ãããããæ°ãç¬ç¿è ã®ããã®ããããçµæ¸å¦å ¥éããã¹ããç´¹ä»ãã¦ããã®ãè¦ã¦ãask.fmãå§ããã¨ãããçµæ¸å¦ç 究ç§ã«è¡ããªãã§çµæ¸å¦ãå¦ã¶æ¹æ³ã質åãããã®ãæãåºããã ç¨éãåãããªãã®ã ããSNSã§èãããã®ã§SNSã§ä½¿ãããã®ç¥èãªã®ã§ãããã主ã«æç³»å¦åãå¦ãã§ãã人ããã¤ã³ã¿ã¼ãããã®äº¤æµãµã¤ãã§çµæ¸å¦ãç¥ã£ããã¶ãããããã®ç¬å¦æ¹æ³ãèãã¦ã¿ããã 1. åºç¤çãªæ°å¦ãå¦ã¶ çµæ¸å¦ã¯è¨èã¨ãã¦æ°å¦ãå©ç¨ãã¦ãããããããç¨åº¦ã®æ°å¦ã®ç¥èãå¿ è¦ã ãè¨å·ã®æå³ãããåãããªãã¨ãèªã¿é£ã°ããã§ããªãããããçµæ¸å¦ã®æç§æ¸ã®æ°å¦ã®èª¬æã¯æ¥µç«¯ã«çç¥ããã¦ããã®ã§ãããããã®æ°å¦æ¸ãèªãã æ¹ãç解ãæ·±ã¾ããç·å½¢ä»£æ°ãéåãä½ç¸ã解æã®ã¤ãããå¦ã¼ãã ä¸è¬æé¤ã§æ°å¦ã履修ãã¦ããªãã£ã人ã¯ããå¾®åã»ç©å30è¬ãã¨ãç·å½¢ä»£æ°30è¬ããèªãã§ããæ¹ãè¯ãã¨æããã ãã ãèªãã§ãã¦ãä¸ã¶
ã追è¨ã http://togetter.com/li/719536 ãã¾ãããããã¡ã«ããã¯ãã¡ã¯ãå¹´éããããã¡ãããã赤ã¡ããã¾ã§ãå½æ°ã²ã¨ããããå¹³åå¹´é2ä¸8,781åè² æ ãã¦ãããã§ããæé¡ã«ãã¦ã2,348åã®ç¨è² æ ã ã¾ãã§ãå ç±è²»ã®ããã«æ»ã¬ã¾ã§æãç¶ãã¦ãã¦ãã¾ãã è¦å¯åºäºç®ã¨é½éåºçãåç®ããªããã°ãè¦å¯ã®äºç®ï¼ã³ã¹ãã¯è¦ããªãã ããã¦ãããã«ã¯åçåãã¦ãå®ããã¦ããã¨ããKPIç®æ¨ãã¾ã£ãããªããæ¯å¹´è¦äºã«ä½¿ããããç´å¾ãããç¨åº¦ã®å¢å ãè¦è¾¼ãã§ããã è¦å¯åºäºç®ã2,673ååï¼æ³å ¥ã®7.3%ã¨æ¶è²»ç¨8%並ã¿wï¼ é½éåºçè¦å¯äºç®ã3å 3,880åå (92.7%) ã»ã¨ãã©ãå°æ¹è²¡æº ãæ¯æããããããªããã¡ã«å人ãç¨éãæ¯æã£ã¦ããããåç¥ã§ããï¼ãã¨è·å質åã®æã«ãéè·å質åãã¦ãã¾ãï¼ç¬ï¼ ããããã£ã¨æå¹æ´»ç¨ãããªãã°ãé£äºã¯äº¤çªã®å¾ãã®ä¼æ©æã§ã
Julia ã¨ãã©ã R, Python ã«ããã³ã³ãã¥ã¼ã¿ããã°ã©ã ï¼ã³ã³ãã¥ã¼ã¿ã»ãµã¤ã¨ã³ã¹ï¼çµ±è¨å¦ å ãã¼ã¿ããªãï¼ï¼ï¼ãããªã®ã§ï¼ã°ã©ãããèªã¿åã£ã¦åæãã¦ã¿ãã > d = read.table("takahashi.dat", header=TRUE) # ãã¼ã¿ã¯æ«å°¾ã«æ²è¼ > plot(x ~ t, type="o", col="blue", pch=16, ylim=c(-1.5, 2), ylab="x", xlab="t") > points(y ~ t, type="o", col="red", pch=16, yaxt="n", ylab="y") > axis(4, at=seq(-1.5, 2, length=11), labels=seq(90, 140, by=5)) > mtext("y", 4, 1.8) > (r_xy = cor(x, y)) #
Julia ã¨ãã©ã R, Python ã«ããã³ã³ãã¥ã¼ã¿ããã°ã©ã ï¼ã³ã³ãã¥ã¼ã¿ã»ãµã¤ã¨ã³ã¹ï¼çµ±è¨å¦ http://abrahamcow.hatenablog.com/entry/2014/09/11/024924 ãæç³»åãã¼ã¿ã®ç¸é¢ä¿æ°ã¯ãã¦ã«ãªããªãâ¦â¦ã®ãï¼ãæãã¦ä¸ããããªãã ãã©... ç§ã®ã³ã¡ã³ããæ°ã«è§¦ããã¨ãå¤ããããªã®ã§ããï¼ç¹ã«æªæã¯ãªãã¤ãããªãã§ããã©ï¼ãã¿ã¾ãããï¼ ç§ã¯ï¼çµæ¸å¦ã¨ãæç³»åã«ã¤ãã¦ã¯ããç¥ããªãã®ã§ããï¼ãããã¯ãè¦ãããã®ç¸é¢ï¼æ¬ä¼¼ç¸é¢ï¼spurious correlationï¼ãã®ä¾ã ãã¨ãããã¨ãªãã°ï¼åç¸é¢ä¿æ°ãèããã°ããã®ã§ã¯ãªãã§ãããããï¼ï¼ç¤¾ä¼å¦ãªã©ã§ã¯å½ããåã®ããã«ä½¿ããã¦ããã¨æãã®ã§ããã > set.seed(1) > x = cumsum(rnorm(100)) > set.seed(2) > y = cumsu
æ¬è¨äºã®è¶£æ¨ è¦ãæãã®å帰ã¨è¦ãæãã®ç¸é¢ï¼æ¬ä¼¼ç¸é¢ï¼ã¯éãã¾ãã æç³»åï¼ã¨ããããã©ã³ãã ã¦ã©ã¼ã¯ããç³»å ã©ã³ãã ã¦ã©ã¼ã¯ - Wikipedia ï¼ã®å ´åãç¸é¢ä¿æ°ã¯æ¯è¼çé«ãå¤ã«ãªãããããã¾ãææãªç¸é¢ãåºãããã®ã§æ³¨æã ãã¨é«æ©æ´ä¸ã®è°è«ãæè·ãã話é¡ãæ··ãã£ã¦ãã¾ãããããã«ã¤ãã¦ã¯ãéèç·©åã¯ãã¿ç©ã¿ä¸çãéèç·©åè³æãæ¶è²»ç¨å¢ç¨å対ã - 廿TT ãåç §ãã¦ãã ããã ãæç³»åãç¸é¢ã ãæç³»åãç¸é¢ãã§ã°ã°ã£ãã¨ãã以ä¸ã®ãããªè¨äºãããããã. æç³»åãã¼ã¿ã®ç¸é¢ä¿æ°ã¯ãã¦ã«ãªããªã: ãã¥ã¼ã¹ã®ç¤¾ä¼ç§å¦çãªè£å´ ç¾æç¹ã§ã¯ Google æ¤ç´¢ã§ä¸ãã 6 çªç® R - æç³»åãã¼ã¿åæã®åå¿è ã«å¿ ãç¥ã£ã¦ãããããéè¦ãã¤ã³ãï¼å帰åæ ã»ç¸é¢é¢ä¿åæãè¡ãåã«å¿ ãããã¹ããã¨ï¼ãã¼ã¿ã®å½¢ã®ãã§ãã¯ã¨å¤å½¢ï¼ - Qiita ç¾æç¹ã§ã¯ Google æ¤ç´¢ã§ä¸ã
å å®åã®é«æ©æ´ä¸æ°ãæç³»åãã¼ã¿ã®ç¸é¢ä¿æ°ãé«ãäºãè«æ ã«ãã¦ãããããã®è«è¨¼æ¹æ³ã¯å ¨ããã£ã¦å³å¯ã§ã¯ãªãã è¨éçµæ¸å¦ã§ã¯æç³»åãã¼ã¿ã®ç¸é¢ä¿æ°ã¯ãã¦ã«ãªããªãäºã¯80年代ããè¯ãç¥ããã¦ãããããã«é¢é£ããæ¥ç¸¾ã§ã¨ã³ã°ã«ã¨ã°ã¬ã³ã¸ã£ã¼ã¯ã2003å¹´ã«ãã¼ãã«çµæ¸å¦è³ãåè³ãã¦ããã é«æ©æ°ã®ããªãã¯ã説æããããä¸ã®ä¸ã«ã¯æéã¨ã¨ãã«å¤åãã¦ãããã¬ã³ã*1ã¨è¨ãã®ãå¤ãããããã®ãã¬ã³ãããããã¼ã¿ãäºã¤æ¯è¼ããã¨ãã©ã¡ããæéã«å¯¾ãã¦ç¸é¢ãã¦ãããããç¸é¢ãããããã«è¦ãã¦ãã¾ãã ä¾ãã°æ¦å¾ãä¸äººãããã®ç±³ã®æ¶è²»éã¯æ¸å°ããã³ã³ãã¥ã¼ã¿ã¼ã®æ®åå°æ°ã¯é£èºçã«ä¼¸ã³ããããã®äºã¤ã®ç¾è±¡ãçµã³ã¤ãã¦èãã人ã¯ããªããããããç±³ã®æ¶è²»éã¨ã³ã³ãã¥ã¼ã¿ã¼ã®æ®åå°æ°ã¯ãé«ãç¸é¢ãæã¤äºã«ãªãã å®ãã¼ã¿ã®å ´åã¯å±çå±ãã¤ããäºãå¯è½ããç¥ããªãã®ã§ãã·ãã¥ã¬ã¼ã·ã§ã³ãã¦ç¢ºããã¦ã¿ããã
ãªãªã¼ã¹ãé害æ å ±ãªã©ã®ãµã¼ãã¹ã®ãç¥ãã
ææ°ã®äººæ°ã¨ã³ããªã¼ã®é ä¿¡
j次ã®ããã¯ãã¼ã¯
kåã®ããã¯ãã¼ã¯
lãã¨ã§èªã
eã³ã¡ã³ãä¸è¦§ãéã
oãã¼ã¸ãéã
{{#tags}}- {{label}}
{{/tags}}