<project name="distribuzione ipergeometrica (2)" app="Snap! 6, https://snap.berkeley.edu" version="1"><notes></notes><thumbnail>data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAKAAAAB4CAYAAAB1ovlvAAAgAElEQVR4Xu1dB1RURxf+6B1UUBSiIIq9t2iMvUZjF9QY7MZu7BW7sYAllmhMbLHE+Nt7F4wFJRYQFZWioFKlt6Xuf+6sbxu7sKuL+GDvOZxl9029872ZuXfuvaMjFAqF0FKJ5YCOjo7Ol9w5HQ6AZ86cQVJSktptrVWrFpo1a8byeXt7Iy0tTVxGYdgm3hgZGaFz584y9V67dg1Vq1YF5ac00p+UUP63wr6rk0edtFy9quSxtLTAkfkuQF7+972sTXm0GOeB7OxsED81SbwA4IsXLxT22eaPzjDSV/4C6U04ifBMM8TExMDGxoYBQ5roe5JHe9SxMVDK07cjL7Nn0ox/8uSJTHp6OXr37i0GIgG9Xbt2LI25uTlSU1PZ//RJ3zmi+sPDw1GlShX2cnB55BsjDaSAgADUr19fYXvv3r2Lli1bypS/b98+DBs2jLVNGojyBQRf3ofO0f+If9ar1gq5IT7i76/dzrP/379/j/bt22sMg7wA4KNHjxh4KleuzAZx69atGDp0KKof6g3TmV7I2OEC01leyHlyEbq2zsg8vRR5b/wgHHEQwQJzmRmJZrOxY8fCxcWF/e54sDfKLPRBbvhD6NXqCMH+cdBv2AuZR+cwJgcPOc0+GzVqJGb6f//9JzOYtra2ePnyJbp06YK3b9+yGff06dOYNm0ajhw5gj59+uD+/fvw9/fHqlWrsH79evz0008YN24cDA0NERsbi4iICFSvXh2VKlXCoUOHWB8pfWZmJlJSUtCpUydW9uvXr1meXbt2YcyYMbCzs8M333yDsLAw/PHHH4iMjMTgwYNZH//8809s2LABTk5ObBa/d+8e7ty5g+joaPz999/spfLw8GCA8j+5HV2iDysFYODAY+wZvXwjR44sXQD08RG9icRoWoZdXV2xZMkS1D85iAFQt3xVZJ5ciBz/szCZeBy6FZyROrcKcoftw7NkIxlm0SA+fPgQa9asYYNR65gryix7jLTVX0PH2BJm7veRFxuC9HUdWL6AvqJBadWqlbicf//9V6bMuLg4WFtba2xQuIKKqlz5hurq6iLh3nF0iDmqtA+Pvj/IZtHmzZvDxMREY33lxQy4d+9etkzJU4tsf+QKRMubmKS2MK8cvkd8QgKcnZ2RkJDAlg95au5YFjmRgQCXT2qVFtrWgV94PFsmR4wYIalCKAQtbRkZGRobiC+9ID09PQwfPpzNvpokXgBQkx3WlvVlcYAXALxw4QJq1qypMc5VqFAB6ycPVFhe207d4NC6D9uTffvttxqrU1lBDx48QPny5fM9lhYaVGmEsvS0ZeGEFtonFiU5ODioXTwvACgvdVIvVVFtULo9e/Zg1KhRMqqSRyv7oJ9DNmOW6eQzgIkl0j1FUisRSXxUflZWFho3bqw2U9XJQEIFUd++fdG0aVPQy7Fz5048e/aMqYxmz56NGjVqMAGChBsSambOnMkEksTERMyZIxKWCiJHR0fcunUL9vb2ePXqFSujY8eO6NWrF3bs2IGDBw+y//fv34/Nmzdj27ZtWLFiBQhQJDRNmDChsCrYc1JNqUu8ACBJnZwKhSRKGqCnT58ySY4Y2KJFC5CqZt26dUw4oWckqNCG+euvv8agQYMwffp0eHp6IicnB8/WDcIAxxzGK7MF95B1ezeyb+wQ846T+K5evYr58+ery1O10oeGhrL0586dw8CBAzFx4kR069YN/fv3ZwCkmW3GjBmoU6cOBAIBA2HZsmXZH0m91N/c3NwC6yQpmABMqigCIAlU3IxJEjFJ8cRf0vNRHXl5ebCwsGCf9BcfH6+wfHm1FtWjLvECgDdv3lTar49ZquJ2jUGXigKlZZLER9SmTRt1+al2+uDgYJbH1MQEgvQUtfMryyDUNRCDjNQ7pEkgAJLE63tkK+IVCGSQV6kWdgalA7Tt0AkmNURbFapHXeIFAAlkBw4cEDNU3U6qm57ebNIz0mAVNZH+kAFwW0ckmDnCatzf4irNzc0AJSeRqWnpCpsWGRGBuidcYfDNcITVdmNpaAm/ffs222tGv36JxtcmIm6i5KW2tjLHbysXKSyvvG0ldHIdlu9ZVFQU3gTcRfeg9YgYfVVcj7r84gUA1e0Un9I/f/6cNbfcH12QNkWkXzx+/Dj6f98d2bMLnoFz195minma2TiiU58sQTpaJF7Hq5pD2c+kcKZVhAEwLAiVqlSDvpExU54TOHOmiY4qiSpO3YKozVNkWJiz5hY7kuSWXPokdcyUKVOwz/k+FJ0WqToGvAAgKY6trKxU7ZPSdHYVrHFrlnLJtknjRkjssgxv3rzR6HFTQQ0nYYPIZmc3pEzyZv+TkPB95/YwXN5DnNWseTek/XdJpqj05dfZvq1cuXLi32m/TEth/XenEOI8hP1O+8cbN24wAMa+CYZ9tToy5eTNaCH+7rjVB+GzuyAvQ6JfzV59EwYGBjIrAgGQTnoIgOHDL4rrUXeQeAFARVJwQR2VPjuVTue9yg3j3T2QF/UC2Xf2wHT6FeiYWLKjOzr3zIsJYhIwEUmMtNEvauL6VmH3d0gcf01cXWZSPIxWSACoqB2Cld5MGS7dTlK4U/8bRp5BULVBLFu9evXg5eXFABj3NhSVnOQMCmZJzo8V1UMApJlWuh4CPhlljHq3Tswzqkdd4gUAubNXkvYGDBjApODHjx8zKZjOO93d3dlA0PkqqRK2bNnCzkJXr17NnpOkR2eeN1YNw1jX72DU0x1Z3ttBB+45/mdg2GkackN9IPhnKjgJmKQ/kqCLmsi4gMh2Tw/EjRUZPnAkFKSxGU4RWdrYQpCZme8RAY1UR01izuOlkyt7TnpAAgsBMD7iFWwdasjkS335EL6nDimsh0DXeMwChfXQj8PC1iB06Fn2vEGDBmqzixcAlD97VdZLOrxv2LChUiZkef+Olmm3CmTSw54H2PO2bduqzcyPyUBtJiHLbl8vxI4WLWUrV67E8gVzIVzYETp6eoCeAYRZAhjaVQN0dZH1NkhU1bq77IhR2sKGrGrIcKLZ+4sIdBggmg0bNsSVK1cYABMjw1C+ikhapWWUAK4/71s4n4hBUL8KcD4ejby0ZIS4OcPmx4V4f+AXpC27BktLS6ai4YiATmUPD1+r0GBDVV7wAoDUGdJ5KTrLVbWjqqarWLEiU1x/LqL9LQ2k/f7eiB55noGRNvxZyfGoU6smsmPewMDWAYIX9yEI9kPcoTVAXh5rXtKiS0xPJ20cQHs9AtzXCVfwrEp/Vl6TJk1w6dIlBsCk6DewthcpjKdOncoUz8bu7WH+dQ+k3juPMj3HwLhmc5g17QxdQ2MEudgjefFlBmpuv0p5qR6ikW898XLQSfY/1aMu8QaA6naML+npKI5AUuXvfogYdoY1m77r52QWugckAJJinQDIGcVyAGyVdA0B9n0YuOmEhY4zCYApMW9R1s5R5mTIbEmnAtmVsuQKMwujerj9NbcqjY5Yj+cux1l+zvBXHd5rAagOt4ogra+vLxtUh0P98fbHU2IA0m8Rzx8jPV2xvq9p+65ISk7OZ41N6hbai7VO8cJjO5GRLJ0UnT9/nqlrUt9HwMq2skxP/Pd4wPCdSBqXJ0tTE9jP2J7vdw6AY6M24tkAkRkX1aMuaQGoLsc0nJ6smImc/ueCsCGimeTo0aMYMdgFeku6QtfYDLqmFsiJj0K5gdOQ6nMWWe9Epye0BySbQX19fXGrCIAkdLRN/xePbHuy38lKmqy2aQZMj4uEeXl79jsdt9Fxn+XyrqhxMhYv+5Znn7kpCQhxq8H2nFkRIXg/7yw7rqO6OOJOp8bFbMKTfv8T16Mue7QAVJdjGk5PRrFE1Y8OQqjrEfY/Se1OduVRp4YzsiJfwbCSEzICfWFUpRZi9yxmezUiEg5IMKATG24J5gDYXnALD8p/x9KRIS9ZaNMMmBEfDTObSuJekABjuKAtrDoPRdLVg7AePAdmTTohfE43MQBj555hsyqdsXNExg1E42M343EfkSk/1aMuaQGoLsc0nJ4byBrHhyB4oMQk3kQnF2ar+xRYW9z8c8wQQfrIkI7cSAhpl3ET/1l3Y/nJrOzEiRNsBhQkxsCkrK1MueXX9iqwnpg5p9lek5TRHFE9tE2Y8H4L/HsfYi/Ax5ivaQGoYUCpWxy3l6p1cihe9JOcAxOoHl05heSkZIVFDpo4ExFRUUqraxF/GffKdmHPSaV07NgxBsCs5FgYWsraH56e2BPtK+gpLMtETxcGi0RSrjRxx3KNzw7Fp6iutABUFzEaTk96O6I6p90Q2EekgyTTsT3btsBkVS/oWZSDfjlbZIYFwmHTDYTP6Q5h5gdXgHV3mWqKU1aTTrBfv37Mw65l4lX4WImkW3I6ouM9AmB2ShwMLET+K3RuTPaHdhv6w7RBG1h1G44034swrFof5fpPwcveoiO+d9OPMZcIOqLkqEOHDqyepufd8KDHfjYDfoy3nBaAGgaUusVdv36dZal3djg89Qaz5ZQMQMkgdO3atexkhzziyBqIgElWKGZmZkwxTN5z5MpJwgHlI8OCoKAg5mXX1/gJbluIHKvI+PTw4cMMgLlpCcjWM2EW5lS2m5sbNm7ciCFDhoBmY9KBUn2bNm1i9dCpE3n7cQYPpE+kfScZ0NL+dVrKH/Dttldcj7r91wJQXY5pOD0dkRHVPzcCj3vsYcAiy2I6aqRBJ0U17a1IuCDjVdrzEXgIHGXKlGFpOAV97dq12V4vOTYCs5rq46ZZO7ZPI0CR1TNJssL0JDy99j/8sHALc/ska2myrCYdH52W0CxGgKZ2cL7UVCf9lpyczGZMMvMn8NFJyk/Rv+Jul92sD/IO/KqwSgtAVbhUhGlo0IkaXhgFUwMdnKu3DKZGErWKuGohuSGIzAO5z3wGpCRBBwdgcNI/0G81jAGQwNO9e3fmL0znzjqZqWh1axp8s+zx1qIeKysfkSFqIQEzstOS4aoncpe902kn++zatavanNICUG2WaT4DuZ3SbKZpoj2hvBM5OcVL6w25OhWFGZH2u5Fum3xamhkXLVJs0FpYn7QALIxD2udFygFeAPBJQADq1K0Lj1WrMc99YZEyRNXCN65bj+mzZuJJwBPUq6++HZyq9Wg6HVlgk7cfOZoXNKspmxEpT2GzJfecK5+kZ9oGKCJeAFDTg1BayyMJmYtssGDBAmb2RdIzCTjkgEX7UZJ4OQCR8lnRck3LLUnpisBIFjNkgU22mNIeheS1qGiPqAVgKUIjSdzkOkkgWbx4MQMR7QnJeJeAd+rUKSxfvhwUDGr79u3MNZRUQuTiSqDi1EIUFGnp0qXMXZSek6kWReAilc2yZctY2WTmRcd8lIZmXBKGFHnN8QKAp46fQJ/+/Vgn5JeO4sLPnBkz4LFhg3i2KK52qFMvzXAf47urTh3K0tKsylsAKurUYz8/NJAKmaYJJn1qGV9im6T7REpkAmCZMlYw8myGHF0DPDVvBgMU7NiujC8mgveoli1yrI8cI/FnURa4kxTl8sSLGfBTgaHNL+IAGaWSkjszJRFZJxeg/FiRApnoyciGcLZQfB7MpTHa/FCcnlQ0tEekOIULcg/g3SiRPrMgAUVRdFVeADA5KQmWVlbMKpfM1b8Ekmf0l9CmwtpA4T9oBsxMTYCldUUGFjrhoBMP4aKucPzdF6/GNka1A0GI2jAeFcZ5IO4fD9gMX4Jg18ow2PSAuQBwhgimpqaYNGkSdlZ/hKgR58TVK+IN/Ub7SF7OgFcuXkK7jh3w5/bfMennqawPxb3c7d/7FwYP/QGhISGo+SFucnG3qTAAklEqATA7LQlmZSUWMUzhPK8Nqh0IRsTKofhq+XGk+3vDwL46YnbMhd3cPQgaaAfdDSLrbQ6EJGQwADr7IcJNFEmWI0UzoSK3TV7MgIUxVvtcNQ6QlEsAzMlIhqmVJJoC5daZLYkAq6w0oackZjSl8fPzY2Ds7u+Ot0Pzm2zJA1KR26YWgKqNXYlIRYYKBMA8QSqMLcvJ7Neif/4G9iYFx8KhUCDMjfODCwBnSjYkfD3CP7gTKAWvUCgTZ5tLxwsArln5CzsBefniJWrUzC9JFQc6Fs1fgBWrVzHTJGNj4+Jogtp1klEqAVCYlQ5DM1Gok6+++or5FguX9kCVjV54PaklnPY+w5s538F20gYkXtyL8iOWIuRHZ1CEBOorF5qYA+DQNxvxerDy+NJUD+ceyss9oNqc1mZQyAEySiUA6mSnQ8/EkqUhl01yDTVZ1AHOxyIRveVnVJzxO5CXi6yIUCSc+R224z3xso8NKBQImYFx105wvsE/vtuEV64ix6SCZkBFbpu8mAG1eNIMB8golQComyOArrHkvhIqvTDfYEpDTlDSxAFwWORmhEj5syhqLeceyssZ8OGDB2jStCnex8bCRkE8ZVWH59nTp6ClkyS5o6dO4uL5C+jeQ+Q5pi6RZTJFUVB2XqpqeSOG/siOrKZMm4aatWth5dJlcF+6RNXsaqUjC2oCoF5eJmBgKpM3170LyhoWbATIOcJzzkmca+bwqC0I6q84tgxXCQFQ+hId7ndezIDr1qzF+MmTsHShO9Zt+pW1vVuHjrjkJTJnV5XCXr+Gg6OjeJA/BYCvX71iZQU8fowGH+LRfEybOMDJt03VPqmTjoI5kSLaQJiNXD2RPpXAREKFdHiOsn0noUz3kUj2Ooy0R9dQYZwnwmd2QtSskyxqGGeBzXn0jYz5DS/6iqLKKiMCoCK3TV4AUB0mF5RWEQDnzxYF+X70VBSl6nOTIgCeOHacbdofPnms0eaQXwkB0BC57BiOiE4ySJdHS3CNU3HMAV7fuhIzvX49oQV0za3EAIyceYIJLeTMREQApNVkVOw2PO9TeATb1q1b5+tPqQDg4AEDmbZ/9vx5GpsBPxUZ3OyrbAakkBx00qBJost1CIBGurnIEsqa/VfaMxHCrCyl1eno6yNy9O8yzynCP82eXR8twLNe+woNoawo5jYvAHjqxAn06dfvo4/ilA3ypyzBa39ZhbkL88fNUxUwxQFAMv0nAJroCSHIk0RToNm2nGdfGOkWvAeMnn1K7AgfGBiI8ePHM/vCyGn2eNJT5BnHBY1XxAdFlzHyAoCqDqqydKoAcMhAF9StV6/IBAD5tqkCQO/r19kS911PUYyXT6Xdu3czIcREX4j0bLBzYIoTTXszvbQE6JtbISc1CU51GiDkqT8MLMogV5COvGyaGYXINSvHzOHIhpB0h3QpYt26dVH/3Eg87iExbJAHIedbQr7E8lSiAcgtY6oAcIOHJ2bMmf2pY6xyflUASIVpchkmg1ECoJmBDhLSMlnZdH0DGZ7S7Zx0nwp9JwNUAtno0aNZbG4yAuHcROkkhCJtkeRO/sbkg9zl/mw87CYBoPxMyAGQ3EN5CcC9u3ZjxGjVg0amUNgygO1PiMnqAJCiRWWxWHimMDZRfsJBxghuI4arDDhqU25entj7TR0A0mxDQkFZqWDkKlcslZD2gHS9q4WhHmqcHYlbbbbksy5SVa1EpvwEPrr2YUziLuYbrMwKhgBIfKVLhngJQEUbck7lQUtnfFwcfv1tKw78tY/9b//VV+Lbg2jJiI6Kgm3Fivhx+HAc+OsvZiJOe5eY6GhUsBUF6gkJDka16tVRmUJQhIejabNmuHXzJkhyPnBYcpEzx0BF1tlcm5o3bMQi10+dMR137/jAqZoT3r19J66DyuDq5trCtY1rK3f7kXT7h5LZ+w7RjU6/rF3zMRjE5cuX2UvZwGv6R+VXlEm3TCXcqTm5wPKU+Qzzfgmm5cF93jx4btyIv/fvxw9ubmLAcW/zi8DnqFylMkzNzLBiyVIsWrYUXlevoUPnTmIzf/L2p4Ehvdgvy5Zj4ZLFTGlNS426wsaJo8fg4OiAJs2aiYHGzeKhwcFwql4d0jMo9+zksePoO6A/goOCUN3ZGb9v/Y3pPwUZGTh35iwGuLowEMdEx6BVa/VDoWkMcRosiNcAJHfNekqurz97+jS+7927QFZxRg4J8fGfvLxRRQSUBXPmYsOWzUhMSEAZuWserl+5go5dRBGrtCTiAG8BSFYoZCnNLaHcgGakp8PE1BS/rt+Aga4uuOdzl122N3b8uHxjTrMQnWY4VnVElQ9XjdL+z/Ajra5fhYay+shQlXxhc7KzUVXqAr9/vb3xbdu2bIm/4e2NtNRUuAwaxI4X13t4olHjxuywv+U3hdvmlRQA8xaAJWUASns/tAAs7Qgo5v5rAVjMA1Daq9cCsLQjoJj7rwVgMQ9Aaa9eC8DSjoBi7r8WgMU8AKW9el4AkDspCA8LE+vrSurA3fDyRrsO7eFz+06JOe0oaKx4AUA6C6Yg2tKXpXyM+TsfQEvKaR26+ShPCDNzM9bkktpXXp+E8AFM2jYWzgFezICFd0Obgq8c4AUAuRjRmzdsxLRZM/nKa5XaTd52ZJVDVi+tFDjxqFQIjxLxAoA84qe2qWpyQAtANRmmTa5ZDvACgFyM6ILs/zTLluIrLTIiApXs7LBl46+YMn1a8TXkM9XMCwAq4sWXHgxSk+NXkvvKWwBqcoC1ZRUfB3gBQC5GNEXjlL4dvPjYVnQ1c85KdP8a3VhZ0okXAORiRP+9/4DYPbOkLksB/v6IiIhkjuDdvhNF7iqpfdWehJT06YUH/ePFDPjF8DFOFBUK1hW+mCYVWUOSEoCc7CLvKy8AyLlP3vDyQjsF8UWKbBCo4G0ewMQ5OLE3HP2avgfqNxH9P6JKkVR75J/DcBk8CHt27sLIMaOLpA6lhUaEA3Yf+vWh31uXPsfkpbWKrB28AGCR9V6Vgj8zAFVpUpGl0QIwH2t1hAXF+yqCkXj1IhWGRrqwd/wQm08VAH6m2ULT3Y0IS0d2lhDWtkYwt9QHVAHgyX+AvoPx2DcBDVqU/eQm8WIG5GJE5+bkQO/DHRWf3HP5AnZvAUZNQb4l5zMD8O6dO2j5zTcIfPYMtRVcbaWRfn/o087ljzFmcQMJmLQAVDwDcjGiyRpmweJFLJHGjTS/EAAumDMH5aytceO6N85culA0fdUCUOX3uOiW4Fmjgfg47KzlicyMPEyqfFmjM2BYUCrsHExhYFjw7UMqc+JTElJfAXgIZ7DPOdXOMcHqk2fAiEtsOd60KBAT3GuyrYu6xIslWN1OqZz+5lWgTWe8e50O++u7NApAVia3j1S5QZ8poaZmwA8A/BRJmRcA5GJEf/TwrFsMDBmDdZtSMGRiVZQrbwQTMz3gcwAw4CFQvRYEu/6AcOQU7PQIwpRlytUanxK3mvHn6D6gVXv4/XULtj/2w6l9bzDeXe56s6IEYEY6sHMT8ibNw27PYIyZ61zgsPECgKoC78LhCHw3yE6cfOdaYkB18XehECAp16mW5JaglVMC4L6lvkwVmYJcGBlLLm9eMSkAi36TpBGk58LYVPZy54Wj/PDL7kbichTpCn9b+gKTltYUpzlz4C1qNrSEcz1L6BQcHzwfCza7P8fUlRIgXzoSgW4ukr5Thu0rXmLCIgn4dqwKwrgFsoDw80lAo1YSaXau20Os3d9Epj7iWdWaynmWkpSN3BwhylgbivOtmhqABZslPAt6koLKTqbIzs6DhZXoigiiEgXA/ZtC4fazk7hzN85Go933ogioRHl5QoQGpqJ6XQvxb77e79GivezVpfIAvH05Bq27Sk4/gp4kw6GGOQyl9nfR7wSwtZeE9N3lEYwRM6tBT0+CrC2Ln2PKcgloAnwTkRiXidbdKkC3kAj18gjcuz6Elc9R4KMk1G4suoCQo4e349GkdTnxd/+7CWjYUlZ18uR+Iuo1K6OUH9lZebh4JAK9hn4leXEOvpX5Tn0nnlWpJvLiI7p1MQbfdpfwLC4mk/EiU5AnwydeANDepgIMDQ3QvkMH+D3yw/Gzp2FtYyO2Fnn75g1c+w1g8Zd79vpefKk1MWL71q14ExaO2nXrimM6x71/D38/P7Ru0wbk8nntyhW4z53PLuG79+gBC/FLlJOdg+TkJBa80nP1GpAU3qxFc5w8L7odnKKWtmnXlsWUJh+OWdOmIzQ4BMYmJqjqVJVF3d+07TcZULRq0gw/z5yB3n37sIitBRGpQCmWIMUu/MHFFf96ebMoqVyZ6WlprK601DRMnTABF85fQFRCHCvSfd58DHR1RaMmjWWqoP669OkLv0ePMGzkSHZ3CheIXFdHh5VH1KRufejp62H2vHks5uHa9Z4Iex2Gas6iFaVZ/YaMXxTBtVnzZuwZhUHu3FUSgLOGgyOu3bqJe3d8MHCQq8Ku8gKA1NFMgYDma1hbW4vD6nI94oJjJyYkQldPN58ZE4XfpWCRFHjSwkI0+1G0dwrHS3nJ35gFNhcKsWPbdowe9xNsbW3Zd/oTZAhYueSzS8Dn4jrTtaXZWVmwtLJiV5iS7zKZU5GuUk9XlwGMYlFzRGmoHZSffH8pHnRhuj4yQaN89ElAZ/VnZsHQSFIuF6/a5/ZtNGjUiAW5pNDFZLpGMaaJODM2eiEnTJ4MegkpeLiZublMoHIuPDB7rqvLAr1Lm4VxJnEU9FOYlwcLC5HJmBBCVh7XX7pWjSy66Te64lXZy8YLABY4TWgf8poDWgDyevj433gtAPk/hrzugRaAvB4+/jdeC0D+jyGve8ALAHJ+wYpuJ+I197WN568iuiQ76pQmXPJiBixNA1La+soLAHJ+waXFV7Y0gZAXAOT8go8fOcquwSLSLsElA6a8AGDJYLW2F4o4oAWgFhfFygFeAJDzCy4N4dmKFQ3FUDkvAFgMfNFW+Zk4oAXgZ2K0thrFHOAFADm/4PexsexyZy2VHA7wAoCcXzDdlFSnbl3GfY37BZecMeVVT3gBQF5xVNtYtTigBaA67PJwB4xNsOJFL+YBJu1gpE4x2rQSDvACgJxfMDkffVW58ucdP1Viw3zeFpWo2ngBwGLluBaARcp+LQA59hLQKlTEZv/msKlojB8mVRU9UX1yU/0AAAJfSURBVAWAPA3PVqTIUrFwXgCQuy+YXA2NjIxU7Jqayb6Q6Fhqtpr3yXkBQO6+4Iz0dLF/qcbVMFoAFguYeQHAIuEMLZvvwrGn3HQkJ2bj56pXSk90rCJh6McVWnoBSPz6HNGxPm5cSk0uXgBQbSuYd+EsWESUUBQcp+LpLSwgIxfHThzd6nMAkMKz1W8CwdZfYTx5mqgNc0WR6LP1RMGMvogglsUEeV4AUFXe7PglCOMWSsKPhT5PgVMtSSQsio519Xgkug6UhDGjkG3yodHko2Pl5gplolxFhmegUhVREB+O3oSkobJUdKj1c59h5to6MmnkI0b9748wQCjEgNEO0NNXMz6bqkz5wtOVKAD6esehRXtrMcvb2V3GjYiu4u+CjFysnBSAlVJx/FqXv4jbsd1lhikrM08m3Kx8GirH2EQ2PmBOdh70DSQhav+7EYfm7SRtoQoC/ZJQu5EkhNqYrj5Yd6ipTFy9LxwvGm9eiQKgxrmjLbDIOcBbAFJYtISEBPjeu4fve/dmjOJumqT/yYKGbhwa7TYcE6ZMRt369VjItWFDfsDKtWsQ9uo1evfry/I9DwxkIc1MTU3xn68vuvfowUK2UWgz+qQwbkTnz55jsfAq2IqCXlKotbT0dAS/DMJ9X1/UrlsHbdu3F4d8u+fjg6pOThgx1A1Xbnhh2qTJWLfpVxZm7dbNm7T6wtTUBG3atWPl7du7l4Uy6zdgAAuLtn6tByuzZ69eRQ6E4qqAtwBUhWECgYANKFFiYiKLDcjFy1MlP6UJDQmB93UvjBo7RtUs2nRqcOBLB+D/ARV2ZIemfNgHAAAAAElFTkSuQmCC</thumbnail><stage name="Stage" width="700" height="700" costume="0" color="255,255,255,1" tempo="60" threadsafe="false" penlog="false" volume="100" pan="0" lines="round" ternary="false" hyperops="true" codify="false" inheritance="true" sublistIDs="false" scheduled="false" id="1"><pentrails>data:image/png;base64,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</pentrails><costumes><list struct="atomic" id="2"></list></costumes><sounds><list struct="atomic" id="3"></list></sounds><variables></variables><blocks></blocks><scripts></scripts><sprites><sprite name="Sprite" idx="1" x="28.078125" y="-345" heading="90" scale="1" volume="100" pan="0" rotation="0" draggable="true" hidden="true" costume="0" color="8,0,2,1" pen="tip" id="8"><costumes><list struct="atomic" id="9"></list></costumes><sounds><list struct="atomic" id="10"></list></sounds><blocks></blocks><variables></variables><scripts><script x="25.275576636904752" y="41.42857142857143"><block s="doSetVar"><l>num. repliche</l><l>10000</l></block><block s="doSetVar"><l>B0</l><l>10000</l></block><block s="doSetVar"><l>N0</l><l>8000</l></block><block s="doSetVar"><l>num. estrazioni</l><l>10</l></block><block s="doSetVar"><l>h (h=0 sì reimmisione, h=1 no reimmissione)</l><l>1</l></block><custom-block s="inizializzazione"></custom-block><block s="doRepeat"><block var="num. repliche"/><script><custom-block s="esecuzione esperimento"></custom-block></script></block><custom-block s="frequenze relative"></custom-block><custom-block s="probabilità"></custom-block><custom-block s="diagramma distr. freq. rel."></custom-block><custom-block s="diagramma distr. ipergeometrica"></custom-block><custom-block s="confronto distr. freq. rel. e distr. ipergeom."></custom-block><custom-block s="distribuzione binomiale"></custom-block><custom-block s="confronto distr. freq. rel. e distr. binomiale"></custom-block><custom-block s="confronto distribuzione ipergeom. e binomiale"></custom-block></script></scripts></sprite><watcher var="X" style="normal" x="10.000000000000114" y="93.40000600000003" color="243,118,29" hidden="true"/><watcher var="j" style="normal" x="10.000000000000114" y="149.00001000000006" color="243,118,29" hidden="true"/><watcher var="num. bianche rimanenti" style="normal" x="10.000000000000114" y="233.80001200000004" color="243,118,29" hidden="true"/><watcher var="num. nere rimanenti" style="normal" x="12.999999999999886" y="271.600014" color="243,118,29" hidden="true"/><watcher var="frequenze" style="normal" x="402.00000000000045" y="154.600014" color="243,118,29" hidden="true"/><watcher var="B0" style="normal" x="4" y="8" color="243,118,29"/><watcher var="N0" style="normal" x="103.99999999999932" y="7.800002000000006" color="243,118,29"/><watcher var="num. estrazioni" style="normal" x="3" y="40.200008000000025" color="243,118,29"/><watcher var="num. repliche" style="normal" x="2.9999999999995453" y="74.60000400000001" color="243,118,29"/><watcher var="h (h=0 sì reimmisione, h=1 no reimmissione)" style="normal" x="213.08587239583335" y="5" color="243,118,29"/><watcher var="freq. relative" style="normal" x="326.0000000000002" y="39.60001399999999" color="243,118,29" extX="112" extY="98"/><watcher var="probabilità" style="normal" x="480.0000000000007" y="38.600014000000044" color="243,118,29" extX="112" extY="98"/><watcher var="distribuzione binomiale" style="normal" x="485.99999999999955" y="176.6000140000001" color="243,118,29" extX="112" extY="98"/></sprites></stage><hidden></hidden><headers></headers><code></code><blocks><block-definition s="esecuzione esperimento" type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="doSetVar"><l>X</l><l>0</l></block><block s="doSetVar"><l>num. bianche rimanenti</l><block var="B0"/></block><block s="doSetVar"><l>num. nere rimanenti</l><block var="N0"/></block><block s="doRepeat"><block var="num. estrazioni"/><script><block s="doSetVar"><l>j</l><block s="reportRandom"><l>1</l><block s="reportSum"><block var="num. bianche rimanenti"/><block var="num. nere rimanenti"/></block></block></block><block s="doIfElse"><block s="reportGreaterThan"><block var="j"/><block var="num. bianche rimanenti"/></block><script><block s="doChangeVar"><l>num. nere rimanenti</l><block s="reportMonadic"><l><option>neg</option></l><block var="h (h=0 sì reimmisione, h=1 no reimmissione)"/></block></block></script><script><block s="doChangeVar"><l>num. bianche rimanenti</l><block s="reportMonadic"><l><option>neg</option></l><block var="h (h=0 sì reimmisione, h=1 no reimmissione)"/></block></block><block s="doChangeVar"><l>X</l><l>1</l></block></script></block></script></block><block s="doReplaceInList"><block s="reportSum"><block var="X"/><l>1</l></block><block var="frequenze"/><block s="reportSum"><block s="reportListItem"><block s="reportSum"><block var="X"/><l>1</l></block><block var="frequenze"/></block><l>1</l></block></block></script></block-definition><block-definition s="inizializzazione" type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="doSetVar"><l>probabilità</l><block s="reportNewList"><list></list></block></block><block s="doSetVar"><l>frequenze</l><block s="reportNewList"><list></list></block></block><block s="doSetVar"><l>distribuzione binomiale</l><block s="reportNewList"><list></list></block></block><block s="doSetVar"><l>freq. relative</l><block s="reportNewList"><list></list></block></block><block s="doRepeat"><block s="reportSum"><block var="num. estrazioni"/><l>1</l></block><script><block s="doAddToList"><l>0</l><block var="frequenze"/></block></script></block></script></block-definition><block-definition s="frequenze relative" type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="doFor"><l>i</l><l>1</l><block s="reportSum"><block var="num. estrazioni"/><l>1</l></block><script><block s="doAddToList"><custom-block s="arrotonda %n %n"><block s="reportQuotient"><block s="reportListItem"><block var="i"/><block var="frequenze"/></block><block var="num. repliche"/></block><l>3</l></custom-block><block var="freq. relative"/></block></script></block></script></block-definition><block-definition s="distribuzione ipergeo [i, bianche, nere, estrazioni] %&apos;i&apos; %&apos;b&apos; %&apos;n&apos; %&apos;k&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportQuotient"><block s="reportProduct"><custom-block s="binom %n %n"><block var="b"/><block var="i"/></custom-block><custom-block s="binom %n %n"><block var="n"/><block s="reportDifference"><block var="k"/><block var="i"/></block></custom-block></block><custom-block s="binom %n %n"><block s="reportSum"><block var="b"/><block var="n"/></block><block var="k"/></custom-block></block></block></script></block-definition><block-definition s="probabilità" type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="doFor"><l>i</l><l>0</l><block var="num. estrazioni"/><script><block s="doAddToList"><custom-block s="arrotonda %n %n"><custom-block s="distribuzione ipergeo [i, bianche, nere, estrazioni] %n %n %n %n"><block var="i"/><block var="B0"/><block var="N0"/><block var="num. estrazioni"/></custom-block><l>3</l></custom-block><block var="probabilità"/></block></script></block></script></block-definition><block-definition s="colonna %&apos;valore&apos; %&apos;base&apos; %&apos;fattore di scala&apos; %&apos;etichetta&apos;" type="command" category="pen"><variables><list struct="atomic" id="225">x,y</list></variables><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input><input type="%n"></input><input type="%s"></input></inputs><script><block s="setHeading"><l>0</l></block><block s="down"></block><block s="doRepeat"><l>2</l><script><block s="forward"><block s="reportProduct"><block var="valore"/><block var="fattore di scala"/></block></block><block s="turn"><l>90</l></block><block s="forward"><block var="base"/></block><block s="turn"><l>90</l></block></script></block><block s="up"></block><block s="doSetVar"><l>x</l><block s="xPosition"></block></block><block s="doSetVar"><l>y</l><block s="yPosition"></block></block><block s="forward"><l>-10</l></block><block s="turn"><l>90</l></block><block s="write"><block var="etichetta"/><l>12</l></block><block s="gotoXY"><block var="x"/><block var="y"/></block></script></block-definition><block-definition s="diagramma a barre %&apos;lista valori&apos; %&apos;base colonne&apos; %&apos;fattore di scala&apos;" type="command" category="pen"><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%n"></input><input type="%n"></input></inputs><script><block s="doFor"><l>i</l><l>1</l><block s="reportListAttribute"><l><option>length</option></l><block var="lista valori"/></block><script><custom-block s="colonna %n %n %n %s"><block s="reportListItem"><block var="i"/><block var="lista valori"/></block><block var="base colonne"/><block var="fattore di scala"/><block s="reportDifference"><block var="i"/><l>1</l></block><variables><variable name="x"><l>0</l></variable><variable name="y"><l>0</l></variable></variables></custom-block><block s="forward"><block s="reportSum"><block var="base colonne"/><l>3</l></block></block></script></block></script></block-definition><block-definition s="asse verticale %&apos;unità di mis.&apos; %&apos;num. intervalli&apos; %&apos;fattore di scala&apos;" type="command" category="pen"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input><input type="%n"></input></inputs><script><block s="down"></block><block s="doFor"><l>i</l><l>0</l><block var="num. intervalli"/><script><block s="setHeading"><l>90</l></block><block s="forward"><l>5</l></block><block s="forward"><l>-5</l></block><custom-block s="scrivi numero %n"><custom-block s="arrotonda %n %n"><block s="reportProduct"><block var="unità di mis."/><block var="i"/></block><l>2</l></custom-block><variables><variable name="x"><l>0</l></variable></variables></custom-block><block s="setHeading"><l>0</l></block><block s="forward"><block s="reportProduct"><block var="unità di mis."/><block var="fattore di scala"/></block></block></script></block><block s="up"></block></script></block-definition><block-definition s="scrivi numero %&apos;numero&apos;" type="command" category="pen"><variables><list struct="atomic" id="323">x</list></variables><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="up"></block><block s="doSetVar"><l>x</l><block s="xPosition"></block></block><block s="setHeading"><l>-90</l></block><block s="forward"><l>30</l></block><block s="setHeading"><l>90</l></block><block s="write"><block var="numero"/><l>10</l></block><block s="setXPosition"><block var="x"/></block><block s="down"></block></script></block-definition><block-definition s="arrotonda %&apos;numero&apos; %&apos;num. cifre decimali&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportQuotient"><block s="reportRound"><block s="reportProduct"><block var="numero"/><block s="reportPower"><l>10</l><block var="num. cifre decimali"/></block></block></block><block s="reportPower"><l>10</l><block var="num. cifre decimali"/></block></block></block></script></block-definition><block-definition s="diagramma a barre %&apos;lista1&apos; %&apos;lista2&apos; %&apos;base&apos; %&apos;fattore di scala&apos;" type="command" category="pen"><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%l"></input><input type="%n"></input><input type="%n"></input></inputs><script><block s="doFor"><l>i</l><l>1</l><block s="reportListAttribute"><l><option>length</option></l><block var="lista1"/></block><script><block s="setColor"><color>255,45,20,1</color></block><custom-block s="colonna %n %n %n %s"><block s="reportListItem"><block var="i"/><block var="lista1"/></block><block var="base"/><block var="fattore di scala"/><l></l><variables><variable name="x"><l>0</l></variable><variable name="y"><l>0</l></variable></variables></custom-block><block s="forward"><block s="reportSum"><block var="base"/><l>2</l></block></block><block s="setColor"><color>41,0,177,1</color></block><custom-block s="colonna %n %n %n %s"><block s="reportListItem"><block var="i"/><block var="lista2"/></block><block var="base"/><block var="fattore di scala"/><block s="reportDifference"><block var="i"/><l>1</l></block><variables><variable name="x"><l>0</l></variable><variable name="y"><l>0</l></variable></variables></custom-block><block s="forward"><block s="reportSum"><block var="base"/><l>4</l></block></block></script></block><block s="setColor"><color>8,0,2,1</color></block></script></block-definition><block-definition s="distribuzione binomiale %&apos;i&apos; %&apos;k&apos; %&apos;p&apos;" type="reporter" category="operators"><comment x="0" y="0" w="186.66666666666666" collapsed="false">Una moneta di trucco p viene lanciata k volte (&quot;trucco p&quot; significa: la probabilità di TESTA è p); sia X la variabile aleatoria che rappresenta il numero di uscite TESTA.&#xD;&#xD;La funzione fornisce la probabilità che TESTA si presenti i volte cioè fornisce il valore &#xD;&#xD;      P(X=i)&#xD;&#xD;Parametri:&#xD;(1) i&#xD;(2) k&#xD;(3) p&#xD; </comment><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportProduct"><custom-block s="binom %n %n"><block var="k"/><block var="i"/></custom-block><block s="reportProduct"><block s="reportPower"><block var="p"/><block var="i"/></block><block s="reportPower"><block s="reportDifference"><l>1</l><block var="p"/></block><block s="reportDifference"><block var="k"/><block var="i"/></block></block></block></block></block></script></block-definition><block-definition s="binom %&apos;n&apos; %&apos;k&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doDeclareVariables"><list><l>num</l><l>denom</l></list></block><block s="doSetVar"><l>num</l><l>1</l></block><block s="doSetVar"><l>denom</l><l>1</l></block><block s="doFor"><l>i</l><block var="n"/><block s="reportSum"><block s="reportDifference"><block var="n"/><block var="k"/></block><l>1</l></block><script><block s="doSetVar"><l>num</l><block s="reportProduct"><block var="num"/><block var="i"/></block></block></script></block><block s="doFor"><l>i</l><l>1</l><block var="k"/><script><block s="doSetVar"><l>denom</l><block s="reportProduct"><block var="denom"/><block var="i"/></block></block></script></block><block s="doIfElse"><block s="reportEquals"><block var="k"/><l>0</l></block><script><block s="doReport"><l>1</l></block></script><script><block s="doReport"><block s="reportQuotient"><block var="num"/><block var="denom"/></block></block></script></block></script></block-definition><block-definition s="distribuzione binomiale" type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="doFor"><l>i</l><l>0</l><block var="num. estrazioni"/><script><block s="doAddToList"><custom-block s="arrotonda %n %n"><custom-block s="distribuzione binomiale %n %n %n"><block var="i"/><block var="num. estrazioni"/><block s="reportQuotient"><block var="B0"/><block s="reportSum"><block var="B0"/><block var="N0"/></block></block></custom-block><l>4</l></custom-block><block var="distribuzione binomiale"/></block></script></block></script></block-definition><block-definition s="diagramma distr. freq. rel." type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="clear"></block><block s="hide"></block><block s="gotoXY"><l>-300</l><l>50</l></block><custom-block s="diagramma a barre %l %n %n"><block var="freq. relative"/><l>10</l><l>200</l></custom-block><block s="gotoXY"><l>-315</l><l>50</l></block><custom-block s="asse verticale %n %n %n"><l>0.1</l><l>6</l><l>200</l></custom-block><block s="gotoXY"><l>-315</l><l>30</l></block><block s="setHeading"><l>90</l></block><block s="write"><l>distr. freq. relative</l><l>12</l></block></script></block-definition><block-definition s="diagramma distr. ipergeometrica" type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="gotoXY"><l>-85</l><l>50</l></block><custom-block s="diagramma a barre %l %n %n"><block var="probabilità"/><l>10</l><l>200</l></custom-block><block s="gotoXY"><l>-100</l><l>50</l></block><custom-block s="asse verticale %n %n %n"><l>0.1</l><l>6</l><l>200</l></custom-block><block s="gotoXY"><l>-100</l><l>30</l></block><block s="setHeading"><l>90</l></block><block s="write"><l>distr. ipergeom.</l><l>12</l></block></script></block-definition><block-definition s="confronto distr. freq. rel. e distr. ipergeom." type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="gotoXY"><l>-300</l><l>-140</l></block><custom-block s="diagramma a barre %l %l %n %n"><block var="freq. relative"/><block var="probabilità"/><l>10</l><l>200</l></custom-block><block s="gotoXY"><l>-315</l><l>-140</l></block><custom-block s="asse verticale %n %n %n"><l>0.1</l><l>6</l><l>200</l></custom-block><block s="gotoXY"><l>-345</l><l>-160</l></block><block s="setHeading"><l>90</l></block><block s="write"><l>distr. freq. rel. (rosso), distr. ipergeom. (blu)</l><l>12</l></block></script></block-definition><block-definition s="confronto distr. freq. rel. e distr. binomiale" type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="gotoXY"><l>45</l><l>-140</l></block><custom-block s="diagramma a barre %l %l %n %n"><block var="freq. relative"/><block var="distribuzione binomiale"/><l>10</l><l>200</l></custom-block><block s="gotoXY"><l>30</l><l>-140</l></block><custom-block s="asse verticale %n %n %n"><l>0.1</l><l>6</l><l>200</l></custom-block><block s="gotoXY"><l>20</l><l>-160</l></block><block s="setHeading"><l>90</l></block><block s="write"><l>distr. ferq. rel. (rosso), distr. binom. (blu)</l><l>12</l></block></script></block-definition><block-definition s="confronto distribuzione ipergeom. e binomiale" type="command" category="other"><header></header><code></code><translations></translations><inputs></inputs><script><block s="gotoXY"><l>-300</l><l>-320</l></block><custom-block s="diagramma a barre %l %l %n %n"><block var="probabilità"/><block var="distribuzione binomiale"/><l>10</l><l>200</l></custom-block><block s="gotoXY"><l>-315</l><l>-320</l></block><custom-block s="asse verticale %n %n %n"><l>0.1</l><l>6</l><l>200</l></custom-block><block s="gotoXY"><l>-315</l><l>-345</l></block><block s="setHeading"><l>90</l></block><block s="write"><l>distr. ipergeom. (rosso), distribuzione binom. (blu)</l><l>12</l></block></script></block-definition></blocks><variables><variable name="B0"><l>10000</l></variable><variable name="N0"><l>8000</l></variable><variable name="num. repliche"><l>10000</l></variable><variable name="X"><l>7</l></variable><variable name="num. estrazioni"><l>10</l></variable><variable name="j"><l>8943</l></variable><variable name="num. bianche rimanenti"><l>9993</l></variable><variable name="num. nere rimanenti"><l>7997</l></variable><variable name="frequenze"><list struct="atomic" id="640">0,34,212,737,1444,2323,2430,1725,846,221,28</list></variable><variable name="freq. relative"><list struct="atomic" id="641">0,0.003,0.021,0.074,0.144,0.232,0.243,0.173,0.085,0.022,0.003</list></variable><variable name="probabilità"><list struct="atomic" id="642">0,0.004,0.021,0.07,0.154,0.231,0.241,0.172,0.081,0.022,0.003</list></variable><variable name="distribuzione binomiale"><list struct="atomic" id="643">0.0003,0.0038,0.0211,0.0705,0.1542,0.2313,0.2409,0.1721,0.0807,0.0224,0.0028</list></variable><variable name="h (h=0 sì reimmisione, h=1 no reimmissione)"><l>1</l></variable></variables></project>