Evidence-based policy (also known as evidence-based governance) is a concept in public policy that advocates for policy decisions to be grounded on, or influenced by, rigorously established objective evidence. This concept presents a stark contrast to policymaking predicated on ideology, 'common sense', anecdotes, or personal intuitions. The methodology employed in evidence-based policy often incl
Summary statistics such as the mean and variance are easily maintained for large, distributed data streams, but order statistics (i.e., sample quantiles) can only be approximately summarized. There is extensive literature on maintaining quantile sketches where the emphasis has been on bounding the rank error of the sketch while using little memory. Unfortunately, rank error guarantees do not precl
Note If you are unfamiliar with differential privacy (DP), you might want to go through "A friendly, non-technical introduction to differential privacy". This repository contains libraries to generate ε- and (ε, δ)-differentially private statistics over datasets. It contains the following tools. Privacy on Beam is an end-to-end differential privacy framework built on top of Apache Beam. It is inte
Zipf's Law on War and Peace.[1] The lower plot shows the remainder when the Zipf law is divided away. It shows that there remains significant pattern not fitted by Zipf law. A plot of the frequency of each word as a function of its frequency rank for two English language texts: Culpeper's Complete Herbal (1652) and H. G. Wells's The War of the Worlds (1898) in a log-log scale. The dotted line is t
Welcome to the dieharder distribution website. Version 3.29.4beta is the current snapshot. Some of the documentation below may not quite be caught up to it, but it should be close. Dieharder is a random number generator (rng) testing suite. It is intended to test generators, not files of possibly random numbers as the latter is a fallacious view of what it means to be random. Is the number 7 rando
GNU datamash GNU datamash is a command-line program which performs basic numeric, textual and statistical operations on input textual data files. Examples: calculate the sum and mean of values 1 to 10: $ seq 10 | datamash sum 1 mean 1 55 5.5 group text file by one column and calculate mean and sample standard deviation on another, with automatic sorting and header line processing: $ datamash --sor
ã¨ä¸»å¼µããè«æãç¾ä¸ã®çµ±è¨å¦ã«ãããæãããããªãããã¯ï¼è°è«ï¼å±éã§ãããã¨ãã¦Francis Dieboldãç´¹ä»ãã¦ãããè«æã®ã¿ã¤ãã«ã¯ãºããªãçµ±è¨çæææ§ã®åå®ç¾©ï¼Redefine Statistical Significanceï¼ãã§ãNature Human Behaviorã«æ²è¼äºå®ã¨ã®ç±ãèè ã¯ç·å¢72åã«åã³ããã¡ãã®ã¨ã³ããªã§ç´¹ä»ããErnst Fehrãåãé£ãã¦ããã»ããæ¥æ¬äººã§ã¯ä»äºèä»æ°ãShinichi Nakagawaæ°ã®ååãè¦åãããã*1ã ãã®1è¡è¦æ¨ï¼One Sentence Summaryï¼ã¯æ¦ã表é¡ã®éãã§ãåæã¯ãWe propose to change the default P-value threshold for statistical significance for claims of new discoveries from
In Android Security, we're constantly working to better understand how to make Android devices operate more smoothly and securely. One security solution included on all devices with Google Play is Verify apps. Verify apps checks if there are Potentially Harmful Apps (PHAs) on your device. If a PHA is found, Verify apps warns the user and enables them to uninstall the app. But, sometimes devices st
Several years back, I wrote an article advocating in favor of using bandit algorithms. In retrospect, the article I wrote was incorrect, and I should have phrased it differently. I made no mathematical mistakes in the article. Every fact I said is true. But the implications of this article and the way it has been interpreted by others is deeply wrong, and I'm going to take the opportunity now to c
5 Common Mental Errors That Sway You From Making Good Decisions I like to think of myself as a rational person, but Iâm not one. The good news is itâs not just me â or you. We are all irrational, and we all make mental errors. For a long time, researchers and economists believed that humans made logical, well-considered decisions. In recent decades, however, researchers have uncovered a wide range
3. ã¹ã©ã¤ãã®è¶£æ¨ åãæ±ãè©±é¡ â¢ å·®åãã©ã¤ãã·ã¼ (en: Differential Privacy) ã¨ããæ¦å¿µãç´¹ä» 1. ä½ãããããã®ãã®ãï¼ 2. ã©ã®ç¨åº¦æçãï¼ 3. ã©ã®ç¨åº¦æçã§ã¯ãªããï¼ 4. ç 究ä¸ã®ä¸è¬ç課é¡ã¯ä½ãï¼ 3 4. ã¹ã©ã¤ãã®è¶£æ¨ åãæ±ãè©±é¡ â¢ å·®åãã©ã¤ãã·ã¼ (en: Differential Privacy) ã¨ããæ¦å¿µãç´¹ä» 1. ä½ãããããã®ãã®ãï¼ 2. ã©ã®ç¨åº¦æçãï¼ 3. ã©ã®ç¨åº¦æçã§ã¯ãªããï¼ 4. ç 究ä¸ã®ä¸è¬ç課é¡ã¯ä½ãï¼ ã¹ã©ã¤ãä½æåæ© â¢ çè ã¯å·®åãã©ã¤ãã·ã¼ãç 究 ⢠æ¦å¿µãã®ãã®ãæ ¹æ¬çã«ãããã¥ããï¼ãè¶ã®éã®è©±é¡ã«ãã¥ãã ⢠ãããããèªãã°ããããè³æãç¨æããã 4
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