IM Alg1.1.4 Lesson: The Shape of Distributions

Which one doesn’t belong?
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[/img][/td][td][img]data:image/png;base64,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[/img][/td][/tr][tr][td][img]data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAWAAAABWCAYAAADxNUxIAAATkklEQVR4Ae2dBcwcRRiGGyRIkGIBgrQ4IYTiEiC4FXd3aSE4JEhwL+7uDiHBXUqgaEhK0SLBoTgEtzLkufQ7Zuff3X/3dqb/9c87yWX3dme/d+aZme92Z2fmBjgFERABERCBPiEwoE9UJSoCIiACIuDkgFUJREAERKCPCMgB9xF4yYqACIiAHLDqgAiIgAj0EQE54D4CL1kREAERkANWHRABERCBPiIgB9xH4CUrAiIgAr064JtvvtkNGDAg8xkyZIgbO3as6ImACIiACDQgUOiAv/32W7feeuu1Puz7ge+//fabf0j7IiACIiACNQnkOmBzvsOGDZOjrQlU0UVABESgKoFcB0y3g7oZqiJUPBEQARHojEAPB0zXAne+uvvtDKiuEgEREIGqBHo4YOt+OOmkk6raUDwREAEREIEOCMgBdwBNl4iACIhADAI9HLC6IGJglQ0REAER6J1ADwfMJXQ/6CVc7/AUQwREQASaEMh1wEyywAGrH7gJWl0rAiIgAuUEch0wl4waNao1+43JGEUTMWyWHFsFERABERCBegQKHbCZ4S64aCqyHLBR0lYEREAE6hPo1QHXN6krREAEREAEqhCQA65CSXFEQAREIAEBOeAEUGVSBERABKoQkAOuQklxREAERCABATngBFBlUgREQASqEJADrkJJcURABEQgAYGud8C33367m3vuud3QoUPdp59+mgCBc6eddpqbfvrpWyvAJRFwzg0fPtxNN9107tRTT00i8fnnn7sNN9zQzTXXXO7WW29NovH000+7hRde2K200kru5ZdfTqJxzTXXuNlnn91tueWW7scff0yiccwxx7ipp57aHXzwwUnsY3SXXXZxM800kzv//POTaLzzzjturbXWcoMHD3b33XdfEo0HHnjAzTfffG6NNdZwb731VhKNCy+80M0888xup512cv/8808SjcMOO8xNNdVU7uijj05iv4nRrnbAb7zxRmYMMhUudrCxzDbWmcKKHQ4//PBMPm688cbYEm6dddbJaLz22mtRNVgjxBixXXDBBaPax5hN/jGdLbbYIrrGJZdcksnHiSeeGF1jr732ymikcJDLL798RuOTTz6Jmg9+0K0c2C699NJR7WPswQcfzGjsvvvu0TW4ufLzccEFF0TXaGKwqx0wjsqHN9lkk7lff/21SX57XHvggQdmNKjYscMKK6yQ0dh///2jSvz+++9uiimmyGhcf/31UTWee+65jH3K5fXXX4+qQePwy3uWWWaJah9j3Jn6Gsz0jB14SvA1jj322KgSX3zxRcY+Wvfee29UDe5+/TywH/sJlB8/X2OBBRaImgeM8VToa+ywww7RNZoY7GoHTMbWXXfdNsAzzzyzSV5zr+XOgcc4KyR+lWOHhx56qG1/3nnndR999FFsCXfWWWe1NdZee+3o9jG4xx57tDUOOOCAJBp0b1hZXHbZZdE1eKqaddZZ2xrPPPNMdA26zSwPiy22mPvhhx+ia+DUTSPFkwIJ3mqrrdoaKR7ff/75Z7fEEku0NW655ZbonJ5//vm2fbo6xowZE12jicGud8BkjsfGhx9+uEk+S69lrYuTTz7ZjR49ujRek5MUPNO6v/766yZmSq995JFH3MUXX1wap+lJnkpwMCnDueee60aOHJlMgju54447Luk/e7/44ovujDPOcL/88kuyfHDXe+WVVyazj+Grr77a3X333ck06NoaMWKEe+GFF5JpvPvuu44frI8//jiZRqeGJwkH3GnmdJ0IiIAIdDMBOeCJWDr//vvvRFSTVBmBVG/cyzR1ru8IdGt5d70DZkjVnHPO6dZff/1kjxCnnHKKm3baaR1vr1OFvffe200zzTStro4UGjxWb7DBBi1WqZYHfeqpp1qjH3hRySN2inDVVVe1+mg333xz9/3336eQaA1HmnLKKR0vYFOE8ePHt4ZVzTDDDI7ulBTh7bffdquvvrrjncI999yTQqI1vG3QoEFutdVWc/SdpwgM0xs4cKDj5dhff/2VQqI13JCX1EceeWQS+02MdrUD5i27vWhgu+aaazbJa+61N910U0bjkEMOyY3X5CBD2/x83HDDDU3M5V7LizdfI/bLBvoyffvzzz9/bjqaHHz22WczGjjh2IE+cj8fJ5xwQmwJt+eee2Y0Yo9QIMHLLrtsRiN2/+Znn32Wsb/UUktF5xSOtNhtt92ia3Bz5Zd3qnHZnSa8qx1w3jA0Ou1jhoMOOihTQAwZix1WXHHFjEbsEQR//PFHj2FosZ28/zbZKnTsuyIG5ZtttimGoe26664ZjRTD0BZZZJGMBi/8YoZx48Zl7MMqtpMPnSMasYehhWuNpxhbvtFGG2VY7bjjjjGLorGtrnbA5I4GYo2SoVaxA5WK2T6mwZCx2IERHGafIW+xB82T3rPPPrutwdC9FMG/s+OHK0VYeeWV2/m44ooroku8+eabbrbZZmtrcNcdO9xxxx1t+4svvniSGX04datTzBpMEbbeeuu2BrMHY4dwGFqKGZyMrjBO/KDHnqDUlEnXO2AyeOmllzqGWKUK3333neNRJfZju59eCp6hbuHfO/lxmu4/+uijrSF7Te2UXU+XDQ4mZeAxkWnPqQKP18cff7xjOm+qwFRthlfFnjjkp5cZdvSZpwxMDU/Vx0y6mUTE+P5U7xTQeO+991rDDlPc+DRlP0k44KaZ1PUiIAIi0I0E5IAnlMrEGCLG23GF7iDw999/d0dClIqJQqBby7vrHTBDquaYY45WX3CKKbyUPl0DDBGjjzNVYIgbK3Dx4iFF4C04Q/VYSYxughThySefdIx+WG655ZLNXKLfl766zTbbzNE1lCIcddRRrZeWsdfksLQy5pRhVaywR998ikBfNsPDWCkw1Uw1XuzNM888btVVV42+7ocxOe+88xzD9bbbbjv3559/2uGoW95XTD755O6II46IajeGsa52wPSbWgc6W5bFix0YLeBrpFiikKFtvkbshXJgwhA9X+PVV1+NiiochsaLy9iBdRn8POCEY4dwpAV9wbGDv2YG+UnRh7rMMstkWMW+OeHltF8WSy65ZGxM7v77789oMEIlduDmys8HDr+bQlc74HCMLr9idNrHDDhcv4AYMhY7+AvMoBV7AgDD0JhY4Ocj9jA0/22y6XAXFjNcdNFFmTywaE7swFhTSz9bnhpih0UXXTSjEdvJf/nllxn75CP2kpfhUpFo8PIyZgid40ILLRTTfMvWxhtvnGHFusPdFLraAQOK2V3WYM4555zo7KhULINnGikW/WEEh9nnET72eEqgMOPKNFI4FTSYzWcaKZ4U0OBx1zRSLDTDDDK6aUyDZTZjhzvvvLNtn9W+fvrpp9gSjgkklgeGi6UI2267bVsj9pKapJcRItxZWz5SLPLE6Aqzz/DD2GPXm3LvegdMBi+//HL3+OOPN81r4fUsF3j66acnLRwKnsWhU02vJXNPPPFEi1VhRiOcYKzmXXfdFcFSsQm6CVKMzzVF1tOlL/7999+3Q9G3r7zySqv/N/YTm59QJktce+21/qHo+9ddd12rqyC64QkG6fflxirVP6wg88EHHzjWHmaR+W4LjR0wM9Niz04LIfUHjf6QB8qlP+Uj1doD/Y3TpN6+eSnarXlo7ID55Uo5aJ7KzNvYlIPm0eAuO8WjIrYJzPpJscD4BPOtDeuepnjh42vwoizloHm0eBRNPWieyR4pHfA333zjuHtMGXhJnXKCEml/7LHHXOwXuiET3ld89dVX4eFo33HAqRZFskTSrXjbbbfZ18pbOeAJqOSAq9UZOeBqnOSAq3EilhxwdVY9YuoOuAeS3AO6A87FkntQd8C5WHoc1B1wDyS5ByapO2D+l+nQQw+t/GHA+TbbbFM5fh3bFnfTTTd1/GOqfU+xZTlHBuansI1NbPOvzqnsYxdGm2yySVINynr77bdPqsEfKTLiIiUr1tJlgH4qjX333bc1eSiVfezyB6P8H1xKDRb62XnnnZNqMGpn+PDhyTQYscOklZScqK9Dhw6trdGjCwIHjLOo+mEIDOu2Vo3fSTwaJOP3Orm26jU0yH322SeZxrBhw1oLaFdNTyfxYEQl6OTaqtfQ4PmzxqrxO4nHCngMyu/k2qrXMNwNJ1k1ft14zKrkB7fudXXi80PID26da+rGxT6z1OpeVyc+Nz9MXqlzTZ24++23n1tllVWS2SctjC9nFcI66SJuDwecew9fclBdECVwvFPqgvBg9LKrLoheAE04rS6IapwmqS6Ialn6P5Yc8P8syvbkgMvoZM/JAWd5FH2TAy4ikz0uB5zlUfubhqFVQ6ZhaNU4EUvD0Kqx0jC0apz6bBgai7TwSRn6g0Z/yANl3J/ykXIccH/iRF5ShtSsuAPu1jw07gNOWTCyLQIiIAL9mYAccH8uXeVNBESgqwnIAXd18ShxIiAC/ZmAHHB/Ll3lTQREoKsJdOSAR44c2ZpZwuySIUOGuNGjR7czydKO/JNB00WoWbke+/bBLsHsc5wZcna8nYCaOyyYMnDgwMxV5Md0mRDQVAMW2PMDurDjeFMNY+IzZ9/WQbWtf95PS5X9Dz/8sLV2K2XvB1hRDuSj6V/VYzssC+qBpZ9tkzyQbriHZWH5IS9oNA1w8DVgR5vgGGXedC1lypuJQz4L0u5rNF0ICHus1RuWd1E96IQZf6UUlrflDVYx2rely9pbDP5mM9xS7tivo9FRbaMQzClRUFbZOIY4jcavHGFCq3zHrgXgmT229rcixKGQOg3YAtqMM86YMTFo0KB2/prmhfTlNXo4WSANnTYYmMO/t3QSh3LrJFgZ80PhN0grb6sLndi2a2iM2Pe5cI4y8jUtfidbOGPP6qtvwzjmnfPj9bbP9eTDt4Ntnz3nOs0TdkyDvFjguGmgF9Zpi1dlS9rQgJefTtOmTvvHq9gM41DfQ07E8esYdZo0NA2k269XMdIfpgkepN0Cer4Ps+PhtiMH7BuximvH+E5i/Mph5zrd0jjNHhUDDQs4y06D2QnvetDwQ/jdP9fbvmmENnwn37RCUMHKmDf9oSKP5IMy8BseDaTTH46QWxGnUDO8rs73Ig1smLMJy6mOfeKiAaMyO1UbZ5G2lYW1ibx4MdpFHnvT9utBnn5vx+zHIuQUtkXfcfZms+h82Db4HsOx+3r24wQfPqTb8ujHC/cbO2AKKWyEYYZD0brfKSTLTPjLHhZgXdvEDwvdd47kLYZGaAOnSF54zAv5dZKHMub+XUUntu2asEFSibHNDwgVDofcNISc0MA+x3nErnJX0VsaQg1+4K1Bhud6s5V3nrII7VB/6XqIVd6UBZ+84Ocn73zVY2F523VFx+18nW3IKfwets06ti2uOUf7bnXKvsfaUv8HDx7cKuOq9bSSA+avT0aMGNH6jB07tp1eHId/220nypyBxQm3Zp+tH7DvO6jwlz0sMP/acL9IIyxk4GGXggJqVY3x48e3OTHTyg+hDb6TLz517ojGjBnT1vD/pqmIOZWv7l0EfztkrMaNG9fORtjwyIPvdOvkw+yH5R1yaos713K+Zef9uOxX0eBuxbfp74f2wu9caxr+XwPlOWDichzniEbVBjpq1Ki2xksvvdROAmXBJwxWd9GrGlgL2/LhT1gIy9vsFR2383lbs8/WDyHvsK6GbdO/tmw/1KOd8UOOP6HO5rErsxee46/FTAPb1s4oX/MZVcqgkgNmEW77mANGNM/5ktAiZxBmwv9u9tlaCJ0vxykwMmshLDA7nrfN0yBeWSHXuZvAARdp+BUNPnbHhT4aRSzDfOCA8zSKmOcxDG2G3337ZQ44bIjkiXRUCb6GH9/n5B+3/fAJyI7nbatokAfuWnipxYeXQmyrOEgaWJ4GDMrygWZVB4ADNo3eHHAnzhduZp9tKgfsa/hlFXLyyxe+4Xn/2rL9Ij2uoZ7iv5oEHLCvQXn6Nvnu35wUaVVywOHFZc6XuEXOILRT9r3IcaBtlbe3dJTZ988VOWB7dPEdvn9dnX2/IllDsespqCqFZfHztnnMqcB1fqDy7PrH4O47WPa5qyCYFtsmweeEHZ99rPIONfz0lp3z45Xtw8W3Qx6MC1u6UnyOZbaKzlEW1g6IY3XKdIquq3M8LG+7tui4na+z9TlxnT11sk+b8PNYx25R3LBsiuLVPU5aWZLSAu2iShl35ICBBDj/498xsE9jaRJ827Zv9igUjuGkY1Q4bPmBtNvjip8vP07dfZj5wR5F0YlRyfKY2+OQr9tkHy4hD45Z+VSpcL3ph5yo2GafczHKO9Tw01R2zo9Xtg8j3441estH07aBNjZ8O+iZfduGZVWW5rxz2M+zUXQ8z0Zvx3xOFtfyknfO4tTdms1YPiNPn3ZMe4Z/1TbdkQPOE9cxERABERCBegTkgOvxUmwREAERiEZADjgaShkSAREQgXoE5IDr8VJsERABEYhGQA44GkoZEgEREIF6BOSA6/FSbBEQARGIRkAOOBpKGRIBERCBegTkgOvxUmwREAERiEZADjgaShkSAREQgXoE5IDr8VJsERABEYhGQA44GkoZEgEREIF6BOSA6/FSbBEQARGIRkAOOBpKGRIBERCBegTkgOvxUmwREAERiEZADjgaShkSAREQgXoE5IDr8VJsERABEYhGQA44GkoZEgEREIF6BOSA6/FSbBEQARGIRkAOOBpKGRIBERCBegT+A5FnCPKqGq3+AAAAAElFTkSuQmCC[/img][/td][td][img]data:image/png;base64,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[/img][/td][/tr][/table]
Take turns with your partner matching 2 different data displays that represent the distribution of the same set of data.
[size=150]Use the applets below. [/size][br]For each set that you find, explain to your partner how you know it’s a match.[br]For each set that your partner finds, listen carefully to their explanation. If you disagree, discuss your thinking and work to reach an agreement.[br]
Press the Previous and Next buttons to look at the different dot plots and histograms. You can enter a number into the input boxes to reference certain dot plots and histograms.
When finished with all ten matches, describe the shape of each distribution.
Your teacher will assign you some of the matched distributions.
Using the information provided in the data displays, make an educated guess about the survey question that produced this data. Be prepared to share your reasoning.
This distribution shows the length in inches of fish caught and released from a nearby lake.
[img]data:image/png;base64,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[/img][br]Describe the shape of the distribution.
Make an educated guess about what could cause the distribution to have this shape.
Close

Information: IM Alg1.1.4 Lesson: The Shape of Distributions