Exam 1

  1. Question

    The following figure shows a scatterplot. Which of the following statements are correct?
    data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAH0CAMAAADWjqPmAAADAFBMVEUAAAABAQECAgIDAwMEBAQFBQUGBgYHBwcICAgJCQkKCgoLCwsMDAwNDQ0ODg4PDw8QEBARERESEhITExMUFBQVFRUWFhYXFxcYGBgZGRkaGhobGxscHBwdHR0eHh4fHx8gICAhISEiIiIjIyMkJCQlJSUmJiYnJycoKCgpKSkqKiorKyssLCwtLS0uLi4vLy8wMDAxMTEyMjIzMzM0NDQ1NTU2NjY3Nzc4ODg5OTk6Ojo7Ozs8PDw9PT0+Pj4/Pz9AQEBBQUFCQkJDQ0NERERFRUVGRkZHR0dISEhJSUlKSkpLS0tMTExNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1eXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2tsbGxtbW1ubm5vb29wcHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+AgICBgYGCgoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OUlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSlpaWmpqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCxsbGysrKzs7O0tLS1tbW2tra3t7e4uLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fIyMjJycnKysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7////isF19AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAgAElEQVR4nO2dBVwUyx/A9+64o47jgkZAukTKAEUpsbEVu8Uu9NmFjd2t2N357I6/9exu7EAxkLz57+6JItyROxfc7/v5vJ292bnZOfy+2925mfkRCAAwQKi6AUDJBMQCsABiAVgAsQAsgFgAFkAsAAsgFoAFEAvAAogFYAHEArAAYgFYALEALIBYABZALAALIBaABRALwAKIBWABxAKwAGIBWACxACyAWAAWQCwACyAWgAUQC8ACiAVgAcQCsABiAVgAsQAsgFgAFkAsAAsgFoAFEAvAAogFYAHEArAAYgFYALEALIBYABZALAALIBaABRALwAKIBWABxAKwAGIBWACxACyAWAAWQCwACyAWgAUQC8ACiAVgAcQCsABiAVgAsQAsgFgAFkAsAAsgFoAFEAvAAogFYAHEArAAYgFYALEALIBYABZALAALIBaABRALwAKIBWABxAKwAGIBWACxACyAWAAWQCwACyAWgAUQC8ACiAVgAcQCsABiAVgAsQAsgFgAFkAsAAsgFoAFEAvAAvNiXRoMlFSGXsUnljQVoZ/bll6UKiowPFDVHx/AReBwXGL97G2k1/ybH0EQ9ZMViVXwkwMaRiH+bQsp1hh254nO3paHXqw0jC3+yQENA59YTv8gdJqYR+6N8Cz+yQENA59YepsQ+kIcI/c26Rf/5ICGgU8s5xHk7fuWD+TeOPvinxzQMPCJNVJ3+Gkq/bzRuEfxTw5oGPjE+tmTU5lKvYmwj8U/OaDOPJo/PD7p7yx8YpFqPaW223P2YyUezqJpr8JWCagj40Xthtex2P9XHkax0nZM3JRK7Vyd+Vf+Jv8s+O6FrBJQR7Y4Pie3h0Uvs2fiE+uTP0EQbs/IvZmK3lm5cuGqBNSSiLV00mFy9kx8YvUQ7P6639wvFcQq6djfopM5nbJn4hOr9Dhyc5k7A8Qq6XifoJNRMdkz8YllsIHaDhB9ALFKOENbUtvvDkeyZ+ITy6sttU2yqZEJYpVsPrs1OZ+w26fVX5n4xFpK1F6YhNBRndrtQKySzfdhXpKAlX/3KuETK3OBFXGTTA/ZEiCW9oGzgxR9+kltM06tUHAcxCq5YBUrP0CskguIBWABxAKwAGIBWACxACyAWAAWQCwACyAWgAUQC8ACiAXkx+Olk3enFfZNIBaQN9Lh4uZ9Krj/V8i3gVhA3izyekVuF5f6Xri3gVhA3ngdppOw9YV7G4gF5A0vkU4Gjyrc20AsIG8kT+iky1RFBS6P6TrtTa5cEAvImxYjqe0ns+vyD0v7mg2Y2Va8MWc+iAXkzWPz/vc/7ivTU8HheK9P5Pai8EmOfBALyIfXHUrp+a1VtN5n1W10Ej0hRz6IBRQL27t0MrtzjnwQCygWvsfoZPDgHPkgFlAsxjSgLpIfrc/lyAexgGLxrVz4nqsrHPrmzAextASFi+0Xl7Tpoa519+XKBrG0gm3ldMWN7yvzjCCWNjDaaeeX5xNEl5V4ShBLC0gQJlDJwmAlnhPE0gJW16OTHzo/lXdOEEsLWNhWlup9Ut45QSwt4Lg7/Ux4zRzbo2FuQCwtIMN7VAZC7yuNU+I5QSxt4Emge9coSZ8Meceur9n+GsMpQSytQHp01jK53Vhv61o1jhCNZv4aCWJpNdKgnuST4jPfaYzXrILIFH8AsVTNeXv68njZivGvLIhModUsbSlLDT4wXTNEptBq1tSnk1TuN6ZrhsgUWs0T/vhVTxFaV47xmiEyhTZz189EHCIatEhynPGqITKFFpPiOC1jmQOP5XSR+bohMoUWsz2A2n497IahbohMocVMlA0oTmbL7ZIvHiqITPH2d+hezwqFrhJgkNnt6OS1IYa6VdBBurNaFkII3atSbpnS42gm18+jzOdDG28WpW7oINVmepU5+P3ZSMkdxSUWmFSKtKqZkCM3fU5Fi4D5eV5AoYNUm5Gu8uJKmj9VXGC9/XXy4fEf7/S/ctNCqh58fKBSRF5mQQdpSeT16CZdtxbs5z+5cmzrWKsv/TXms4faSn32/nV4cRAlWlqFVXnUCx2kJZAd4q6rpntV+0HtZ15af+KHwpKp8hatTY10n7t1uHgu+Wadr3ROn4l/FagnM2pJ0zzaAB2kJY8P4jPkNr0+tZzCzfIO9f2st8srlird48vjVVyeayD81BDqmeuh+B5C+u/onC5/D6upup9Odkbk0QjoIC15rJBNyrluTT7TWc3OROi4Sc6VFRDa4s3V1Zv5sKEORzf09t+H/GSrjvYg72Wqz6f2flhf+qtAh8l0Etstj0ZAB2nJY2wMnSSzMtGcRvTurMayI2mzqjpU30KXcdr7zniIyDrm+zHLFkbH/nq/5SM6mdYdoYvi+T/RjeAWf5/grBl1A3bT5G/d/gZC95Y8Fsvufe6aI9R5Nr17zYlOkgND995c794eoTfGz9FxP9RWiJI7siOc9NtkX2zb7wid9BxLbq4G8/iSSak5zrBQ1Ca2lWhZXo2Aocklj1dCukuzbU/ycia7aJ33pJO4WuR1EX11PCTtacQ1C6uIonQ+d4p0/O+of6Nqsza8zHp/XBh1S/9YLOve+pl74VqEXsyNmf9STv4fQKwSyDLx6H/Xh/okIrSxAqUSiulO51eW9RqM69XdpurXJ91Z15vr3za8Y/jtuKcXu2V90eRfb0+pVWbBrlESRQPKCwaIVRK50zWo/lzqaycjsMkzlDTa/AWd7S5bFWRpLfMjpTMQ8rDtyzvjWbMnGsifW+E4euyy+tfbpZvaRPS8UbwmgFglm68DjIx5DR7LXtSW9T/1q9b5mq133KtbXB7XkdPl50p+AHK/QN6bWdTptJWpE4NYJR3pq9+doFucqKmpV0W9K5p0dubr+hGtJrizvKx82g+9Kk5By4TcjXM8aqcwc1oQS5sYLuk9ta14TV/9twidG6ZXmsyaLp75Nbam9TL0RHjAFKG0iPEMnQrE0iZuTuwx/RWKMJkjRShBUpvKOlyOx+VuQ2hah9FUd9UpT2bOBGJpIa6by/p0ayKq20r2MjW1XbkTPztXNaU6Rl8JmTkHiKWFBO7PODBj5dPYPlkZGYtcOQaOz6ndswwNvgSxtJDJdEdpkv3RbHlpD0UPyCSj9mhmzgFiaSE/AkP2XF/jkiNKyTzJqL1L/EKSmTkHiKWNpM0Kca6ZayzNrR5hzdcwtToIiKXNXJg0eC1D/VY5AbG0l9Q21n1GhjhdxVI5iKW9jAin1phZWhrLIt0glkbxbHDdDuuZug2ykP3OHLCbofr+AsTSJNaL+m2Y5xPyPf+SBeA7hx5Sg6JnMFJdDkAsDeINHQ0no37OoJNFI1NXtoxfw3hGqssBiKVBLG5CJ//Z5lHmQRsXt3aPC1RdA2rsMXoszHsoaBEBsTSIUYPo5CtHcZF/RWOvXh4lOl6Q6h5adL94f5kV8ysmU4BYGsTCKDq5UUphiQxbesrfNmd5N/jpC2q5edQc/+R3xvtenqVqHme0ib8BsTSIl0LqOU7aLOZ3zuV5M07J9n5Orx8W8+KqA/1CailnnY/vgVXqCasZlxMtVEJTQSyNIl40dPfygICkXy+/R1l1jHas9p7cfelSe/2u/qIJAbIjPmdzv3l0vU0u79Frsx2S60poKoilUdzvHd5s2e91PDo1+o5Qavca5G7TAVTGMYmIngKYbCQnPE7Zk3VXkkm/UYMHKqGlIJbmkmRIfVehFJOHKOVXKMIg74GZ5J1Wr7pyils+8rqAqAnOK/NazIMpQCzN5bpsfjMK24PeCGS7raaU9x8xzDvwnZziFfeFUgMaOk+a0EMJjQOx1JI9AzrNTsqv0GNT6tkv7aL9koxUA5lKAfsytw0Zukvujz7zyk8JSUdXhdftDzHbWLmAWGrI9xpu42Y1tjydTzGp026ETrrace19LrXpSsm02yqPYXoZHaztS1czinaKZrKtigCx1JC+jaipgFutFS+YJuNf8awTwh7m8dLlxl1M7Ket6mByLM/yJwcGOLs0wPKbcy5ALPVDKpKtI1R5Z34lr1XjsAzCb6a1NgyaXpYj8l6kxKDP+QBiqR9fuNT2078h/+RX8oap5fQrcZLmVePrxYuaGU3zDc3vS05pgFjqR4bee4TmS6qaS8Ke5l2y6uzg+SffX+Acjq8tvIEaLM2ILPg/J2ZALDWk2RC0wf7GNdHrER7yFp/9TaL+dhHf36gNe3PdRq0RGjYcXXRUVhvzA8RSQ17YRTlP7sgzrzzRf0de5R6LTMeK6l/uzA50GTACofYz0Ed9ZbUxP0AsdeTbKJapYez1g3UlQ/MqlsxxcqxuQHAIk7ezW6Pn4gfoEnxjUYBYCjE0oXs8XarmVSid5b5ONGS5gMOpscpouOVElFFvmHKalz/4xKqYDQVFQCyFuFahtj/MbPIqtI8dyGk/MaSUcUWvKpa81jsW+QUzMxyeAfCJtdqDcK//CwVFQCyFtNKf8Q1dq1pPklehqTbdvIf2X/mZWKeXhh70rdGKsXnMxQfjpfCD3qR8SoBYCplVO4JnYBa3RxYF/O3S4Qse5iixvUtkRFXDYPLv3IiVof9B6S3MB5z3WMEgVpF5LTqR9gF99qMjQ6ySBFuxCctN2Y6n1HGftb49K9JA7KYXFP6SjyFGavHAKdbl+/kUALEUs9u0+dQB5t2oqX9XJFPN1v28Iig19c/h8RFUD1czjnDJ8fHiy207K6pGZajgqfD55izcyjNUZUnk4+yesf+j97qPtjuKXrXns9izM7OOetBD3TMr8QmWpGn5gEQVNVIxKgjde6BpFiYehaxSO4lYZIruGXlUdnR3bp+VJ3xFJ0312jUua+yPZfWF4gGhe9WfxuNK3+M7Lmxvpj/b+gJC9JOfGx3PK4FHrfaYEjYxz/erBAjdq/4sC+T7CO5lVJ2jX7730G7WOm5z0tHISOqqOIJHPyueUsNvfgjdq8Y8be/i0OwmSg+21OFvCw+IaiDqLOh2//upyg3Rj+Byy/eN0acX1EZvjVTcUDlA6F715YxoxJUbU8Q7UFo0lzDwNG2R5GseRh346XIQZa5sFtItphNd8KKTStspFwjdq65kLtXne436gU6Yp6Jb1tMtZ99BmUY6x+ljIwfIyjwQUct/SBsPUVkrFQKhe9UUaSMvoxfnGpb5ijzPIKn76omiht3s9Mzv0gend/1VaqbJpMPrKlf8qrp2KgJC96odr7cuO4/QHvcLLuSLxrHUtEH0P5OuK2IqGl8KHU//dhM1K6vw1Y6BDRaqXbc7gtC96sdEUY2WDlWf9piYaEh+4R+smG5+e2fbyg2jwsKH3m7O5RpUuY42mqjdT4O5gPFYquNUXTufmE85Mhd5kLdN6SPLtFqMmnVMQ1fchgX66RBsDrv8q2SXvt/miLz0/BzPqKS9hQLEUhnTrBbfPtvZ6unfua701ECpT6vu6FOY+6A6xn7VOE4vpJfseYELapJHXq0LrYVpaXZGAbFURYKQXtBxRNPV/gb23d//yk1jyazpMYRale9Ab8HwFI4Bdcf+Wcekzlz60GkfFbS20IBYqmJ5Yzp5o+O1/92t7tYvUeaO4eOOSHkfqdxPZZw9DSKGtRZNRc8Jg11UIHk7Gx/Zb65ny6qszYUAxFIV02SR5S8Qb6kkptMzP/8hA5xqhlFfS9fEOpXaNjVsu/Apel+HYIeLxkhv8lgCdktq2atRHVXY6gIDYimPxDWxK/+sL7Q9iE56GtLJLSuPNuTlMLVVXfGUT2kWbI/Z/U0aO2QiFBJtYLL2nFUZXZbho1IVXZOla8R3VdL6QgJiKY2tZnVjGkris14ml1pNbr/b0fNwpINZ3PKCmJ/oo8HFWvo6xKgM8iLpYHEZXbJNG8vR0a3MYbEqSB9V5zpYlZWzCqQaAmIpi9siyohrpheyMi6WjoiNKVWR+h05ozpbR98krgZ5kbO/hTKbmdAFlprsRyuaIdSXxSEIVhnHFSijgUVQ30cq+gCFA8RSFv1l8SQm/x6rh5LjY3r2HGAcT6rDsR3kd8ltkuBlhuAlQrX1fqbdvJt+inszrbXA0CO0kagaa9kioVNSgH2lnYNFa1T0CQoFiKUs6mymk8OBf7LSu5h3H+HP9e7GYY9ONjl/QxyyZ5Uvmd/FJczI0loSYJQRHsC/dd5WP3azeAzay45uXn82Qv+J3qjmExQKEEtZNF9EJ5tq/MmaGPSZ3C6TtLYzQ2iDZKale3PxrGF9lm43YvEc+AJWtTUV0geWPT2A1VCyVLzuX6Gwly31c3OTJSr5AIUDxFIW8YHUb8XSGtkmAJQeW1Hg1PdT5WCxbpdEdLWBDrtxmNPQybUsCGNTNpfLNW4+H2UuteMRgrPodBk9PhFKDxgdGKuij1AYQCxlkR4cdvr9hUj/P6uEphOeu97819nCwFOvHV94BW3jDOrbgOp492Gb+7tUacAzDqEHS37S5S48tznQ30kkCzDYaKlKPkDhALGURmpcGX23MdlWn/0fi+6RMjdd0Cdolpgj4dRPl/3M40isIrc/GnDayNb0C5U0LFtz0QKHfk2oge4XRW+V3vbCA2KpjljnEeT2iRH7cfoYgYeOYLb0ox59wJ41GT1tyBMQ4cZUF8VN03Cb/qNCnK59reK/YFN/0QaVtrqAgFhK5tO/62/82h3Yz7LrpcejuKRN2+s5CwZJUSqPuptH4VyXy6WGXRZwepqZRP7TWLwUnZ7wzxryIpm5um2dQc9U2PqCA2IpjWdnPyA0R1KlnlXNBDpjcYMPvdwtKuuVl7ZxjT8rdGmQgSLp2JQziBBdoYue0FTabNSq0cs1oXchFyCWkrhYTuLNbzjDNlhiHBzlRw8mTjSlurZeGTTb4f4dzfNJKbcSPbLsePzqDBNLe7YJt275WLQuUsXNLjIglnK4J16WiX4M0uHPev5mvJFgMH0Pf6Z06MC24h52Ni1XNrW+gVbWIzVr5+3a7PLTSgaVm5j0ykBbaqm64UUFxFIOHUdR2zSiC5L+I2nAcbSjRxcnbxy98AH64Whl7j0vAx0JTOym62zsQx6SNgleeo8sEK02y2sXFhBLOXidp7aPiJZoofc7JOm92ezz72MbdIN2Lg8q93leVKVWH5F0jfgSQk8lK6Qoc5HpK5W1uJiAWMpBJtZ1XiXkcxB9481GdZdnHXovWmrxDEnbdLAb7U0vUzSbvCSi/3nbhdj4X1FRc4sPiKUcZJfCJLbBfP67q4G6D9DI37OXyVurKeL+izqzhv0jW3z7iSm1zbix51am3Lo0AhBLOdwTL6Vu3gUhQSw980oRCHX/vY7mpD4I3R3VpjXB45hspDKe5bmirYYAYimJi+UkLlxxqJ+Vi7tT+Dv00fw/Wb50g4uu97BvaJfY6PtGFydKt8U18qxJMwCxlMYY4+FHNgRb27GNezzc6tr3V24nz1XCxc1cPjmF9Ebp3m2NEtFeE2oZyMzLm86q4UJ9BQbEwsjFBQsuUan06qbTyU9E1JiXDoJ6lxrzOf51A8p1e06+Pm2bhLaK+lStouN7Ohm9acpxLe2wj8y/Vs4+smzp/SptfrEAsbDxpWGp9u2tGyWhWxVLR3rbdGlH5h2zP2NHJtUMeh45PkR0GKGh1IDlF4Mr67NNXfUHfEehsbeo5ZA/ms8nb9wPSK6q8gMUCxALG81a/0DoR4sWn61mkZIc1u9A5sWM/EQNYHCxpQrssU1H3afRZZeyDZ6gV5H1Dxq0mEcFGY9rQWdPaq2ithcfEAsDH48ceIneGNGrViXxx8umPDemwuJ0nHveGaHnAns6y+UCmi5Tx9FjSNU3KElf32l6I4v9Q+0I8ZBvZPYFL5W0nwlArEJwt3eNNhvyDVeTOU4UEGLc/aAsWgnyrTOHTg9zLiA0oVNELEJXrKodHdh6wuvQvei16CB57DmxIr2/uLY726Ozp40fJ/JGu8GNfclb9xN+OD8OVkCsgrNAPHzHQu+IPJ7V6A7NceUeIfShXq1fC4M6NJlCp2dtRF3jB7MrpyB0k13JNnZhZ7HoJkL/mvi2aStmkZU+3SypaNTz4t3m7LYovmpmddLHXv2wfyhcgFgF5pGI+lk4vcZYRQVOVDE0qva/VCFVDH0VmtC/M5+0XBOwfdz82yimx8sxUT1HmDYZFy02taLCv/XivEQPq5byteJP9t5Fvs5g6VPrOdSrovcm1bf13MikkRYa+1MhVrGk/+1aMn/HFcW/S2iWWHGygDWnPXMf2hEV2PLgSotV//4TYjjNWpYXMdB02ft3S0y3/Kcv6dxeEiCe17+cmffwF4tipt71cAqYPC3cud7Mn47j0hG6aDXC+jh5a8ZjUb9Mh1fxWosSe/G4vIZPlPbhGKdIYlWY/7EA5eNdCBrnlYpKaJZY/cbTyUtRzgOZzV0WH51np3exs2Wb9uU5xrLcqnvPhhgZhe45YTu1r4GYy9O35fM7n2rqSoW9ET1f16vbstTx/dcG02XXhmyydvDjO7OpF230mlErzgxrl2egcXWnSGLV4nAb7kjNp3g8Ebn5zrt393a2IlYrKKJZYk2RLap+yhNlrqgg8hj6LevAGp8f5PZfXhc3B5dwKy5rD5X50ugD+Z19J1Rgx4m4n5nQIMLCNul11SGInnjjIou+1G3iYPq3aZQgQqk3Tn98xal56PIciYHLAfISKr6p5M/HLEW7FL6bU5EQ97yY5wOSf5usw4MUBfnSLLEeiajZWunVx6EWvntf/S/KNSvkVv14anvQXmC0kzxuriPcK0X/K0v9Yd+YT7kZYOkmeP1Y9IUgjXpq9PMsdSUd3Iz62yRIbo/sNLL1sGvogYWsphiniu5NznfjBHcLs8gzfr36U+R7rEexzoTrxBeKixv9HnD0r0BBEc0SCy0SDd0236vGz8NOdOTlVlkDXwKPUNvnhixqNtdHQ5eyznyR+YJMlJEyLHqFuE7oRkvztdXe6kxLiG0pWPaAugVL8g/dcnamxQTUhdN3ySCT4eOjZDWlNC/Vb2Sw89ltM7YlqeADMklRxUrd31FMeBjqTldYvErNXxfLzLaKQrFrmFjoXt9a7TZKUYzs+nXS+1d2U9mqDO6seIS+NeoY5I8+JCB0KUyPZ9hdeOOR+PWmUnUCx5cJEnVbamhdmf5jpM2p4dviHDprEVrjLnoiMrqTdYozEwatze8mQyMoklg/d7c1JsqMvYe+jiAULi93iFdm3M5Tp3ZNLsc9pKCIpon1i06z6eR26V+vdzqRzzLXw1gEu1oby+aPDOme9iPiRZ9TfIwtOg9q4di/kjFPvJW1AB21e6if/VeabuOTR4v4PHeNnTKhmCKJxSc8xsj+H/tG7FVY/mQkm3ooZNc5oaiEhoo1uQOdrInIyogx7xPA1qnXSp9XZdNSG9t4MuuusbFxyLEWOuxxoxwCTHmEf+noauZ+huHi1r7Zaqq9hdy8ST0aoNT2K4UiiTXqVtZeRkJez8Rf7x4/difXzcL9xVk4+Rf45OrES/pnmGf2237ndGETLAu7qpIgjkONmt7kpeyUkPvwdbxAh8Ndir668E9bog0iDs+u+ax7L7IPD20rC12ySmNnDypGBaF7j0dnYVGmkFWqCf9a1hraRvQnrOkGVh+DxO12rr2rsyW8LlQ4Ep+5YvTWpzRnCMFyEpY3bzAQofHR9FzCs+7ZKtrpRvVZpJSLV2rzlQKE7i0KSatGLHz856Vl8FMzhB7ynVGdafT/Sm/5PwUBHLaFaJeJgW5cHBFKPkbeMqEm1ksbjMhWj7Sd8/Kzq70aqGOUpWICoXuLz1vuqFRj0rNA/fRSspHsDy0P6jvqPevJcQl5YxPU0pDu0ZtgPv3kxioVv/313p2NvOuvz3fAhAYCoXuLzxOjDuif8E/vvUQdq6LnjzLJx2a+87aGhD6fYN9DbRb1lt3so/OtytdZkP7j8v0S+AWVCwjdW3xSjYzvpXU15LF0uIHWYgvRrEzUUWeWmc7YQD4R0LeUlb5Xh9/9VD8HG7rZWGvEClfFA0L3MsAgV9HIdpZ8/SNzDIMQuu4/cEYlFivEWRy0QYdjSHD6nhonXveraMsaLxA6YbNepe1VBhC6txB8u3BM7rCOtG4iR7Z+mdcZFqdM7yJ0jx28Rc9KEGYTzOezuVGXzc6gS2LZUg13TOlfgw6rYXRwhoHQvQVnlrhsBUHfZHmH7k3ln0PUb8l1NyIUY7YP1TG7Kr4RYSTW4yWiGc0RCt9Kl1spG/+eqXfnh/LarRIgdG+BmeV5A6E3deRPnHklkKIjniwTs6UI2ZffjY6JxKV9DMpeNTJE6Jw3Qm0X0sVkYqVOYhnxKl9UXtNVAAxNLigZZvQkv6+ix3IPOx4cpWvGDWDpXkF8oxebe4nC69WoN7Veb6MX6EAlhCrI5p7eNqMuha3K2qDUxeLzSmu7CgCxCsozWeQkVGuzvKMPBxiz26V1129jb9yMVynId/IIATugJq9RcrcW6WEeZb1Fv7qvmtV+ha5KbNeSu0vClNRylQBiFZQXv4YkV9+WLfN2xwoRk85GuZsZ1LQmOAKLhvocQs+a7ZOB0EldQaxP9VXN+WxW/RCRTwB9146SBxiWkRjQYZYSuRq8SlG+gFgFRWpDrdWBPlDhubKIF487scOTZSMwr2nb3KpqN7TVZBXryDcOp9389pLt3kd+VuewhDom5lO+SutlxSlJujCwG72TzE5X9mdQIiBWgVltcwShOwF9/uS8F11D6DTbqYrhUFFDL8OX+j66FrrEjQRxd8+GfRNQ1IpbkhfpIwZk1h2D0HHv3287WIb+DWe/hv4EXzBArHxJzoowv9lWUkoQl+1rZk1dcuPh+VKvCjol0WN34MSGb/TQ90rU7cuzduSPq7xnXE+Euk1Hp0iFHlj9fluGfz/ycfmGg0bEHSwqIFY+nAvkGVhO27Pg4E/0eWZU5wPZj03vitBnnU5StqRihA07hs1ubafHOxy0xssgmLydL6v3rfdkhCZGo2emCO3OFqfwVV3zOv1zLgIAABYFSURBVAGS+Ur+JMoFxMqbY5IVKdKpOgalLEtNNY+aPdqxQbYZ9ltCEXosrDqVpbtmhyn7lZijwzW8hCb1NNWpvP/EKKF+AjXH9Ynw6iE/9NVvUfZq72w+/DnnqUoWIFbeVFiP0AVeKYOZjXnEAPT+8OHwbH+wr+aT4/cZmOq0nO6wh+8axJmcmdmkzNqeVTiRw0P8Oz+ovu2J8AZCa4UWjUdYdS7Jj4ByALHy4MW+A5wUhMo5pFaztK3IEtoIAsoJBH8MOWerY1eay2PXnd6IQ3DZVadQS4rWMXQ3kg2wqrEVxYt6r5pk69Vq8GlVfQZVAWIpJKmjMMyPmCJFBtOGsMU1DQ2MS9VB6DYxJqvAK8naT1PahrH0wyo5mp39wT0lXILQ9/7uP8wvU4e/CJ8h9HRE017/qu4zqA4QSyGRUYkIWTnMQtw6fuyKZmIO6yX/PXpiLEj5VSCWvIPKGCKy5Oo7zUxGjwws+WwdB6PGL9Fc1ysIJUR0UGnzVQyIpYib5tRt+jwH00wzHTfWwifHWMRWrwuoV4fSWXOUmqxEaGSlhEOcUCvHe+kekvMoY5kpvcraQhMXH/7gFMWVl3y0R6zMtdEt4grxKLamIZ3EsRwFBEsU5WfFYkkkixs6vbHOmqPbegFKNX6QUkHXqBJXz5JDjxI9a0Xfgv28ev4Ls83XNLRGrE8Vy89c2tLsVIHfsLEOnRxn+dRkEQRLj2vEYvNCxv24aJY1ZH1ZiPShJZpkOTRxsnlFvV9zJC0eMNxwDUVrxGrfkfoq2VaqwIvyPxdSEwQ/G1sjqZEunxOwvRdBVLiDjpT+HUM+1S/qjOi1idm7GSKeob65LNPuNtMt10y0Raw0A1kA3AoH8in4hz7l1/SsVYa7AyFn9ijHejyWEduAZWC78U+JL/2FLH29i/3L/2v0MYpFC/dQoNV3Vn/QFrHe/FpKqdWSAr8lI5Stp2to0FWKytqZEToGi8s5SI8InqDzI7pMe5dVaJWZzSbBdrexqJuzPpn5pMKYvKrUIrRFrBRd2TJpVXcW9B0ZHdmujsK67dw3o1qzy+oIq/H1HZZktJ8ebTl4dhvJ1qxix6xYbMfV0oeia7pGIZWEo7Wsg10h2iIWakQvk3ba5GtB3zDA/B+EbrsZzGiI1paJrq6j30IYGxg4rJo/9bh3TpiQVe5nWf6i3SMlc5DZuf2HP2BouWaiNWI9t2+49dAQ0faClk80jNhEJo94Fo73z7hwotkNJf2aOQslpWSD19tN+13ykWFUtZ7nkxfxtyUqqEsb0Rqx0I+JNar0kD8RQg5HI409elM7Lq1MrXwG7Q8yth8vbD68M4t9kD4e1+tP2RZ1Yq25LI5XuGmJHmFVOLRHrMIgjbbp6tie05/cdXSiZy3/MzyUpR/gwWabyvqr+ma7Sf9oy3HXMagtuXWpEN1kJR0QSx4bPZO+8BO6cbruGc5uTQ9VmN26qUHLOgPXiUqxqXust2a/A779GKSnY8r3S0JxDdGcJiprsroBYsmj/gqEhvnd6upWTihb3B0lCPVqIpRaLdaaU2XPpSU2Q3+XbVJ7SA8UbrwTPReiS+4KKtQ+QCx5VDiOUOZ0YzN98YKstatms0RrprnW/emvU9XTtcGR30WvWSaPHoSiO3ihT3romGaufYkDEEse9eKpbVr/pn9mTnzQl3h33fkxSMc+NtBLFuNmc223iGWLWqItldAmP86PneVQx0Eqaa46AmLJY50XNXH5g+2RbHne05xDxrsZ6TxB0jHUKsfSVu5rr2wp79ESpTiPSwlmrbef3d0O+rGyALHkkdm+9KzdcZYDs+dtMJ42rwvHfBK5m2F5C6Fd7tTc5jRvYQp6GORQmcsmJF3eya9OGwGx5HOgQ1iX7OPUt9oa8QgWW1c2vz58N0IdZtC7G0wbvUPSReJB7ws8bkIrALFycWvGsNX06lX3l806+uvefX2piLK7T/vYsWWTVz3PkPdhsvUeT/r2MvR1sFonvy7tBcTKgTTGpEsfV37lyNYhkqiuHgGy+3SHGfbkXVeiyLg29eqoZSpCvWURdRY2QYlnb5SI8DeMAmLlYL7v++WihoYcA3eR3UOUOdqbGi/6lj9oGHWwbhfOPxeujBeRV0J02fQ+uX1lt0+lzVVbcIr1df/SKSsPvlFcQB3F8j50XXKj/PTIKZy5E4PILzCPY2Tma0FXOsxZ/WmWXbxcW8kGvc8XdZvdVwLjr+SDTyzpGAEduZdT74qiIsoSK3Njjw6zvuXOfy1nDA3/XcyQ+2aZI/vpNE4XPUOoHbXEgtS6dxsy+W4yIzRb0ccTO43V7DCoGMEn1izO2Gs7S0+9ucTfWJFZShLrU6B/3PxGVv/7Ozd9uomQVz7XDGXr2w3XHvU93nIsxxv5kkfrr6JyFzoIDqC3kZFOfwYmvzj+UBsCARQVfGL5UgtJHeUloZTwegqKKEmstvQ8ijX2f99hdw68htJWmxzNUbhLn06DyrPLscs4umWaPkQJQlkQ2YXGOsY8d+HYrGLHrdhcXaezuJuuueATy5B6HP9GHKfWvVNQRDli/TSQ9Vt6/+XQXZMvKO1Z2voKOUq/tq3CGWBt3m++jn59jy87nUb9yv9xcuiA+Q+zSh1ih1x/ssDIEKbkKAJjZAqq3/oitdT7oNIKiihHrKwIgc3is+cujXrZgmfOa8nJ2a/5uTJXx55fw0PipGus678VycWaDmd5WV/+2twATrFmcqfe2Ovmnv6+PhGroIhyxPquK7tHr/RXMNgFze1irj1434v1Omf5BmvWVbOzdfW1+YQUheV6yZVF7/VQ9L8MgE+sjF7kI6HDf+iSZIyiRVyVdI9Vm74zOi2LNpLFWVGAhZm1qLfhlJzFG66mk32KQqST3OHLxAqwY6qNJQ6c/VhPt59KRig157PTjclZlPaV+z6meVSq5d5jI3LMo5AaGBxBaLuub66wuXHN7k7uNfNV9zyGwHzXDaaSdH5jZltaglBBz/u5wVlYl2WoynxIGhVWvuvvG2/07FQCQmk6viY1A8Sj9cLJnI9nn/656n021mswprWBca5rZDbaG/X4htKq6zzMo4x2o30/6dyoLPEXhd+7KYh5uO1wIjJvjl43Myxr4v2762Aqj8tm6fga5/XE962mIUfM5hd8vr7WoXViJZjOyUBpkyxP2lIxBKWrdNamuPf5jqSrxTdkBW7wOkgTT3Uq0z/v0aCnY3usLYkhd5kCn1gVs6GgiCrEGiibENhmtGCjh3NtR3f9dytDyNdvzg5pISvQwoIOnlQlGmbcFAd8Yq32INzr/0JBEVWIFSzrdFhfL9bv1qWte4N7oh5x6GF1gbdAT/a7n2O5HVQyOTBa+Y0rQWC8FH7Qm5RPCVWIFbKHTtbVy5xs7O1vNDSNFOuT1bhUdMXElI6S4zAwgvoFaJxwb17VAPmA8x4rWB3FGtSdTlpOQOjruVPU0pErQya0IpOJLXoOTD+54lDjCZWD993eZBig/LaVJHCKdfl+PgVUIdYrs6lpKCXW+s8CHinuDsvom/d9vp6eUYGm/NUzq9jZWsMQ9mKhdU+F6HaIoAy/5qNsOa+sdenuhnXcleSrk8aOFr7UotpAcdA+scgnwPPv/86Y0ITuIA30oF9Ni3p0Kvc8rncxgeV7vFBG80oG2ihWLuib9/RZunH0q//JiyN4xaTH4WODRDlHbwGKALEQ2tYpxI7vLazSSDZT8Fg5OWX86KVrd9nBoNECAmKl1HWfs3mI8T8v0ZpAegHR6IG5Cz0TyYxy/l/uY4A8QKzJYdSQ5buihyg9oNF99DamlJyJ8pfdZGkITPYqIFor1qXR0VPpmWnex+jX0ZMQ+jZYrMdvLe958B0/mUoyrW7JOQjIoaSKdWvJnJN5HJb2MR84q52YGpZv+ozOmUyvOIo+KfhhufYA6kCcvNsvQB4lU6zULmYtuziHvFJYYIUXdb27JHyCkNcJOqfbxDxrfOUTGDetmnN+Xb5AFiVTrH+qJSKUPqCywnEtno48Qa3rKHo8QuNrUCOnH4nzcSZjbc+uSyGcSYEpkWKlGdNLeaTbKpopG6czN+ntLPGJ2Z0R+hnhvXjPKMlsPE3RWkqkWM9MZWmDtfKPfzCmV2TY4DuYClchXd8yvMcNPC3RXkqkWB8MZPOCQhQEztkRNqY+eZVM15eN6QMwUCLFQr70ov8PjD/JP7y24bfyYbuvLOd0xHR+oISKdVI07WXiJtvpCg5fsUlPmxHmGmaYhun8QAkVC92qK9KvqLCXXBrUj1TqY+hQRQWAYlNCxSLJawrN63CH9s1MusMXFj5Krlhy2dW/46wkaufM/OX3lH1yrUKrxPpWzWP87MaWZ5R7Vu1Eq8Tq1ZS6+G2xTlbuabUSbRIrU9YhjyrtVupptRMNFutIt7r9rhXmDYm6srTj3OKcFigQGitWZnvbKZtGmeQ9JuFv0nVlMZRqbCj6aYECorFirfSh1td+YX6xEO9pQndcXRV9LPppgQKisWJVl33tjOgv76CCyabP7aL2n54gWVX0swIFRWPFKiOb1hDfLNeRHyOtCdOecr+Vvo0O8WkLa/4rA40Vq9pmOhndJ+eB9MDImxmPOjl9LnrdQPHRWLGWVKCud2+tcvV2rqxMT+JqMbrodQPFR2PFSm/qumBfnEXu5reZRyf7gopeN1B8NFYshHa0Du58Lnd2E9m9+Sm/4tQNFBcNFksBo7rRSVwbDHUDBabkifVcTC31eNYEJsOrFHUT6+OUdjH7f+1/OXNBTpDBfDlmX7FDqPmmYrUMKC5qJta/pq3nj3OOpB740oYLfL2EcUVY8vrngbk7vzDQPKAY4BQr9Sv53+pRmxVG4s4lVqLJIep9NUeQ217BzxC66zuusGcF1AJ8YqV053EapbUgWES5RAVFcom1ig4Sj/6zQeg9n15274EA1gLVSPCJFcuNmWbrbXU+/Zg4RkGRXGKNl/3yl8zKQIcqybIcCzUyBlAX8InlNBSh8wQVqnuss4IiucRaJPvl76EEoSO/wlmUhjnKGgk+sfTXIfSdOEjubdRXUCSXWAlCemmOrl3I2y0+vU7VDTFMpdFI8IlVJhqh/QQVQ2CQp4IiuZ8K55nEnd5Z1426vRrmR35XnXeBxTo0E3xiLSHqdjFsIFh5Z6HC0Cdy+rGutvatNpm+X8+cKbSxNFteuJMC6gI+saSz3WyHSYcQBNFM0YNdPj3v6fcfZRbunIDagLuDVHph/fUcfZwX/0RY9S5KlYAmoIKe96u/xSrlw1CVgNqhZj/pACUFEAvAgtaF7gWUg9aF7gWUg9aF7gWUg9aF7gWUg9aF7gWUAzwVAljQVLG+MtgMAAMaKdbnfhKuqIeCRdwBtUATxUr2avUIPe3gWpQpPICS0ESx5tSkk4ZxTLYFYBZNFKuBbBL95hpMtgVgFk0Uq+Y2lPAwA+2vynBzAAbRRLEGRJYWWRlPGdKD4eYADKKJYk1nj0XotpvebYabAzCIBooltZteulzritaG8sLNA2qCBoqVIJQmH1p88Hv1rUy3B2AODRTruUSW1oEFZdQYDRQrw+wqlXwTP2S2NQCTaKBYaKbnTYTeRrZguDUAk2iiWGimyKeioNcPZhsDMIpGioW+njvyntGWAEyjmWIBag+IBWABxAKwAGIBWACxACyAWAAWQCwACyAWgAUQC8ACiAVgAcQCsABiAVhQJ7GkKwMkXsO/M34aQAWok1gtffYknG/iDuHnSwJqJNZhJ/rLqsUwxs8DKB81Eqv/aDo5AWt0lwTUSKyOc+jklj3j5wGUjxqJNakjnaypzvh5AOWDT6zGkzPyK/K3WAmiI+T2ucO2wp0HUEvwiUWwg57mUyTHU+E+izrD24kmFO40gHqCUawxvY1G5h1MPmcH6Zf44fMfFe4sgJqCUayp6FgZ8egneRSBnveSC1axUMZaJyJ45kVF0XdBrJILXrEQyjzYmEsYKCgCYpVccItF8m1PbwVFQKySixLEUgyIVXLBJ9bpBEUHorOwKFu4KgHNQQU977cmZxHgNrhI1CwbgAEXfxy1OuCotLwzjlp9qhXtn0Mugar8SedSERvtboPj72rkjqNWojyGSsvoY6g0wN6BQbGGXlWhWEWlH5be+cAjOGrl4Ij6c8kDQ6VoXgccteYP86F7iwqIpc1iFSB0b1EBsbRZrAKE7i0qIJZWi5V/6N6iAmJpt1j5hu4tKiCWdouFDRALxMICiAViYQHEArGwcOEmjlp3fMRR63Iphkq/Yon28uAkjlrzR33EAkoUIBaABRALwAKIBWABxAKwAGIBWACxACyAWAAWQCwACyAWgAUQC8ACiAVgAcQCsKAeYmUu9za07/mJ3DscLCi/irF6ma0N4WsoGmSOmK70VStri+5JTNdaUNRDrIVE6/WxgnJp6CSvxrLWxEqGqmW2NgpMDUWHWZRYjFb6xtFz3nj9KBx/hYKgHmJZ1yY3u4mdKLJMKpJGujI03InZ2igwNfSDpQklFqOVDjd5i9AQ4jWGv0JBUAuxEomF5PYrMfErZxy5s5m4xki1zNZGgamh0sjQfuYMtzfDilpn6uv5L8z/FQqEWoiVcpO6FdhPbLpLfhcgdIfYxUi1zNZGgamhc8UJA8wZbu9rYn3qxaspOP4KBUItxKK5bO6aepw4Re69I5YwUiOztf2G8Ybe0N2GKLEYrfQqMVJMEJYHcP0V8kPFYn3777//HlI7SQO5vk/RsV9/hPmMVM5sbb9gvqHJnl0QLRaj7T1IGG1Juhdq9ALLXyF/VCzWaYIgwsn0uK1oemrWF/Y9YgcjlTNbmwwMDZ1gsHbHjnrGO/7HaHv/R1Cznp4Qi3D8FQqAelwKD3NrfKDSJHYcud1JXGakVmZro8HR0AGEjMaMtvclsY7cprPHYvgrFAS1ECvDrlambK9OeXKnlVMmM/UyWxvC11DZpZDRSqU+zcntAWIv83+FAqEWYp0m2s2kuIpOcNsdHEysYKheZmtD+Br6SyxGK93Kar5uojA4k/m/QoFQC7Hif10MZpL3nEFG5Zj7+YHZ2jA2VCYWs5XuqMR3Gvid6VoLilqIBZQ8QCwACyAWgAUQC8ACiAVgAcQCsABiAVgAsQAsgFgAFkAsAAsgFoAFEAvAAogFYAHEArAAYgFYALEALIBYABZALAALIBaABRALwAKIBWABxAKwAGIBWACxACyAWAAWQCwACyAWgAUQC8ACiAVgAcQCsABiAVgAsYrBSWo5xsf6U1TdDnUExCoOvUw+SMMDMlTdDHUExCoO30q3Wa53T9WtUEtArGJxlDCYqeo2qCcgVrGQevMSVd0G9QTEKhar9MyjVd0G9QTEKg4vjSdvI46puhVqCYhVDKS1fNKk9R1+qLod6giIVQyWs68glGAUo+p2qCMgFoAFEAvAAogFYAHEArAAYgFYALEALIBYABZALAALIBaABRALwAKIBWABxAKwAGIBWACxACyAWAAWQCwACyAWgAUQC8ACiAVgAcQCsABiAVgAsQAsgFgAFkAsAAsgFoAFEAvAwv8B+RcoysYdoB8AAAAASUVORK5CYII=

    1. The absolute value of the correlation coefficient is at most 0.8.
    2. The standard deviation of X is at least 6.
    3. For X=17.1, Y can be expected to be about 19.9 .
    4. The scatterplot is standardized.
    5. The mean of Y is at least 30.

    Solution


    1. False. A strong association between the variables is given in the scatterplot. Hence the absolute value of the correlation coefficient is close to 1 and therefore larger than 0.8.
    2. True. The standard deviation of X is about equal to 20 and is therefore larger than 6.
    3. True. The regression line at X=17.1 implies a value of about Y=19.9.
    4. False. The scatterplot is not standardized, because X and Y do not both have mean 0 and variance 1.
    5. False. The mean of Y is about equal to 20 and hence is smaller than 30.