Variabile casuale Poissoniana
La variabile casuale Poissoniana è una variabile casuale discreta, detta pure degli eventi rari.
Table of contents |
2 Storia 3 Vedi anche: 4 Tavole dei valori della funzione di probabilità |
Metodologia
La v.c. Poissoniana è definita con la funzione di probabilitÃ
dove
La funzione generatrice dei momenti è pertanto:
- g(t) = eλ(e^t-1)
- μ = σ² = λ
Quando λ è molto grande (orientativamente λ > 10), allora la Poissoniana può essere approssimata con una variabile casuale Normale con valore atteso e varianza pari a λ: N( λ ; λ).
La Poissoniana porta il nome di Siméon-Denis Poisson in quanto questo
la utilizzò nel 1837 (tre anni prima di morire) in una ricerca
sulle statistiche giudiziarie, derivandola
come distribuzione limite della distribuzione di Pascal
( P(x)=p(1-p)x )
e della distribuzione binomiale.
In realtà la poissoniana come approssimazione della binomiale
era già stata introdotta nel 1718 da Abraham de Moivre
in Doctrine des chances.
Storia
Vedi anche:
Tavole dei valori della funzione di probabilitÃ
λ = 0.1, 0.2, ... 1.0
+
=+
=+
| k \\ λ| 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 |
+=+
=+
| 0 | .9048 .8187 .7408 .6703 .6065 .5488 .4966 .4493 .4066 .3679 |
| 1 | .0905 .1637 .2222 .2681 .3033 .3293 .3476 .3595 .3659 .3679 |
| 2 | .0045 .0164 .0333 .0536 .0758 .0988 .1217 .1438 .1647 .1839 |
| 3 | .0002 .0011 .0033 .0072 .0126 .0198 .0284 .0383 .0494 .0613 |
| 4 | .0001 .0003 .0007 .0016 .0030 .0050 .0077 .0111 .0153 |
| 5 | .0001 .0002 .0004 .0007 .0012 .0020 .0031 |
| 6 | .0001 .0002 .0003 .0005 |
| 7 | .0001 |
+=+
=+ λ = 1.2, 1.4, ... 3.0
+
=+
=+
| k \\ λ| 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 |
+=+
=+
| 0 | .3012 .2466 .2019 .1653 .1353 .1108 .0907 .0743 .0608 .0498 |
| 1 | .3614 .3452 .3230 .2975 .2707 .2438 .2177 .1931 .1703 .1494 |
| 2 | .2169 .2417 .2584 .2678 .2707 .2681 .2613 .2510 .2384 .2240 |
| 3 | .0867 .1128 .1378 .1607 .1804 .1966 .2090 .2176 .2225 .2240 |
| 4 | .0260 .0395 .0551 .0723 .0902 .1082 .1254 .1414 .1557 .1680 |
| 5 | .0062 .0111 .0176 .0260 .0361 .0476 .0602 .0735 .0872 .1008 |
| 6 | .0012 .0026 .0047 .0078 .0120 .0174 .0241 .0319 .0407 .0504 |
| 7 | .0002 .0005 .0011 .0020 .0034 .0055 .0083 .0118 .0163 .0216 |
| 8 | .0001 .0002 .0005 .0009 .0015 .0025 .0038 .0057 .0081 |
| 9 | .0001 .0002 .0004 .0007 .0011 .0018 .0027 |
| 10 | .0001 .0002 .0003 .0005 .0008 |
| 11 | .0001 .0001 .0002 |
| 12 | .0001 |
+=+
=+ λ = 3.5, 4.0, ... 8.0
+
=+
=+
| k \\ λ| 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 |
+=+
=+
| 0 | .0302 .0183 .0111 .0067 .0041 .0025 .0015 .0009 .0006 .0003 |
| 1 | .1057 .0733 .0500 .0337 .0225 .0149 .0098 .0064 .0041 .0027 |
| 2 | .1850 .1465 .1125 .0842 .0618 .0446 .0318 .0223 .0156 .0107 |
| 3 | .2158 .1954 .1687 .1404 .1133 .0892 .0688 .0521 .0389 .0286 |
| 4 | .1888 .1954 .1898 .1755 .1558 .1339 .1118 .0912 .0729 .0573 |
| 5 | .1322 .1563 .1708 .1755 .1714 .1606 .1454 .1277 .1094 .0916 |
| 6 | .0771 .1042 .1281 .1462 .1571 .1606 .1575 .1490 .1367 .1221 |
| 7 | .0385 .0595 .0824 .1044 .1234 .1377 .1462 .1490 .1465 .1396 |
| 8 | .0169 .0298 .0463 .0653 .0849 .1033 .1188 .1304 .1373 .1396 |
| 9 | .0066 .0132 .0232 .0363 .0519 .0688 .0858 .1014 .1144 .1241 |
| 10 | .0023 .0053 .0104 .0181 .0285 .0413 .0558 .0710 .0858 .0993 |
| 11 | .0007 .0019 .0043 .0082 .0143 .0225 .0330 .0452 .0585 .0722 |
| 12 | .0002 .0006 .0016 .0034 .0065 .0113 .0179 .0263 .0366 .0481 |
| 13 | .0001 .0002 .0006 .0013 .0028 .0052 .0089 .0142 .0211 .0296 |
| 14 | .0001 .0002 .0005 .0011 .0022 .0041 .0071 .0113 .0169 |
| 15 | .0001 .0002 .0004 .0009 .0018 .0033 .0057 .0090 |
| 16 | .0001 .0003 .0007 .0014 .0026 .0045 |
| 17 | .0001 .0003 .0006 .0012 .0021 |
| 18 | .0001 .0002 .0005 .0009 |
| 19 | .0001 .0002 .0004 |
| 20 | .0001 .0002 |
| 21 | .0001 |
+=+
=+