2577:
2563:
2601:
2589:
56:
Interestingness â interesting effects are those that "have the potential, through empirical analysis, to change what people believe about an important issue". More interesting effects are more compelling than less interesting ones. In addition, more surprising effects are more compelling than ones
69:
Song Qian noted that the MAGIC criteria could be of use to ecologists. Claudia Stanny discussed them in a course on psychology. Anne
Boomsma noted that they are useful when presenting results of complex statistical methods such as
60:
Credibility â Credible claims are more compelling than incredible ones. The researcher must show that the claims made are credible. Results that contradict previously established ones are less credible.
209:
53:
Generality â How generally does it apply? More general effects are more compelling than less general ones. Claims that would interest a more general audience are more compelling.
31:. In this book he posits that the goal of statistical analysis should be to make compelling claims about the world and he presents the MAGIC criteria as a way to do that.
1698:
2203:
2353:
1977:
618:
1751:
2190:
220:
613:
313:
1217:
365:
2000:
1892:
2605:
2178:
2052:
2236:
1897:
1642:
1013:
603:
1227:
2287:
1499:
1306:
1195:
1153:
392:
2530:
1489:
71:
1539:
2081:
2030:
2015:
2005:
1874:
1746:
1713:
1494:
1324:
2150:
1451:
2627:
2425:
2226:
1205:
874:
338:
163:
Adapted from
Abelson, Robert P. (1995). Statistics as principled argument. Hillsdale, NJ: Lawrence Erlbaum, pp. 12â14.
2310:
2277:
2282:
2025:
1784:
1690:
1670:
1578:
1289:
1107:
590:
462:
1456:
1222:
1080:
2042:
1810:
1531:
1385:
1314:
1234:
1092:
1073:
781:
502:
2155:
2525:
2292:
1840:
1805:
1769:
1554:
996:
905:
864:
776:
467:
306:
1562:
1546:
2434:
2047:
1987:
1924:
1284:
1146:
1136:
986:
900:
2195:
2132:
143:
2472:
2402:
1887:
1774:
771:
668:
575:
454:
353:
83:
2593:
1471:
2497:
2439:
2382:
2208:
2101:
2010:
1736:
1620:
1479:
1361:
1353:
1168:
1064:
1042:
1001:
966:
933:
879:
854:
809:
748:
708:
510:
333:
2576:
1466:
2420:
1995:
1944:
1920:
1882:
1800:
1779:
1731:
1610:
1588:
1557:
1343:
1294:
1212:
1185:
1141:
1097:
859:
635:
515:
2567:
2492:
2415:
2096:
1860:
1853:
1815:
1723:
1703:
1675:
1408:
1274:
1269:
1259:
1251:
1069:
1030:
920:
910:
819:
598:
554:
472:
397:
299:
2142:
2581:
2392:
2246:
2091:
1967:
1864:
1848:
1825:
1602:
1336:
1319:
1279:
1190:
1085:
1047:
1018:
978:
938:
884:
801:
487:
482:
278:
2487:
2457:
2449:
2269:
2260:
2185:
2116:
1972:
1957:
1932:
1820:
1761:
1627:
1615:
1241:
1158:
1102:
1025:
869:
791:
570:
444:
238:
50:
Articulation â How specific is it? Precise statements are more compelling than imprecise ones.
2512:
2467:
2231:
2218:
2111:
2086:
2020:
1952:
1830:
1438:
1331:
1264:
1177:
1124:
943:
814:
608:
407:
374:
270:
188:
2429:
2173:
2035:
1962:
1637:
1511:
1484:
1461:
1430:
1057:
1052:
1006:
736:
387:
247:
2378:
2373:
836:
766:
412:
24:
2621:
2535:
2502:
2365:
2326:
2137:
2106:
1570:
1524:
1129:
831:
658:
422:
417:
47:
Magnitude â How big is the effect? Large effects are more compelling than small ones.
688:
282:
2477:
2410:
2387:
2302:
1632:
928:
826:
761:
703:
625:
580:
2520:
2482:
2165:
2066:
1928:
1741:
1708:
1200:
1117:
1112:
756:
713:
693:
673:
663:
432:
274:
110:
1366:
846:
546:
477:
427:
402:
322:
193:
176:
1519:
1371:
991:
786:
698:
683:
678:
643:
40:
1035:
653:
530:
525:
520:
492:
2540:
2241:
2462:
1443:
1417:
1397:
648:
439:
261:
Boomsma, Anne (2000). "Reporting
Analysis of Covariance Studies".
382:
2351:
1918:
1665:
964:
734:
351:
295:
291:
177:"Statistics in ecology is for making a "principled argument""
144:"Criteria for a persuasive statistical argument: MAGIC"
2204:
Autoregressive conditional heteroskedasticity (ARCH)
2511:
2448:
2401:
2364:
2319:
2301:
2268:
2259:
2217:
2164:
2125:
2074:
2065:
1986:
1943:
1873:
1839:
1793:
1760:
1722:
1689:
1601:
1510:
1429:
1384:
1352:
1305:
1250:
1176:
1167:
977:
919:
893:
845:
800:
747:
634:
589:
563:
545:
501:
453:
373:
364:
210:"404 â Page Not Found | University of West Florida"
16:Set of guidelines for using statistical analysis
1752:Multivariate adaptive regression splines (MARS)
86: â Criteria for measuring cause and effect
65:Reviews and applications of the MAGIC criteria
307:
8:
2361:
2348:
2265:
2071:
1940:
1915:
1686:
1662:
1390:
1173:
974:
961:
744:
731:
370:
361:
348:
314:
300:
292:
57:that merely confirm what is already known.
192:
138:
136:
134:
132:
105:
103:
101:
99:
95:
2278:KaplanâMeier estimator (product limit)
236:
23:are a set of guidelines put forth by
7:
2588:
2288:Accelerated failure time (AFT) model
151:COURSE HOME PAGE INDEX AND MAILLISTS
2600:
1883:Analysis of variance (ANOVA, anova)
1978:CochranâMantelâHaenszel statistics
604:Pearson product-moment correlation
14:
29:Statistics as Principled Argument
2599:
2587:
2575:
2562:
2561:
2237:Least-squares spectral analysis
1218:Mean-unbiased minimum-variance
1:
2531:Geographic information system
1747:Simultaneous equations models
72:structural equation modelling
1714:Coefficient of determination
1325:Uniformly most powerful test
263:Structural Equation Modeling
35:What are the MAGIC criteria?
2283:Proportional hazards models
2227:Spectral density estimation
2209:Vector autoregression (VAR)
1643:Maximum posterior estimator
875:Randomized controlled trial
2644:
2043:Multivariate distributions
463:Average absolute deviation
275:10.1207/S15328007SEM0703_6
2557:
2360:
2347:
2031:Structural equation model
1939:
1914:
1685:
1661:
1393:
1367:Score/Lagrange multiplier
973:
960:
782:Sample size determination
743:
730:
360:
347:
329:
246:Cite uses generic title (
194:10.1007/s10980-014-0042-y
153:. Simon Fraser University
2526:Environmental statistics
2048:Elliptical distributions
1841:Generalized linear model
1770:Simple linear regression
1540:HodgesâLehmann estimator
997:Probability distribution
906:Stochastic approximation
468:Coefficient of variation
2186:Cross-correlation (XCF)
1794:Non-standard predictors
1228:LehmannâScheffĂ© theorem
901:Adaptive clinical trial
2582:Mathematics portal
2403:Engineering statistics
2311:NelsonâAalen estimator
1888:Analysis of covariance
1775:Ordinary least squares
1699:Pearson product-moment
1103:Statistical functional
1014:Empirical distribution
847:Controlled experiments
576:Frequency distribution
354:Descriptive statistics
84:Bradford Hill criteria
2498:Population statistics
2440:System identification
2174:Autocorrelation (ACF)
2102:Exponential smoothing
2016:Discriminant analysis
2011:Canonical correlation
1875:Partition of variance
1737:Regression validation
1581:(JonckheereâTerpstra)
1480:Likelihood-ratio test
1169:Frequentist inference
1081:Locationâscale family
1002:Sampling distribution
967:Statistical inference
934:Cross-sectional study
921:Observational studies
880:Randomized experiment
709:Stem-and-leaf display
511:Central limit theorem
2421:Probabilistic design
2006:Principal components
1849:Exponential families
1801:Nonlinear regression
1780:General linear model
1742:Mixed effects models
1732:Errors and residuals
1709:Confounding variable
1611:Bayesian probability
1589:Van der Waerden test
1579:Ordered alternative
1344:Multiple comparisons
1223:RaoâBlackwellization
1186:Estimating equations
1142:Statistical distance
860:Factorial experiment
393:Arithmetic-Geometric
111:"The MAGIC Criteria"
2493:Official statistics
2416:Methods engineering
2097:Seasonal adjustment
1865:Poisson regressions
1785:Bayesian regression
1724:Regression analysis
1704:Partial correlation
1676:Regression analysis
1275:Prediction interval
1270:Likelihood interval
1260:Confidence interval
1252:Interval estimation
1213:Unbiased estimators
1031:Model specification
911:Up-and-down designs
599:Partial correlation
555:Index of dispersion
473:Interquartile range
175:Qian, Song (2014).
2628:Statistical theory
2513:Spatial statistics
2393:Medical statistics
2293:First hitting time
2247:Whittle likelihood
1898:Degrees of freedom
1893:Multivariate ANOVA
1826:Heteroscedasticity
1638:Bayesian estimator
1603:Bayesian inference
1452:KolmogorovâSmirnov
1337:Randomization test
1307:Testing hypotheses
1280:Tolerance interval
1191:Maximum likelihood
1086:Exponential family
1019:Density estimation
979:Statistical theory
939:Natural experiment
885:Scientific control
802:Survey methodology
488:Standard deviation
117:. 16 February 2015
2615:
2614:
2553:
2552:
2549:
2548:
2488:National accounts
2458:Actuarial science
2450:Social statistics
2343:
2342:
2339:
2338:
2335:
2334:
2270:Survival function
2255:
2254:
2117:Granger causality
1958:Contingency table
1933:Survival analysis
1910:
1909:
1906:
1905:
1762:Linear regression
1657:
1656:
1653:
1652:
1628:Credible interval
1597:
1596:
1380:
1379:
1196:Method of moments
1065:Parametric family
1026:Statistical model
956:
955:
952:
951:
870:Random assignment
792:Statistical power
726:
725:
722:
721:
571:Contingency table
541:
540:
408:Generalized/power
208:Caludia, Stanny.
181:Landscape Ecology
2635:
2603:
2602:
2591:
2590:
2580:
2579:
2565:
2564:
2468:Crime statistics
2362:
2349:
2266:
2232:Fourier analysis
2219:Frequency domain
2199:
2146:
2112:Structural break
2072:
2021:Cluster analysis
1968:Log-linear model
1941:
1916:
1857:
1831:Homoscedasticity
1687:
1663:
1582:
1574:
1566:
1565:(KruskalâWallis)
1550:
1535:
1490:Cross validation
1475:
1457:AndersonâDarling
1404:
1391:
1362:Likelihood-ratio
1354:Parametric tests
1332:Permutation test
1315:1- & 2-tails
1206:Minimum distance
1178:Point estimation
1174:
1125:Optimal decision
1076:
975:
962:
944:Quasi-experiment
894:Adaptive designs
745:
732:
609:Rank correlation
371:
362:
349:
316:
309:
302:
293:
287:
286:
258:
252:
251:
244:
242:
234:
232:
231:
225:
219:. Archived from
214:
205:
199:
198:
196:
172:
166:
165:
160:
158:
148:
140:
127:
126:
124:
122:
107:
2643:
2642:
2638:
2637:
2636:
2634:
2633:
2632:
2618:
2617:
2616:
2611:
2574:
2545:
2507:
2444:
2430:quality control
2397:
2379:Clinical trials
2356:
2331:
2315:
2303:Hazard function
2297:
2251:
2213:
2197:
2160:
2156:BreuschâGodfrey
2144:
2121:
2061:
2036:Factor analysis
1982:
1963:Graphical model
1935:
1902:
1869:
1855:
1835:
1789:
1756:
1718:
1681:
1680:
1649:
1593:
1580:
1572:
1564:
1548:
1533:
1512:Rank statistics
1506:
1485:Model selection
1473:
1431:Goodness of fit
1425:
1402:
1376:
1348:
1301:
1246:
1235:Median unbiased
1163:
1074:
1007:Order statistic
969:
948:
915:
889:
841:
796:
739:
737:Data collection
718:
630:
585:
559:
537:
497:
449:
366:Continuous data
356:
343:
325:
320:
290:
260:
259:
255:
245:
235:
229:
227:
223:
212:
207:
206:
202:
174:
173:
169:
156:
154:
146:
142:
141:
130:
120:
118:
109:
108:
97:
93:
80:
67:
37:
17:
12:
11:
5:
2641:
2639:
2631:
2630:
2620:
2619:
2613:
2612:
2610:
2609:
2597:
2585:
2571:
2558:
2555:
2554:
2551:
2550:
2547:
2546:
2544:
2543:
2538:
2533:
2528:
2523:
2517:
2515:
2509:
2508:
2506:
2505:
2500:
2495:
2490:
2485:
2480:
2475:
2470:
2465:
2460:
2454:
2452:
2446:
2445:
2443:
2442:
2437:
2432:
2423:
2418:
2413:
2407:
2405:
2399:
2398:
2396:
2395:
2390:
2385:
2376:
2374:Bioinformatics
2370:
2368:
2358:
2357:
2352:
2345:
2344:
2341:
2340:
2337:
2336:
2333:
2332:
2330:
2329:
2323:
2321:
2317:
2316:
2314:
2313:
2307:
2305:
2299:
2298:
2296:
2295:
2290:
2285:
2280:
2274:
2272:
2263:
2257:
2256:
2253:
2252:
2250:
2249:
2244:
2239:
2234:
2229:
2223:
2221:
2215:
2214:
2212:
2211:
2206:
2201:
2193:
2188:
2183:
2182:
2181:
2179:partial (PACF)
2170:
2168:
2162:
2161:
2159:
2158:
2153:
2148:
2140:
2135:
2129:
2127:
2126:Specific tests
2123:
2122:
2120:
2119:
2114:
2109:
2104:
2099:
2094:
2089:
2084:
2078:
2076:
2069:
2063:
2062:
2060:
2059:
2058:
2057:
2056:
2055:
2040:
2039:
2038:
2028:
2026:Classification
2023:
2018:
2013:
2008:
2003:
1998:
1992:
1990:
1984:
1983:
1981:
1980:
1975:
1973:McNemar's test
1970:
1965:
1960:
1955:
1949:
1947:
1937:
1936:
1919:
1912:
1911:
1908:
1907:
1904:
1903:
1901:
1900:
1895:
1890:
1885:
1879:
1877:
1871:
1870:
1868:
1867:
1851:
1845:
1843:
1837:
1836:
1834:
1833:
1828:
1823:
1818:
1813:
1811:Semiparametric
1808:
1803:
1797:
1795:
1791:
1790:
1788:
1787:
1782:
1777:
1772:
1766:
1764:
1758:
1757:
1755:
1754:
1749:
1744:
1739:
1734:
1728:
1726:
1720:
1719:
1717:
1716:
1711:
1706:
1701:
1695:
1693:
1683:
1682:
1679:
1678:
1673:
1667:
1666:
1659:
1658:
1655:
1654:
1651:
1650:
1648:
1647:
1646:
1645:
1635:
1630:
1625:
1624:
1623:
1618:
1607:
1605:
1599:
1598:
1595:
1594:
1592:
1591:
1586:
1585:
1584:
1576:
1568:
1552:
1549:(MannâWhitney)
1544:
1543:
1542:
1529:
1528:
1527:
1516:
1514:
1508:
1507:
1505:
1504:
1503:
1502:
1497:
1492:
1482:
1477:
1474:(ShapiroâWilk)
1469:
1464:
1459:
1454:
1449:
1441:
1435:
1433:
1427:
1426:
1424:
1423:
1415:
1406:
1394:
1388:
1386:Specific tests
1382:
1381:
1378:
1377:
1375:
1374:
1369:
1364:
1358:
1356:
1350:
1349:
1347:
1346:
1341:
1340:
1339:
1329:
1328:
1327:
1317:
1311:
1309:
1303:
1302:
1300:
1299:
1298:
1297:
1292:
1282:
1277:
1272:
1267:
1262:
1256:
1254:
1248:
1247:
1245:
1244:
1239:
1238:
1237:
1232:
1231:
1230:
1225:
1210:
1209:
1208:
1203:
1198:
1193:
1182:
1180:
1171:
1165:
1164:
1162:
1161:
1156:
1151:
1150:
1149:
1139:
1134:
1133:
1132:
1122:
1121:
1120:
1115:
1110:
1100:
1095:
1090:
1089:
1088:
1083:
1078:
1062:
1061:
1060:
1055:
1050:
1040:
1039:
1038:
1033:
1023:
1022:
1021:
1011:
1010:
1009:
999:
994:
989:
983:
981:
971:
970:
965:
958:
957:
954:
953:
950:
949:
947:
946:
941:
936:
931:
925:
923:
917:
916:
914:
913:
908:
903:
897:
895:
891:
890:
888:
887:
882:
877:
872:
867:
862:
857:
851:
849:
843:
842:
840:
839:
837:Standard error
834:
829:
824:
823:
822:
817:
806:
804:
798:
797:
795:
794:
789:
784:
779:
774:
769:
767:Optimal design
764:
759:
753:
751:
741:
740:
735:
728:
727:
724:
723:
720:
719:
717:
716:
711:
706:
701:
696:
691:
686:
681:
676:
671:
666:
661:
656:
651:
646:
640:
638:
632:
631:
629:
628:
623:
622:
621:
616:
606:
601:
595:
593:
587:
586:
584:
583:
578:
573:
567:
565:
564:Summary tables
561:
560:
558:
557:
551:
549:
543:
542:
539:
538:
536:
535:
534:
533:
528:
523:
513:
507:
505:
499:
498:
496:
495:
490:
485:
480:
475:
470:
465:
459:
457:
451:
450:
448:
447:
442:
437:
436:
435:
430:
425:
420:
415:
410:
405:
400:
398:Contraharmonic
395:
390:
379:
377:
368:
358:
357:
352:
345:
344:
342:
341:
336:
330:
327:
326:
321:
319:
318:
311:
304:
296:
289:
288:
253:
200:
187:(6): 937â939.
167:
128:
94:
92:
89:
88:
87:
79:
76:
66:
63:
62:
61:
58:
54:
51:
48:
36:
33:
25:Robert Abelson
21:MAGIC criteria
15:
13:
10:
9:
6:
4:
3:
2:
2640:
2629:
2626:
2625:
2623:
2608:
2607:
2598:
2596:
2595:
2586:
2584:
2583:
2578:
2572:
2570:
2569:
2560:
2559:
2556:
2542:
2539:
2537:
2536:Geostatistics
2534:
2532:
2529:
2527:
2524:
2522:
2519:
2518:
2516:
2514:
2510:
2504:
2503:Psychometrics
2501:
2499:
2496:
2494:
2491:
2489:
2486:
2484:
2481:
2479:
2476:
2474:
2471:
2469:
2466:
2464:
2461:
2459:
2456:
2455:
2453:
2451:
2447:
2441:
2438:
2436:
2433:
2431:
2427:
2424:
2422:
2419:
2417:
2414:
2412:
2409:
2408:
2406:
2404:
2400:
2394:
2391:
2389:
2386:
2384:
2380:
2377:
2375:
2372:
2371:
2369:
2367:
2366:Biostatistics
2363:
2359:
2355:
2350:
2346:
2328:
2327:Log-rank test
2325:
2324:
2322:
2318:
2312:
2309:
2308:
2306:
2304:
2300:
2294:
2291:
2289:
2286:
2284:
2281:
2279:
2276:
2275:
2273:
2271:
2267:
2264:
2262:
2258:
2248:
2245:
2243:
2240:
2238:
2235:
2233:
2230:
2228:
2225:
2224:
2222:
2220:
2216:
2210:
2207:
2205:
2202:
2200:
2198:(BoxâJenkins)
2194:
2192:
2189:
2187:
2184:
2180:
2177:
2176:
2175:
2172:
2171:
2169:
2167:
2163:
2157:
2154:
2152:
2151:DurbinâWatson
2149:
2147:
2141:
2139:
2136:
2134:
2133:DickeyâFuller
2131:
2130:
2128:
2124:
2118:
2115:
2113:
2110:
2108:
2107:Cointegration
2105:
2103:
2100:
2098:
2095:
2093:
2090:
2088:
2085:
2083:
2082:Decomposition
2080:
2079:
2077:
2073:
2070:
2068:
2064:
2054:
2051:
2050:
2049:
2046:
2045:
2044:
2041:
2037:
2034:
2033:
2032:
2029:
2027:
2024:
2022:
2019:
2017:
2014:
2012:
2009:
2007:
2004:
2002:
1999:
1997:
1994:
1993:
1991:
1989:
1985:
1979:
1976:
1974:
1971:
1969:
1966:
1964:
1961:
1959:
1956:
1954:
1953:Cohen's kappa
1951:
1950:
1948:
1946:
1942:
1938:
1934:
1930:
1926:
1922:
1917:
1913:
1899:
1896:
1894:
1891:
1889:
1886:
1884:
1881:
1880:
1878:
1876:
1872:
1866:
1862:
1858:
1852:
1850:
1847:
1846:
1844:
1842:
1838:
1832:
1829:
1827:
1824:
1822:
1819:
1817:
1814:
1812:
1809:
1807:
1806:Nonparametric
1804:
1802:
1799:
1798:
1796:
1792:
1786:
1783:
1781:
1778:
1776:
1773:
1771:
1768:
1767:
1765:
1763:
1759:
1753:
1750:
1748:
1745:
1743:
1740:
1738:
1735:
1733:
1730:
1729:
1727:
1725:
1721:
1715:
1712:
1710:
1707:
1705:
1702:
1700:
1697:
1696:
1694:
1692:
1688:
1684:
1677:
1674:
1672:
1669:
1668:
1664:
1660:
1644:
1641:
1640:
1639:
1636:
1634:
1631:
1629:
1626:
1622:
1619:
1617:
1614:
1613:
1612:
1609:
1608:
1606:
1604:
1600:
1590:
1587:
1583:
1577:
1575:
1569:
1567:
1561:
1560:
1559:
1556:
1555:Nonparametric
1553:
1551:
1545:
1541:
1538:
1537:
1536:
1530:
1526:
1525:Sample median
1523:
1522:
1521:
1518:
1517:
1515:
1513:
1509:
1501:
1498:
1496:
1493:
1491:
1488:
1487:
1486:
1483:
1481:
1478:
1476:
1470:
1468:
1465:
1463:
1460:
1458:
1455:
1453:
1450:
1448:
1446:
1442:
1440:
1437:
1436:
1434:
1432:
1428:
1422:
1420:
1416:
1414:
1412:
1407:
1405:
1400:
1396:
1395:
1392:
1389:
1387:
1383:
1373:
1370:
1368:
1365:
1363:
1360:
1359:
1357:
1355:
1351:
1345:
1342:
1338:
1335:
1334:
1333:
1330:
1326:
1323:
1322:
1321:
1318:
1316:
1313:
1312:
1310:
1308:
1304:
1296:
1293:
1291:
1288:
1287:
1286:
1283:
1281:
1278:
1276:
1273:
1271:
1268:
1266:
1263:
1261:
1258:
1257:
1255:
1253:
1249:
1243:
1240:
1236:
1233:
1229:
1226:
1224:
1221:
1220:
1219:
1216:
1215:
1214:
1211:
1207:
1204:
1202:
1199:
1197:
1194:
1192:
1189:
1188:
1187:
1184:
1183:
1181:
1179:
1175:
1172:
1170:
1166:
1160:
1157:
1155:
1152:
1148:
1145:
1144:
1143:
1140:
1138:
1135:
1131:
1130:loss function
1128:
1127:
1126:
1123:
1119:
1116:
1114:
1111:
1109:
1106:
1105:
1104:
1101:
1099:
1096:
1094:
1091:
1087:
1084:
1082:
1079:
1077:
1071:
1068:
1067:
1066:
1063:
1059:
1056:
1054:
1051:
1049:
1046:
1045:
1044:
1041:
1037:
1034:
1032:
1029:
1028:
1027:
1024:
1020:
1017:
1016:
1015:
1012:
1008:
1005:
1004:
1003:
1000:
998:
995:
993:
990:
988:
985:
984:
982:
980:
976:
972:
968:
963:
959:
945:
942:
940:
937:
935:
932:
930:
927:
926:
924:
922:
918:
912:
909:
907:
904:
902:
899:
898:
896:
892:
886:
883:
881:
878:
876:
873:
871:
868:
866:
863:
861:
858:
856:
853:
852:
850:
848:
844:
838:
835:
833:
832:Questionnaire
830:
828:
825:
821:
818:
816:
813:
812:
811:
808:
807:
805:
803:
799:
793:
790:
788:
785:
783:
780:
778:
775:
773:
770:
768:
765:
763:
760:
758:
755:
754:
752:
750:
746:
742:
738:
733:
729:
715:
712:
710:
707:
705:
702:
700:
697:
695:
692:
690:
687:
685:
682:
680:
677:
675:
672:
670:
667:
665:
662:
660:
659:Control chart
657:
655:
652:
650:
647:
645:
642:
641:
639:
637:
633:
627:
624:
620:
617:
615:
612:
611:
610:
607:
605:
602:
600:
597:
596:
594:
592:
588:
582:
579:
577:
574:
572:
569:
568:
566:
562:
556:
553:
552:
550:
548:
544:
532:
529:
527:
524:
522:
519:
518:
517:
514:
512:
509:
508:
506:
504:
500:
494:
491:
489:
486:
484:
481:
479:
476:
474:
471:
469:
466:
464:
461:
460:
458:
456:
452:
446:
443:
441:
438:
434:
431:
429:
426:
424:
421:
419:
416:
414:
411:
409:
406:
404:
401:
399:
396:
394:
391:
389:
386:
385:
384:
381:
380:
378:
376:
372:
369:
367:
363:
359:
355:
350:
346:
340:
337:
335:
332:
331:
328:
324:
317:
312:
310:
305:
303:
298:
297:
294:
284:
280:
276:
272:
268:
264:
257:
254:
249:
240:
226:on 2019-04-16
222:
218:
211:
204:
201:
195:
190:
186:
182:
178:
171:
168:
164:
152:
145:
139:
137:
135:
133:
129:
116:
112:
106:
104:
102:
100:
96:
90:
85:
82:
81:
77:
75:
73:
64:
59:
55:
52:
49:
46:
45:
44:
42:
34:
32:
30:
26:
22:
2604:
2592:
2573:
2566:
2478:Econometrics
2428: /
2411:Chemometrics
2388:Epidemiology
2381: /
2354:Applications
2196:ARIMA model
2143:Q-statistic
2092:Stationarity
1988:Multivariate
1931: /
1927: /
1925:Multivariate
1923: /
1863: /
1859: /
1633:Bayes factor
1532:Signed rank
1444:
1418:
1410:
1398:
1093:Completeness
929:Cohort study
827:Opinion poll
762:Missing data
749:Study design
704:Scatter plot
626:Scatter plot
619:Spearman's Ï
581:Grouped data
266:
262:
256:
228:. Retrieved
221:the original
216:
203:
184:
180:
170:
162:
155:. Retrieved
150:
119:. Retrieved
114:
68:
38:
28:
27:in his book
20:
18:
2606:WikiProject
2521:Cartography
2483:Jurimetrics
2435:Reliability
2166:Time domain
2145:(LjungâBox)
2067:Time-series
1945:Categorical
1929:Time-series
1921:Categorical
1856:(Bernoulli)
1691:Correlation
1671:Correlation
1467:JarqueâBera
1439:Chi-squared
1201:M-estimator
1154:Asymptotics
1098:Sufficiency
865:Interaction
777:Replication
757:Effect size
714:Violin plot
694:Radar chart
674:Forest plot
664:Correlogram
614:Kendall's Ï
269:: 461â483.
157:13 February
121:13 February
39:MAGIC is a
2473:Demography
2191:ARMA model
1996:Regression
1573:(Friedman)
1534:(Wilcoxon)
1472:Normality
1462:Lilliefors
1409:Student's
1285:Resampling
1159:Robustness
1147:divergence
1137:Efficiency
1075:(monotone)
1070:Likelihood
987:Population
820:Stratified
772:Population
591:Dependence
547:Count data
478:Percentile
455:Dispersion
388:Arithmetic
323:Statistics
230:2019-12-23
115:jsvine.com
91:References
1854:Logistic
1621:posterior
1547:Rank sum
1295:Jackknife
1290:Bootstrap
1108:Bootstrap
1043:Parameter
992:Statistic
787:Statistic
699:Run chart
684:Pie chart
679:Histogram
669:Fan chart
644:Bar chart
526:L-moments
413:Geometric
41:backronym
2622:Category
2568:Category
2261:Survival
2138:Johansen
1861:Binomial
1816:Isotonic
1403:(normal)
1048:location
855:Blocking
810:Sampling
689:QâQ plot
654:Box plot
636:Graphics
531:Skewness
521:Kurtosis
493:Variance
423:Heronian
418:Harmonic
283:67844468
239:cite web
78:See also
2594:Commons
2541:Kriging
2426:Process
2383:studies
2242:Wavelet
2075:General
1242:Plug-in
1036:L space
815:Cluster
516:Moments
334:Outline
217:uwf.edu
2463:Census
2053:Normal
2001:Manova
1821:Robust
1571:2-way
1563:1-way
1401:-test
1072:
649:Biplot
440:Median
433:Lehmer
375:Center
281:
2087:Trend
1616:prior
1558:anova
1447:-test
1421:-test
1413:-test
1320:Power
1265:Pivot
1058:shape
1053:scale
503:Shape
483:Range
428:Heinz
403:Cubic
339:Index
279:S2CID
224:(PDF)
213:(PDF)
147:(PDF)
43:for:
2320:Test
1520:Sign
1372:Wald
445:Mode
383:Mean
248:help
159:2020
123:2020
19:The
1500:BIC
1495:AIC
271:doi
189:doi
2624::
277:.
265:.
243::
241:}}
237:{{
215:.
185:29
183:.
179:.
161:.
149:.
131:^
113:.
98:^
74:.
1445:G
1419:F
1411:t
1399:Z
1118:V
1113:U
315:e
308:t
301:v
285:.
273::
267:7
250:)
233:.
197:.
191::
125:.
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.