{ "info": { "author": "Steve Howard", "author_email": "steve@thumbtack.com", "bugtrack_url": null, "classifiers": [], "description": "Tools for statistical analysis of A/B test results.\n\nABBA provides several statistical tools for analysis of binomial data, typically resulting from A/B\ntests:\n\n* Wald and Agresti-Coull confidence intervals on binomial proportions\n* Confidence intervals on the difference and ratio of two binomial proportions\n* Hypothesis tests for inequality of two binomial proportions\n* Multiple test correction for control of familywise error rate\n\nSome simple example usage::\n\n >>> import abba.stats\n >>> abba.stats.confidence_interval_on_proportion(\n ... num_successes=50, num_trials=200, confidence_level=0.99)\n ValueWithInterval(value=0.25, lower_bound=0.17962262748069852, upper_bound=0.33643200973247306)\n\n >>> experiment = abba.stats.Experiment(\n ... num_trials=5, baseline_num_successes=50, baseline_num_trials=200)\n >>> results = experiment.get_results(num_successes=70, num_trials=190)\n >>> results.relative_improvement\n ValueWithInterval(value=0.4736842105263157, lower_bound=-0.014130868125315277, upper_bound=0.90421878236700903)\n >>> results.two_tailed_p_value\n 0.047886616311815511\n\n\nABBA requires SciPy for underlying statistical functions.\n\nFor more info, see the docstrings, unit tests, and the ABBA website (including an interactive\nJavascript version) at http://www.thumbtack.com/labs/abba/.", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://www.thumbtack.com/labs/abba/", "keywords": null, "license": "LICENSE.txt", "maintainer": null, "maintainer_email": null, "name": "ABBA", "package_url": "https://pypi.org/project/ABBA/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/ABBA/", "project_urls": { "Download": "UNKNOWN", "Homepage": "http://www.thumbtack.com/labs/abba/" }, "release_url": "https://pypi.org/project/ABBA/0.1.0/", "requires_dist": null, "requires_python": null, "summary": "Tools for statistical analysis of A/B test results", "version": "0.1.0", "yanked": false, "yanked_reason": null }, "last_serial": 6013524, "releases": { "0.1.0": [ { "comment_text": "", "digests": { "md5": "d2c8b66fa06592eab22d5bf930193ef9", "sha256": "b733c8f7b88bfa8e3148396339c163bb3ffdbca661ccea334080d4aa5453ea53" }, "downloads": -1, "filename": "ABBA-0.1.0.tar.gz", "has_sig": false, "md5_digest": "d2c8b66fa06592eab22d5bf930193ef9", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6293, "upload_time": "2012-09-28T01:55:15", "upload_time_iso_8601": "2012-09-28T01:55:15.749233Z", "url": "https://files.pythonhosted.org/packages/a9/31/a4625be8bdd38abaf442c066fc8f2ee217aba448ec9c298e1ec0f08b4e1f/ABBA-0.1.0.tar.gz", "yanked": false, "yanked_reason": null } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "d2c8b66fa06592eab22d5bf930193ef9", "sha256": "b733c8f7b88bfa8e3148396339c163bb3ffdbca661ccea334080d4aa5453ea53" }, "downloads": -1, "filename": "ABBA-0.1.0.tar.gz", "has_sig": false, "md5_digest": "d2c8b66fa06592eab22d5bf930193ef9", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6293, "upload_time": "2012-09-28T01:55:15", "upload_time_iso_8601": "2012-09-28T01:55:15.749233Z", "url": "https://files.pythonhosted.org/packages/a9/31/a4625be8bdd38abaf442c066fc8f2ee217aba448ec9c298e1ec0f08b4e1f/ABBA-0.1.0.tar.gz", "yanked": false, "yanked_reason": null } ], "vulnerabilities": [] }