{ "info": { "author": "Los Angeles Times Data Desk", "author_email": "datadesk@latimes.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3 :: Only", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "census-error-analyzer\n=====================\n\nAnalyze the margin of error in U.S. census data\n\nFeatures\n--------\n\n* Statistical difference tests\n* Statistical range\n* Alternative confidence level conversion\n\nInstallation\n------------\n\n.. code-block:: bash\n\n $ pipenv install census-error-analyzer\n\n\nUsage\n-----\n\nImport the library. ::\n\n >>> import census_error_analyzer\n\n\nTest statistical difference\n^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nAre two values, considering their respective margins of error, statistically different? The Census Bureau advises that this test be conducted for all comparisons. This test answers the question and returns `True` or `False`.\n\nAccepts two lists, each expected to be a pair with a value and its margin of error. ::\n\n >>> us_medianage, us_medianage_moe = 37.9, 0.1\n >>> nyc_medianage, nyc_medianage_moe = 38.4, 0.1\n >>> census_error_analyzer.is_statistically_different(\n >>> (us_medianage, us_medianage_moe),\n >>> (nyc_medianage, nyc_medianage_moe)\n >>> )\n True\n\n\nThe precise difference can also be accessed. According to the Census Bureau, values greater than 1.0 can be considered to be statistically significant. ::\n\n >>> census_error_analyzer.statistical_difference(\n >>> (us_medianage, us_medianage_moe),\n >>> (nyc_medianage, nyc_medianage_moe)\n >>> )\n 3.535533905932737\n\nGet statistical range\n^^^^^^^^^^^^^^^^^^^^^\n\nThe minimum and maximum values in an estimate's statistical range given its margin of error. Expects two arguments: The estimate first. The margin of error second. ::\n\n >>> census_error_analyzer.statistical_range(us_medianage, us_medianage_moe)\n 37.8, 38.0\n\nConvert to alternative confidence levels\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nThe margins of error published by the Census are at the 90% confidence level. They can be converted to the 95% and 99% levels using tools in this library. ::\n\n >>> census_error_analyzer.convert_to_95_percent_confidence(3778)\n 4501.446808510638\n >>> census_error_analyzer.convert_to_99_percent_confidence(3778)\n 5925.373860182372\n\nReferences\n----------\n\nThis module was designed to conform with the Census Bureau's April 18, 2018, presentation `\"Using American Community Survey Estimates and Margin of Error.\" `_\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://www.github.com/datadesk/census-error-analyzer", "keywords": "", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "census-error-analyzer", "package_url": "https://pypi.org/project/census-error-analyzer/", "platform": "", "project_url": "https://pypi.org/project/census-error-analyzer/", "project_urls": { "Homepage": 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