[size=150]Priya’s cat is pregnant with a litter of 5 kittens. Each kitten has a 30% chance of being chocolate brown. Priya wants to know the probability that at least two of the kittens will be chocolate brown.[br][br]To simulate this, Priya put 3 white cubes and 7 green cubes in a bag. For each trial, Priya pulled out and returned a cube 5 times. Priya conducted 12 trials.[br][br]Here is a table with the results.[br][/size][img]data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAANEAAALoCAYAAADm0BCjAAAgAElEQVR4Ae2dPZLiQPr0ifib72G4RXOE4QacgAtwgPZZmwPg7A0w1lsXe3pN1lxcvZGaSeLpGtEjQWXzSEpFMPqqyipl1k9V0PuxaLzZATvwlAOLp2q7sh2wA40h8iCwA086cBei//d/i8Yfe+Ax0D0GIndfQhQL+ng8DmDge9M5UPp71+2yoK5LVq7tgLOr7ehnvdJfQ/TZn0mclSFP4qESPUTpryFKFE6trpQh19K1zi8HSn8N0QRHRhnyBB/xpY9U+muIXhqHpvEyZE0r81Ut/TVEExwLZcgTfMSXPlLpryF6aRyaxsuQNa3MV7X01xBNcCyUIU/wEV/6SKW/huilcWgaL0PWtDJf1dJfQzTBsVCGPMFHfOkjlf4aopfGoWm8DFnTynxVS38N0QTHQhnyBB/xpY9U+muIXhqHpvEyZE0r81Ut/TVEExwLZcgTfMSXPlLpryF6aRyaxsuQNa3MV7X01xBNcCyUIU/wEV/6SKW/huilcWgaL0PWtDJf1dLf2UF0OByaxWLRbDab5nq99hoJu92urYP9GLYy5DH0eUx9LP0dPUTn87lZLpftB8d/2wjEarVqLpfL34q391nHEPWya/KFZg/RIwkbokdcm26dSUHEWQjLM34ww/znP/9pl2u4djqdGkCA2Qrlu5ZzvBY14ixliKYLxCNPNguIAAAHPsG4B1EXiKgTl3vUwn4MWxnyGPo8pj6W/k72OxEHPuFhSJx14g8LP3/+5O12tkIdzmK4QS1DdLNp1gezgyjCguS7ILo3G2EpiM0QzZqZPx5+dhCVs0cJEUDhkq/cG6I/xo8vNE37vwwcjZjMci4uv/CA92aPEqKyHL5P4ftQ1CvLRAMzHpdvyox9HHOfSn9HD1Ec9Bj4XL7dG/glRDwvZyFDNOZhru375CCCXXFJNhQi/KcWUIcQrdfrBh+cAzBs94DURvW4ehny40qu2eVA6e/oZ6Kuh5z7tTLkuftR+/lLfw1RbYcT6JUhf3eXuDKIf2v77j4o2yv9NURKt1+kXYb83d0wRL8df3UQ3x38lNp7Jjt+/+N3RJxziz/i8Of/+Dc2XCNArI89v6dCp7wf70Ut1It/KI/fXY/H4+0XVJSDZqzbNQOWPyChzqNb6a9nokedTFyvDLlPV+MgjQBECJ6FqAQU2oS0hCv2gQO+q34sF48jnPfqUbePP7FM6a8hiu5M5LgMuc9jxUHMwRXf3rjWByK0Ra04I8SZguCwXxFgDv7YFq8RBup2abLPZRmeo02WoS770Xdf+muI+jo3onJlyH26Xg5Q1IkDGQMvnhO0OJB5rQsiDtw4mNmvqIFy3Mo67CMh/Ko/XApSI85SPO7qC9v+al/6a4i+cmuk98qQ+zwGB2gcWHGQYjDGcwITAeA1Q/Tb8UeC6BOWy+gdeCQ7Dny8pQlDfIvjWoSIs0FXPV7jbIAn5jXosy6dGLqcY/3YH+hjI9Rsm+3ynG0+sy/99Uz0jJtJ65Yh9+lmHMhc7nDPQQsdHPN6uS8HMu+zfldd3uNgZx3u4+BnfdbpA9FXz8X+9vEnlin9NUTRnYkclyEPeSwOVA5izEZxiwMXZbbb7e0/NhXLxlmMgx468Trqxy/3nEXYdlxaoi77Rr3YFwJBjQhfrEtt7GN/4zP+7bj01xAFx8qQwq1RHZYhj6rzI+hs6a8hCqEZomCGD+86YIjuWvPncuGLoqlvlSGn7uwIO1f6m2Ym4hdLrJH3+/3ty+u9tS3XxfGLI69xRoEO9LgOxho4rqO/0qYG6sZ1OzOP96NO7A+eCeXifdZX7suQlW3NUbv0Nw1E/ELIAR/3cRBz8GKPLQ5aXiu/vEat8jh+eaV2WQbn7ENsL5aLoJQ68d53DLoy5O9oc05tlP6mhIi/mhCGOAg5QAlMHNS8VtaLsw9h4MzXpR2vlVqsRx0MnrJPPI863znIypC/s+05tFX6mw6iOPA4O8VrHKAE5iuIONBjGQIawQIY2EptXGMfMOtweRZnoHjM9qjD8+8eWGXI393+1Nsr/TVE4S/0HPwE9FmIos53Dqwy5O9sew5tlf6OFiJ+l4kzCgctl2CcCYbORNTGgCBYnA2pHcuUA4d12J/yvvq8DFnd3tz0S39HBxG/k8RlFI85aDnQH4WIenFP7QhtvE/IMKAM0bSxGj1EcZBiEGNGeH9/b3/GJjSPQBRnq/K/OQm9uMWyEaSvvlvF+urjMmR1e3PTL/1NMxPNLQjl85YhK9uao3bpryGa4CgoQ57gI770kUp/DdFL49A0XoasaWW+qqW/hmiCY6EMeYKP+NJHKv01RC+NQ9N4GbKmlfmqlv4aogmOhTLkCT7iSx+p9NcQvTQOTeNlyJpW5qta+muIJjgWypAn+IgvfaTSX0P00jg0jZcha1qZr2rpryGa4FgoQ57gI770kUp/DdFL49A0XoasaWW+qqW/hmiCY6EMeYKP+NJHKv01RC+NQ9N4GbKmlfmqlv4aogmOhTLkCT7iSx+p9NcQvTQOTeNlyJpW5qta+muIJjgWypAn+IgvfaTSX0P00jg0jZcha1qZr2rp75cQobA/9sBj4M8xEF8hX0IUC/p4PA6Ub8rx9HwcPf3f//73qaOG6JMd0zgxRNocDZHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0McweosPh0CwWi/az2+20br9I3RBpjZ8tROfzuVkulzeAAJIh0g62qarPFqLr9dpst9sGMAEeQ/TYEIePm83m9jLCMXyNL6RaZcoX3/v7e7NarZrT6XTrfJ8yt8KVDmYLUfTPEEU3+h8TDoCDY2xcHhOiWmUIB/SxURcvP0LUp0xbufI/hqhpPBM9OKgweLEkxuDlxsFNiGqVgV6EFe0RGkLUpwz7WXNviAzRw+MJs0I5sEuIapShJmchdjhC1KcM69XeGyJD9PCYqgEIGv+bTh9A+pR5+EH/UtEQGaK/DJH7t2st1fro9Fmq9Slz/2kev2OIDNHDo+dyubS/jsUlHWaV+EtnrTIADbpc0nHmiT8s9Cnz8MN+UdEQGaIvhsffbxESDGZ89vt9+z2Jgx0KtcoQErSDHzSOx2Pz9vb26YeNPmX+/lTDShiiYX6NsvR3/icWOENgMN/bapXBDwvr9bqF9F5bfcrcq9v3uiHq69SIyykh+vnz5ydnMAPhD6CYfbjVKAPwoiZBxPcgbn3KsGzNvSGq6WZSLRVEHMhcymFfAlSrDH/Ojm1FgGB9nzKKiAyRwtVkmiqIkj3my7pjiF5m/fc1bIi0Xhsirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEMgghh+DNODxC0PzoPIqaLeBKP/TaLbozr2Nlp8xo0E2m7YnWVA4ZI5ewvXUOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyzhmi32zWLxeL22Ww2zfV61Tr+AnVDpDV9thCVABGm1WrVXC4XrevfrG6ItIbPFqLz+dwcj8ebu6fT6TYj4XhKmwoieLhcLm++vb+/N3gJRf/6lIne42W23++bt7e3BnVxD23gmNvhcGjbiS87vBTjSiK+JNEn9C3ep1aN/WwhKs2LYcdBUJYb47kCIvqFAY0Ny2AMUkBA//qUIUCsAzAw6AkOz2M72+22hYx12DbPAVBcUbANQyQevQgJAyCaL27y2+QVEJVvfjwMoYmDuRy4sQwHP7TihvqECNdxn2UAFY4xWxEsaHLmivpRE3XKvsT7zxx7Jmqa9s3J70QM5hlTs9WtDREHf+lVHMB9ynCWIXT0rYQI5wQAxwACbWFGQjvoR7zf9SI0RHRXsEcAUwYIlo0dIsC2Xq9bcAADQAI8gAgw4RqBxj1DJADlniTMJ0Awf6pbbYjgU9ebPc5EfcpwtoJW3JBFXM6xHH4IwowDqKiPawQM18o+ULerv7z37H6WyzmGQoDKPd9qz5qbpb4CIgx0+Eavoqd8IfUpw5UA63CJFyGCjyiHmQe/snFDHXwX4rIO19mPOBuxH1zysX6tvSEKf2wlTBwYtUx+tY4CIjwTByd8w6DHrMAv+HzmPmUIEnQw+KETIYBW1wxD4Mq8CBLzxCzED/tVcz9LiGoaOAYtFUTls2OgY2nF5VZ5H+d9ygC82rMGICph6+rfI9cM0SOujayOAiK87SMsfPtjsHJ7pMy92YWaffbQQNvcAGW5POS9GntDVMPF5BoKiLi84pIJ+wgQLOlTJi73qPXsjIF+UAt7JUB4TkOUHIAa3VNAVKNfU9EwRFNJ8ovnMERfmFPhliGqYGJ2CUOkTcgQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyDIEIY/ozTAwTtj86DiOkinsRjv82iG+M6dnbavAbNRNquWF3lgCFSOftL1xBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG8NsIbpcLs1qtWoWi8Xtg3Ncn9pmiLSJzhaiw+Fwg2fqIBkiQyRx4OPjo8GH2+l0aqFaLpfN+Xzm5Unsa0B0vV6bzWbT7Ha7myeczfFC4gbv4CH8xEZf+aLa7/fN29tb6zHulX5Dq1wRoE20jT5gwzn1UPb9/b29/9///vehPraiT/wz25kInjFwBlIG+oSvqarWgAgPVA5wQAAgttvtbYDjGgc8AcIeG6GjzzwnhIAEWtBkHcLLcwAUIWMbbHNoH2sEZYiWy9tbDTAx0BrmZtGoBRFeOpxF8Gzw6ng8ttDwuyQGOT4c/DiOGwY9IcJ1lscxNHCO2Yo5xDb50iNQ1EUdQhTL4/5XfWT9Z/ezhiiaB7MBUQw43h/zcS2ICAYGMWcNDFoMYlzjzFIeR+9wL3qMcwKAY2hBk7Mbcon34yxE3QjRkD6y/rN7Q/TbQQ6AKc5GtSCCVRjU5UCPg3+9Xrcw0U/cixvOI0QohzoRxhJQtIkNdf8GEcr17WPs1zPHs4Xo3//+920dT+P53agM/hmDM9StCRG8wcxQLrkwc+AaAMPGGYHn9KGEiOW6loW4RsBQH6ABwDKfOBOhXN8+sk/P7mcLEYwnNHHPpcOzxmaqXxMizBzwCNBgUGPjzBF/EMB1zAjwloOes1OciVgOeviVjRvqlD9aELg4G6Ec2oi5Dekj23tmP0uIEAbechEeHHPZ8IyhGevWhAjPV775cQ3excFNHwgS/MV9+F6W65phCFyZCUFidugLP2xzaB9jvUeOZwnRI0aNuU5tiJ7xgkstwFBrA0QlbLW0++gYoj4ujbzMqyACKJhRuN2bXXi/zx4aEUBAWS4P++jULGOIarqZVOtVEPH7CpdeNZbMmHWi3qsBQuSGKOnAr9mtV0FU8xkyaxmizOlU6pshqmTkHRlDdMeYKV02RNo0DZHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGMAgihOHPOD1A0P7oPIiYLuJJPPbbLLoxrmNnp81r0Eyk7YrVVQ4YIpWzv3QNkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGKKmaQ6HQ7NYLNrPZrNprter1vVvVjdEWsNnD9H5fG6Wy6Uh0o6zSavPGiLMOJh5ANF2u/VMNHColy+g9/f3ZrVaNafTqeE9HHPDMbzGPW5YBaDO5XJpL+12u9sLDdehWa4OapVhH57dzxoihIplHELhkq4M7FmDM9RXLOcICXzDxhcS/ISvPIe33HD848eP1ut4jRq4H4FiPjGTWmXYfo39bCHCmw+B8c1oiIYNJwzmOLhRm2Bh8GODpywDqFDneDy2e9xnBihf1m0FmqYtS41aZahdaz9biBAo3pp8Cxqi/kOKswy9Y81ykON8vV63sOAYS+aPj48WLAAEeDjzxGPqYR9hrVUm6tc4niVEDJu/yJV7BlvD4AwatZdzfSFiOQx+AEfoAAav4RhbLUD66NTOxBD9/mk7gmSI/j7M4gzB0nw5YSBzQ7n9ft/OQriPDTDhGpZpLNtVF2VjO7XKsG+19rOEqMs8BAuQuP7uKjPWa7VnIviAwQ+/OLtw1sE1gsFy8BQwoAw2wIAfGLjUwzXWjy8wtsFMapVpO1HxH0P020xDNHxUcZADHPxAgx8N3t7ePv2EzR8PCBtaIQwAK268Dj18cJ8flqtVhno19oaohovJNRQzUdcjY4aJs0tXmaHXAFEEsKt+rTJd2n2uGaI+Lo28jAIizAiYZbhxhsCAfnSDHnS4YabjnyB4rVYZ6tXYG6IaLibXUEDEL/lcenH59YwVADDqlQBBu1aZZ/pZ1jVEpSMTPFdANEGbHn4kQ/SwdeOpaIi0WRkirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEMgghh+DNODxC0PzoPIqaLeBKP/TaLbozr2Nlp8xo0E2m7YnWVA4ZI5ewvXUOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyzhmi32zWLxeLTZ7lcNufzWev6N6sbIq3hs4Xoer02m83mE0AAyhBpB9wU1WcL0eVyaVarVfvB8ZQ31UyEGRsvHc7m7+/vrZ+n0+lmZ58yKE8N7Pf7ffP29tauCHCvfLEdDoc/csOqAi9FvByxxVUGckbf4v1bBysczB6iGJ7K5Ao5PSWhgIhwYEBjizM7IepThgCxDl9uBIfnsZ3tdttCxjpsm+cACODw5cg2VPnOFiIGHCHCcTT/qZGbqLICovLNj8elp3EwlwM3luHgh1bcUJ8Q4TruswzAwDFmK4IFTc5cUT9qok7Zl3j/mePZQoQwOPXDQARCoBjOM8ZmqlsbIg7+0qc4gPuU4SxD6OhZCRHOCQCOAQTawoyEdtCPeL/rRWiI6K5wz0ABUjk4hM1+i/TYIUI26/W6BQcwACTAA4gAE64xM9wzRN8yrJrm58+fn1qC+ZyJcDylrTZE8KbrzR5noj5lOFtBK27wPy7nWO54PLYzDqCiPq4RMFwr+0Ddrv7y3rP72S7nYCqhifsy0GcNzlBfARFfOpwBONDhJV9CfcqgfqzDFUGECB6iHGYe/MrGDfr4LsRlHa6zH3E2Yj+45GP9WvtZQgSjEUaEB8ccELXMzaKjgAjPxsEJ7zDoMSvwCz6fvU8ZggQdDH7oRAig1TXDELgyN4LEfPFi5If9qrmfJUQ1DRyDlgqi8tkx0LG04nKrvI/zPmUAXu1ZAxCVsHX175FrhugR10ZWRwER3vYRFr7943L4kTL3ZpchlkMDbXMDlOXykPdq7A1RDReTaygg4vKKSybsI0CwpE+ZuNyj1rMzBvpBLeyVAOE5DVFyAGp0TwFRjX5NRcMQTSXJL57DEH1hToVbhqiCidklDJE2IUOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MQyCCGH4M04PELQ/Og8ipot4Eo/9NotujOvY2WnzGjQTabtidZUDhkjl7C9dQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIaoaZrD4dAsFov2s9lsmuv1qnX9m9UNkdbwWUN0Pp+b5XJ5AwggGSLtgJui+mwhigBhJpryVnMm2u12n140mLXx4sF1bpfLpVmtVu0MP7Q8NGI2eLG9v7+3eqfTiU1UK3MTfOJgthAhXAS03W4/zUZTBKomRBjImL0x0LFh/+PHj2a9XjeAh9d4PrQ8AWIOhBRZEaJaZdrOVvhnlhDFYBBO+WGAFfxNIVETIs4yHNDY7/f79mVEsOAfl8VDy5czFwwkNGyzVpla4cwSIgYLeBAItggWB0Atk1+tUxMiPAs844sGxxjcOMeHPvL+kPJddVE/QlSrTM1MZg8R324wFcEDLKznuTSpafartGpDBM/wovn4+Gj38AoDHUtjXMNSjrMSnrlv+VqA9NGpmcUsIYKBeIMCGM46ND5eq2n0K7VqQwRAAMrxeLzN5AAJXuIaPeUzDymPXLrq43sYX3i1yrB/z+5nCxGCLX/eBkDxS/Oz5mapXxsivHAw6+DDgY1nxeDGjwxxKYfrQ8pDDzlQI77c2FatMrXymS1EMDB+N5oqQHjO2hBBE4O8XPZicN97CQ0pT0iYCWa3t7e3P5aIuP9smRogzRqiGgaOQUMB0Xc+N5eDX31PrVXmkecyRI+4NrI6Y4IIy7cIC5dzWCpyq1WGes/uDdGzDo6g/pgg6vquGgGC3bXK1IrOENVyMrHOmCBKbOPdrhmiu9ZM54Yh0mZpiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGMAgihOHPOD1A0P7oPIiYLuJJPPbbLLoxrmNnp81r0Eyk7YrVVQ4YIpWzv3QNkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxzBai3W7XLBaLzg/uTWkzRNo0DVEHSIZIO+impj5biMogz+dzs1wu2w+Op7SpZiJ6xhn9/f29Wa1Wzel0apTLtlkAABekSURBVHgPx9xwDI+jv4fDoa1zuVzaYnGFAC1objab5nq9UqapVeYm+OSBIfptIIOZ2iyEx1NAREgAATYMcgx2AAVYeB79xPGPHz8a1kE9XOM5jgEOgYIO9CJEtcq0na70jyFqmjZ0hFW+JSt5/HIZBUQYzHFw4yEJFmcfwMEygAp1jsdju0d5wPLVzIUysZ1Sn8YOLcN6tfazh4hvTECEMKa41YaInnEGoWflIMf5er1uYcHxdrttPj4+WrAAEGDjzBOPqYd9BKRWmahf43j2ECGYKc9CGCSvgoiwwWMAR+gABq/xxVULkD46NcCJGrOGiCFPeRZSQATNOENwQJUzEcvt9/t2FsJ9bIAJ17DUw6DH1lUX12M7tcq0DVb8Z9YQIcypz0IYK7VnImhi8MM7zi7xhUQwWA6wAAaUwQYY8AMDl3q4xvpc3rEu2ojfq3D8bJm2ExX/mS1EfKtNfRbCWFFAFAc5X0T40eDt7e3TT9j88YCwoR6B4VKO45nXocdcUCaWq1WGbdbYzxaiGuaNRUMFUfn8eDHF2aW8/8g5AIoAdmnUKtOl3eeaIerj0sjLKCDCjMC/58AezhBx1hhqG/Sgww3LwvLPDrXKsI0ae0NUw8XkGgqI4nI4Lr+esQIAUgv7EiBo1yrzTD/LuoaodGSC5wqIJmjTw49kiB62bjwVDZE2K0Ok9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNoZBECEMf8bpAYL2R+dBxHQRT+Kx32bRjXEdOzttXoNmIm1XrK5ywBCpnP2la4i0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjWHWEJ3P52a5XDaLxaL94BjXprYZIm2is4XodDrd4CFE2E8RJENkiCQO7Ha7FqLNZtNcr9fmcrk0q9WqvXY4HCRtvkpUARH9w4sHvr2/vzf0ks/5VRnci+WRAc5xnRszYR7lygFtom28EHkPx9xwXL4UoYU60K61zXYmgpkcADCUgeFaDKKW0a/UqQ0RBnociPALvkUo/lamHOCA4MePH816vb4NcFzjOSEhUISOefE8QohjaLIOMsC1eF4jl9lCFKFBEPzUNrhGSM9q1ISIg7l80WBwEqI+Zeg/dbDf7/fNdru9fS9FFtSM+vSjbCeWB1Soczweb7Nb2SZ1nt0bogAQQCqn/2cNzlC/JkQY7HEW4vPFQd6nDOqhDl9aOEY9nOPDmaU8ZnvYlxDhPM5cAPLj46MFEQDd61fUfOR4lhAxIECD8LDxLYVrfPs9YmjGOlkhwqCG13GgAwQOfgCBc+ZF4OhxCRHLRRhRNgLKvKlRYz9LiCIw0VQcG6Kvh1U5cFka3vHl06cM6qEcQCmXXNDBNeqhbNRnm13toFzXshDXoAfAam+zhIihAJiuT/nGq236d+vVnIn4to9LOgzM+PLpUwYeoBxmHXzi4AYI5Q8CbIPZsA20G+viGLBAA2WwAbbyR4uaGcwWIpiIQEqIYiA1jX6lVk2I8BxxAMM/DFh++Jx9yqAsMohA4hoy6PpuiuvMC/cxW729vbWQsF2uMggbrrMv6KNimzVECkMzataGqOsZMUDjwH20TFe9e9e4HAQ4r9wM0Svd/6a2a0OEQculEh6ha+boU2bI46O9CIt6dhnSN0M0xK2Rlq0NEWYdLquw71p69SkzxE7+iBDbVS3PhvQLZQ3RUMdGWL42RCO0QNplQyS1N4e4IdLmYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxjAIIoThzzg9QND+6DyImC7iSTz22yy6Ma5jZ6fNa9BMpO2K1VUOGCKVs790DZHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0McwaovP53CyXy2axWLSf1WrVXC4XreMvUDdEWtNnC9HpdLrBQ4iwnyJIhsgQVXfger02m82mhWi327X6mIEAEEA6HA7V23ylYA2IOGvj5cMNx5jJcY8bvIOP//rXv9p7fcv/85//vKsVVwfIC9khQ2w450sQ7b6/v3+637cM+//IfpYzUQQmhsxAYkiPmJqtTg2I+OLhSwfPiOMfP358eungGkAaWp6Z8AWG+tvttnl7e2uYETV5jrbiygHXAVTMr0+ZZ/OaPUQwGRsDKkN41uAM9WtAhOfAAOcAhV/w7ng8tnvcJwgc5EPLQ495QAvH+/3+BilmPECFfdfMiD6gDvvYp0yNfGYJEQcElwHlnkHWMDiDRi2IMCjX63ULC44xU3x8fLSDFoMe8MSZYWh51CcAOEYObAfQRijLtuhzhKhPGdZ7Zj9biGAaQiFACB8B4hzXp7TVgoizNQYnPKJPGLi8Fl9AQ8sDREAKcKgJDcDKa2yzDyB9ytTIedYQRQMRGgCKb9J4f8zHtSCCB/AJSywObFzDwMY1vIQwcOM2pDyhwxIRWoAKGzRwjYDhGqDCjxpd7XE261Mm9vXR49lChIAADGci7Mtfmh41NVu9mhBh0GKQYmBj0GPDYMUPDFzqxecfWh5AAlD8ysYNGvguhOtsk8DFlx7KIUdC1KcM23hmb4h+/6GVy4RnzMxatyZEfPlEvzhYAVa5DS3fNXt0aaAdtssXIdrnh/3oU4ZlH93PFqJHDRtjvZoQZX9+QBQB7+pvnzJd9e5dM0T3nJnQ9alChBkKMw03LOfKJXmfMqz/6N4QPerciOpNFSLMKFzK3ftO26fMs1EaomcdHEH9qUKUxXpDlCUJYT8MkdDcpmn/X9ljC/5/D49uTOTYEGmD9Eyk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MQyCCGH4M04PELQ/Og8ipv4v5UU3JnLsmUgb5KCZSNsVq6scMEQqZ3/pGiKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpY5gdRLvdrlksFu3ncDj84S6u8T72XWX+qJT8giHSBjQbiE6n0yc4ugApASJMYwfJEBmiKg5cLpdms9k0Hx8f7b6ECPdXq9WnGYqzFq7j/lg3FUTn87lZLpe3l9P7+3vrIV5Y3MqX136/b97e3hrU5fZsGdRHP6ImXnxlbsgTY+B6vbLpKvvZzER0CwbCyBIiBhmN5yApA6LWWPYKiOgNZ+noK7zERk95zhdV9LNGGerGvmy32xZWts3+8bxmdobot5sIAGB1QYTrCvNrBvmVlgKirrc6wYJXHLQoFzfcI0S1ykAf7bAtQIVjzHoEC30rZ8DYr2eODdFv9wxR/2HEwc8BypoRIs4O5csnQlSrDNqHLpdqOAZE6A9mJPQXfeV99rfW3hD9dhLG35uJ+OasZfp369SeiTJCBCDX63ULDgBCnugnIAJMuFZCXysHQ/TbSb5F43clGF+CVcv479SpDRH6Dm/KNzs95ADGfZSLG+7xpUQYny0DfWodj8e2X4AKG7RxjYDFvtQ6NkTBSS7pAE78qN5goWnpoQIiztz0hoMYvuEeNvrJcy7fCFHNMtTCzINfCbmhbXwX4rKO12vuDVHhJoMnRBwARbFRnSogggHwhj4BDLzxyy/v0U/8aIMy8ccb6NQqE2dCBkRw0YZqmx1EKiMz66ogKp8ZgxjLJi6lyvs4B3jlMrAsV6tMqas6N0QqZxPpKiDC8i3CwuVc/H5TlumaFWqVeaXdhuiV7n9T2wqIuHTicg77CBAeLS73WK5cVtUq801WdjZjiDptmdZFBUTTcui5pzFEz/k3itqGSBuTIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbwyCIEIY/4/QAQfuj8yBiuogn8dhvs+jGuI6dnTavQTORtitWVzlgiFTO/tI1RFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGMDuIdrtds1gs2s/hcPjD3cvl0qxWq/b+crlszufzH2XGdsEQaRObDUSn0+kGzz2IImAoY4i0g28q6rOBCDPMZrNpPj4+2j0gKWcigAaQMPsAIEP05zCHP/Dxer22N7HHOa5z42xOf1mGLy+U3263n+p8VYZ5IB9uOC7zQXtYRaB9bOWLc7/fN29vb9VXF7OBiObHsBgy73HP0MqQeH9s+5rLuXLwwqsfP3406/X6Nnhxjef0O4IH3wEUwftbGd5nefiPY7QbM8Q1nhMg7LERbEWmhqiDCEPUYcrvSxyMHJzY4w2PmQW+YcNAJjS4Xw7cEoo+ZaIm6gOY4/F4AzH2q9Tn03S1w3vP7A1Rh3uGqMOUcCm+8XGMwYlBjg8HMI6xxcFPCZZB3b5l4uyGY0DLpTkAQh+4lItAsU3sDVF044ljBtj1nYiyhohOdO8xGDHTxEEcBzaWcjjHVgsi5haBhX6EmFAaou7cql1lGIbocUsBCEApl1MAC9e4lEMLXW9/ZsBB36cMtFC+a+mIa2gTOthK/fbinb7w3jN7L+c63PNM1GFKuIRBiuUUPhy4uI1BXn7Z56wQwcLsFH9Y6FMG+mgLOmgHfcCGrMofNnCdbbB/bKP8ftaKPPmPIeow0BB1mFJcwiDldxDewoDtGqQcwAAHH84c0OA2pEysd2/WgS5BQpvoK2bJss9s/5n97CB6xqyx1q35E3cNDzjwOUt0afYp01Xvq2ucyTiLfVV2yD1DNMStkZZ9NUQ/f/785FzXLNanzCeRv5wAFMxu3DjTxVmM957dG6JnHRxB/VdCxBmFSzkureIA71NmqM2YdWKbOFYAhH4ZoqHpjLD8KyEaoV2Du2yIBls2vgqGSJuZIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbwyCIEIY/4/QAQfuj8yBiuogn8dhvs+jGuI6dnTavQTORtitWVzlgiFTO/tI1RFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxGCKtvynUDZE2BkOk9TeFuiHSxmCItP6mUDdE2hgMkdbfFOqGSBuDIdL6m0LdEGljMERaf1OoGyJtDIZI628KdUOkjcEQaf1NoW6ItDEYIq2/KdQNkTYGQ6T1N4W6IdLGMDuIdrtds1gs2s/hcPjk7vl8bpbL5e0+yp1Op09lxnhiiLSpzQYiwEB4uI8QdQHUVU4bh0bdEGl8pepsILpcLs1ms2k+Pj7aPQCJEMGQf/zjHw3KYbter7dyqIfzsW4qiMoXz/v7e7NarT7N3n3KlC+4/X7fvL29NaiLe1gd4JgbckM7zArXscKIOcUVB8qib/E+tWrsZwMRzYpwlBCxDPcMQmU+21HvFRARDnoYfeUSuE8ZAsQ6AAODnuDwPLaz3W5byFiHbfMcuUXI2IYqR0N0ZwQzvK4Z606VtJcVEJVvfjw8oYmDuRy4sQwHP7TihvqECNdxn2WQC44xWxEsaHLmivpRE3XKvsT7zxwbog73GC4Aim+0jqKjuFQbIvrDQUwT4gDuU4YvKkJHnRIinBMAHAMItIUZCe2gH/F+V2aGiO5W2DPcezMMg50KQLBs7BAhk/V63YIDGAAScgREgAnXCDTuGaIKoHwl8RVEfJMCIL7ZvtIay73aEOG5u97s9A8DuU8ZZgGtuKF+XM6x3PF4bHMBVNTHNQKGa2UfqNvVX957du/l3G8HERzg6fp0vdmeNf476ysgol+cATjQ4R8h6lMG9WMdrgQiRPAK5TDz4Fc2btDHdyEu63Cd/YiZsR+qF6Mh+p0IjTZEHKJ/30fPMOgxK/ALPmv3KUOQ4D0GP3QiBNDqmmEIHEFmmwSJWWIW4odlau5nB1FN88aipZiJup4dAx1LKy63Hi0D8GrPGoCohK2rf49cM0SPuDayOgqI8LaPsPDtj8HK7ZEy92YXavbZQwNtcwOU5fKQ92rsDVENF5NrKCDi8opLJuwjQLCkT5m43KPWszMG+kEt7JUA4TkNUXIAanRPAVGNfk1FwxBNJckvnsMQfWFOhVuGqIKJ2SUMkTYhQ6T1N4W6IdLGYIi0/qZQN0TaGAyR1t8U6oZIG4Mh0vqbQt0QaWMwRFp/U6gbIm0Mhkjrbwp1Q6SNwRBp/U2hboi0MRgirb8p1A2RNgZDpPU3hboh0sZgiLT+plA3RNoYDJHW3xTqhkgbgyHS+ptC3RBpYzBEWn9TqBsibQyGSOtvCnVDpI3BEGn9TaFuiLQxDIIIYfgzTg8QtD86DyKmi3jiYztgB4Y7YIiGe+YaduCTA4bokx0+sQPDHTBEwz1zDTvwyQFD9MkOn9iB4Q4YouGeuYYd+OSAIfpkh0/swHAHDNFwz1zDDnxywBB9ssMndmC4A4ZouGeuYQc+OWCIPtnhEzsw3IH/D1+5urXr/JMoAAAAAElFTkSuQmCC[/img][br][br]How many successful trials were there? Describe how you determined if a trial was a success.

Based on this simulation, estimate the probability that [i]exactly[/i] two kittens will be chocolate brown.

Write and answer another question Priya could answer using this simulation.

How could Priya increase the accuracy of the simulation?

A team has a 75% chance to win each of the 3 games they will play this week. Clare simulates the week of games by putting 4 pieces of paper in a bag, 3 labeled “win” and 1 labeled “lose.” She draws a paper, writes down the result, then replaces the paper and repeats the process two more times. Clare gets the result: win, win, lose. What can Clare do to estimate the probability the team will win at least 2 games?

List the sample space for selecting a letter a random from the word “PINEAPPLE.”

A letter is randomly selected from the word “PINEAPPLE.” Which is more likely, selecting “E” or selecting “P?” Explain your reasoning.

Is there a proportional relationship between the perimeter and side length? Explain how you know.