
"# normal metrics\n",
"normal_mean = np.mean(normal_distribution)\n",
"normal_median = np.median(normal_distribution)\n",
"normal_mode = mode(normal_distribution)\n",
"normal_std = np.std(normal_distribution)\n",
"normal_variance = np.var(normal_distribution)\n",
"normal_range = np.amax(normal_distribution) - np.amin(normal_distribution)\n",
"normal_kurtosis = kurtosis(normal_distribution)\n",
"normal_skewness = skew(normal_distribution)\n",
"\n",
"\n",
"# chi metrics\n",
"chi_mean = np.mean(chi_square_distribution)\n",
"chi_median = np.median(chi_square_distribution)\n",
"chi_mode = mode(chi_square_distribution)\n",
"chi_std = np.std(chi_square_distribution)\n",
"chi_variance = np.var(chi_square_distribution)\n",
"chi_range = np.amax(chi_square_distribution) - np.amin(chi_square_distribution)\n",
"chi_kurtosis = kurtosis(chi_square_distribution)\n",
"chi_skewness = skew(chi_square_distribution)\n",
"\n",
"\n",
"# results\n",
"print(\"Normal Distribution:\")\n",
"print(\"Mean:\", normal_mean)\n",
"print(\"Median:\", normal_median)\n",
"print(\"Mode:\", normal_mode)\n",
"print(\"Standard Deviation:\", normal_std)\n",
"print(\"Variance:\", normal_variance)\n",
"print(\"Range:\", normal_range)\n",
"print(\"Kurtosis:\", normal_kurtosis)\n",
"print(\"Skewness:\", normal_skewness)\n",
"\n",
"print(\"Chi-Square Distribution (degrees of freedom = 3):\")\n",
"print(\"Mean:\", chi_mean)\n",
"print(\"Median:\", chi_median)\n",
"print(\"Mode:\", chi_mode)\n",
"print(\"Standard Deviation:\", chi_std)\n",
"print(\"Varaince:\", chi_variance)\n",
"print(\"Range:\", chi_range)\n",
"print(\"Kurtosis:\", chi_kurtosis)\n",
"print(\"Skewness:\", chi_skewness)\n"
]
},
{
Expand All @@ -54,12 +129,37 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 4,
"id": "d590308e",
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Standard Deviation: 2.0\n"
]
}
],
"source": [
"# TODO"
"# TODO\n",
"\n",
"data = [4, 2, 5, 8, 6]\n",
"\n",
"def calc_mean(data):\n",
" return sum(data) / len(data)\n",
"\n",
"def calc_std_dev(data):\n",
" mean = calc_mean(data)\n",
" variance = sum((x - mean) ** 2 for x in data) / len(data)\n",
" std_dev = variance ** 0.5\n",
" return std_dev\n",
"\n",
"\n",
"standard_deviation = calc_std_dev(data)\n",
"\n",
"\n",
"print(\"Standard Deviation:\", standard_deviation)"
]
}
],
Expand Down