Question
Which questions is NOT a statistical question?
- How many hours a week do students spend playing video games?
- What is the height of each tomato plant in the garden?
- How much rainfall was there each month last year?
- How did Micah come to school today?
Hint:
A statistical question is a question that can be answered by collecting data that vary. So ,we need to fetch the question which will not give many responses (or) much data .
The correct answer is: How did Micah come to school today?
Here, The question "How did Micah come to school today?" is not a statistical question. Because it will not bring many more responses.
Related Questions to study
Which questions is NOT a statistical question?
Which questions is NOT a statistical question?
Find the minimum value in the box plot below.
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAV4AAABLCAYAAAA4R++GAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAFxEAABcRAcom8z8AABguSURBVHhe7Z0HmNVE94elWFGQDgqIiKAigvRuQ6qKIkVRrPS+S6/SVJpUAUV6E1Ca9C6KVGmKdLEhIFLVT7HA+ecdk/2W3Szce7O5f+79zvs880Am2Uwy5TfnnElyrxJFURQlrKjwKoqihBkVXkVRlDCjwqsoihJmVHgjjNOnT8vhw4fl2LFjcvTo0ahJ3I+T3PZrunw6cuSIHD9+XP7++2+7tyhXKiq8EcSFCxekd+/ekilTJpPSp08vGTJkiOjk3MMtt9wiuXLlksyZM0fFfYU7UWcZM2aUfPnyyZo1a+weo1ypqPBGGJ06dZJUqVJJt27dZPjw4TJgwICIToMHD5Z+/fpJoUKFjIC0atVKhgwZ4nqsJvc0cOBAU2fVq1eXq666SmbNmmX3FuVKRYU3wujSpYukTp1aDh48aOdEBz179pS8efPK2rVr7RwlWGbMmGGEd/bs2XaOcqWiwhthILwpU6aUHTt22DmRzz///CNdu3aV3Llzy4IFC+xcJVgmTZpkhHfOnDl2jnKlosIbYUSj8LIYxH2p8Hpj4sSJKrwRggpvhKHCqySFCm/koMIbYajwKkmhwhs5qPBGGCq8SlKo8EYOUS28P//8s0yZMkU2btxo50Q+KrxKUqjwRg5RLbzr16+XrFmzSsuWLe2cyEeFV0kKFd7IIaqFd8OGDUZ4Y2Ji7JzIp0ePHiq8iivRJLznz5+X999/X2JjY+WLL76wc6OHqBZeQgy8itqiRQs5e/asnDlzJqIT99CxY0cVXsWVaLN4mzVrJilSpJCPPvrIzokeolp4N2/eHPf+f+nSpaVEiRIRm0qWLCmlSpUyFny6dOlUeJVEOMK7ePFiOyey6du3r2TLlk2WLVtm50QPUS28mzZtkpw5c0qBAgWkSZMm0rBhQ2nQoEFEpkaNGknjxo3NNw3SpEmjwqskYvLkyUZ469evb75/0atXr4hMfAiKV8grVKhgPNYVK1bYdxg9/E+EGtq1a2fnRD50TNwvFV4lITzBg/DyhbJy5cpJ0aJFpVixYhGXihcvblL27NklR44csnLlSvsOo4eoFl6eauCLV8R4owW+aaAxXsUN51sNU6dOlV9++UVOnDgRkenkyZNy6tQps56hoYYIZNeuXWbmx+2KFhAoFV7FDSfGGy2LUd27dzdrGiq8Eca5c+fk0KFD5kWKaEGFV0mKaHuqgW9PZ8mSRZYuXWrnRA9RLbzRiAqvkhTRJLz82grP8KZNm1aWLFli50YPKrwRhgqvkhTRJLx//fWXjB8/3jyNRMgw2lDhjTBUeJWkiDaLl1DhH3/8Yd5iizZUeCMMFV4lKaItxhvNqPBGGCq8SlKo8EYOKrwRhiO8O3futHMiH35zTYXXO/qba5GDCm+EgUDxK8N79uyxc6KDPn36mF8ZXr16tZ2jBMvMmTNVeCMEFd4Ig7d5EN6mTZtKhw4dzCM3kZx4nZt/eb31mmuukRo1akj79u2lbdu2iY7V5J6oQ9L9999vhJfPKSpXNiq8EQSxUN7CK1y4sPlYTsGCBaMmcU+Ib7TdVzgTH4PiwzJ8h1q5slHhjSCIhf7000/y448/yrFjx6IucW9u+ZoCS0eOHJHTp0/bvUW5klHhVRRFCTMqvIqiKGFGhVdRFCXMqPAqiqKEGRVeRVGUMKPCqyiKEmZUeBVFUcKMCq+iKEqYUeFVFEUJMyq8iqIoQcJbpF4IWXhPnTwpn37yifznP/+xcwKDr8kfPXJETp44Yb4y7zcHDxyQE2H4sctff/1VDn39tfz55592jj9Qfz8fP25eEfW7/i7YbUX9+V0WP+n9w/ffe+7QgUBZ3xw6ZG/5x5/nzsnhH36Qs2fP2jn+8bs1Dn+0yvrN6od+w0/HL1u6VPbv22fn+MfX1phas3q1+Skgv/n0009l+bJlAf3ixZ7du2XI4LdknfU3oRC08P72228yd84cKV++vJQvUyZoUaMChw8dKoMHDjTn8ptXXnlFpkyaZG/5xxc7d0q3rl3N9wb8hE4xdswY6dG9m/z+++92rj8wqXbt3FkmTZwo530W3jVr1kjb2Fgjvn4zY9o0adK4sb3lH/SFHlafmDVjhp3jH4hgm5YtZeWKFXaOfxzYv1+qV60q8+fNs3P8Y8Xy5VK3di3zfRK/adG8udSrWzegyX/Htm2S/858kj59evMlvR3bt9t7AiNg4WUm5ff6q1kVfvXVV5vPz5UpVTJoixcGDRwg7WJjzO8p+c0TTzxhhMpv6Ix8shFrwG9GDh8ur7z0ou9WwDnLeq//3HPy3nvv2Tn+wRe1nrfK+v677+wc/xg/dqw89thj9pZ/4AW1atFc3h42zM7xDyzrOk8/LfPnzrVz/IOynrUE6rN16+wc/9i2das0fPUV42H7TYf27aVpo0b21qWhnxYvWtToIOnWW26R2DYx8vmWLfYRl+aywovrPGnCBHnk4Yfl6tSp4woi3VewoIwZPVomjh9vOnMgaeL4cVZFviqVH60oI4YNNed2O85rGmeJxczp06VkiRLSwLJ6J1tWm9txyZEmWfc/sH9/qVunjoweOdLco9txyZGoLzrig5bH8e6oUUHVfTCJ875jnb982bLSzLIO/WonEud+4/XXpazlQfXp1dPXsugHjRo0kBLFixvLl37idpzXNHHcOBnzzjvy9FNPGUEcZ03+E6w8t2O9Jtpq6ODBUsFqq5bNmsnUyZNcj7tcoh+PHDHCeANMgi+88EKihAdZq2ZNyX3bbVLTuje23Y5LjvTyyy9L7Vq15M68eaVO7dpm2+04r6l+/frS2BJcvmecP18+c08vvvii67EkruM5q36yZct2kR6SMlgWcP9+/S7rjV5WeLHgYtq0kXRp0yYq5I48eYzl2i4mRlpbbs7lUkzrVtI2po1UKF/OGmSlTV7bAP822NSqRQvp07On3FuggFStVEk6dWgvbVq5H+s1tW8bK/Xr1TMTUeOGDa06iXU9zmui/mLbtJaK1iTIbBtrtQvbbsd6TZyX8xctcr9UrljR/J/y3Y71llpIl04dpY41wO7Kn99Mkn7VH+1PP6hWubLcc8/d0uu1HqafuB3rNdEnmjVpLMWKFJEqlSuZceJP/bU0537Z8oAKWn29tiXy1Gco99W8aRMTWprzwQeyYP58+cglLVm82EwgD1aoIN27dpUlixbJAssTdjvWa1psnbu3NYarVakiM2fMkEULF7oe5znNmycfr1ljrPhKVl+nnIULFrgey71yXcOGDJE8t99+kR5mz57dTFirVq68bLgioFADH+DetHGDmRVQdKegCuXKytkzZ/gtZvnHOuZyifgk7nHf3r3MADhj/S0LOG7Hek1cMzxtdUQsQ6Ay3I71mmD7tq3S0ursfBMV3I7zmqg/7mvIoEHStHEjEyMnz+1Yr4nzcn68k5FvjzDl+lGW004rrc76omVNfH3woFnIczvWc7IHw3uWJfqUZa0B5bse6zEBfYF2wgsydedX/7Pqa++ePfKMZRU6oYaQ7su6PsJ/l1tI/f7bb43Vy6KX32zcsMHqF/Xl5zAskBNqaGBZs4FwYN8+KXDPPUYHs2XNagyudevWyd8Bhv+CXlzbsnmzNLAGY4YMGaTA3XfJiRPBVQiN+kbfvsYaCMdHm6tXry6jLPfJb1hca92qVVg6yKD+/c0iwK8+L04So8QSHR6GGOXatWulljVJ7t2z187xj3csIaxsWb1+c+LECWtANpCB/fvZOf7B0zuPV6smM8Pwsz8s5LG4hmXoN6tXrbL64NPyXRhi/xhOzz/77GWtVfjSGu8PPfCAPGONQ55sOBfkelXQwuuwYtkyGdCvn7Fag+HC+Qsyfdo06f/mm2ER3tiYGJkVhs5Ixx9tWdbB1kcozJg+XXp06+r7UyEIL67nbMv19JuvvvpKOnfsKPv2+v8jntwPT1D4DWG6IW8NMjH/QAazF1jw6ti2nSxbusTO8Q+eZHrf6oPheCTvB+u+PrTai0nMb3iUjBBLII9O/nL2rOzbs9sa76FpWMjC6wXCDQzq8z53RjhjifsfPj92BbiSLET6/bwrUM6v1qD2uyzOj3j85fOzyQ6U5fdz0IB1Eo5nawHXnQkyHG3FmDp37pydE12EY1yFk/8X4VUURflfRoVXURQlzCSr8OIO7N692/yuv5NmzZolH3zwgWzbts0+6l+2b99u8r9PxjeVCGGsWLEiruwZM2aYMubPny+nTp0yxxAzIp908OBBkxcMhw8flg8//DCujJkzZ5oyKBe38ujRozJ37lxzfucY4pehQsx44cKFicpbsmSJiZEvX748bp9zv1xLoPFfVr9ZjU14DtrtkB3Dw/1fvHix2c8rnMkFC2qck3txnm6Iz5dffmnqOrn6yKpVq0x58+bNS7S+QP9kH/cZ6osphC8WLFhgzsO9xY/r7tu3z9Qp+5xrSI5wB3XH+WhDh71795p+4pTljMHVHp9CoH8vXbrUnJN+F7+eaL+PP/7Y7Nu0aZOdGzzO+OQ83377rZ37X7iGRYsWmXsJNazCq8Gcn/6QkI0bN5p9tI+fb4Ymq/AS5+zTp0/c42bxU9OmTe2j/u2EBQsWlBQpUsjs2bPtXO8wmHgI2q38/fv3y44dO+Qe+xEQUr58+czbeMHEjxDVa6655qJzk+699145fvy4jBs3LtG+Xr162X8dPDt37pRcuXIlOmfOnDnNvsKFCyfax30FugpMXJW3uBKeg8QA4J549MrJy507t+mYXmDwvPHGG3LttdfGnbdRo0YXvW7NBO60FaLhBd6u7NGjh6RMmTKuvBo1asQN7EGDBsn1119v8jmmXr16ZoINBiapOnXqxJ2fPhITExMn8LxW6uwj3XzzzbJr1y6zLxQQbR7md85HXXbq1MmMwSFDhlxUlpNKlSpl/3XwsLjFSwXxz8c2hgGx5datW8e90cq9jR07Nui47ObNmy8av3feeacR2fgMHTrU7OOTBcE+QcRE0aFDB7nuuuvMOVKnTi0tW7Y0+VzrsGHD4somPfTQQ57a6FIke6iBDsGgJ3HRxYsXl0yZMpl38Wmk3r17S1r7ZYw77rhDli1bZv+ld+h0WJyUzbvdw4cPN+UwINiHFVCsWDEzWzMrs++BBx4w4hMozILMypSB9demTRu58cYbZcSIEabxGGC33XabHDhwwAx4hMuLZUOn4F4oj3MiUIgD5bHPuV/S22+/be6JV5cDXUXnmrlG/h7LEu+A98/pdHyIZ+DAgeacr732mimfCRPxZSILFeo+S5YscvfddxuBZWLinubMmWP6SP/+/c3gpdxbb73VWKFeoAzO9fDDDxsrunPnzmb79ddfN/uffPJJqVq1alx7sg/hCIY333zT/B1iy4RYpUoVueGGG4x1RTtVq1bNvCFF/6E/ULfkh8pnn31myqtbt66ZQMqUKWPEnuehEUKnTzAGuW+uBSMjVHhtnPJ4Y4u2r1mzptnGysWi5v8NGjQw+55//nnTnghpoFAv1BkTCMYYRhIGBJMvkxdeI4+GUg6JMc3HjoIBg8H5W+qGPp0qVSpznZTfsGFDKVmypBkP48ePN8diSPmBrzFeZmAqcpL9kZpPPvlEKlSoYG6wQIECkiNHDuO6+AFixcAuW7as6YjxoVFr165trEY6TbAzswOzMZMKsybnoBwGGBYqA7Bv377Guk8umDCwzFq0aJFo9R/RvP32280ARIxDhUFKvSBQQGfn1UjEC5zO67RpKHAu2p+yYPLkyXLTTTcZtxlXDxHEmsKLyJo1qwm1eAExwBpr0qSJ2X733XfNPbz11ltm24HyCxUqZNow2PDGqFGjJF26dOZf4PozZ85svkFB+UWLFpUSJUoY0Z86daon0QVnMqGfQa1atcyz9QhvfJigOW7kyJF2TmjgdWBg4DkAdUmdEuLAY6AM+icwgbI9evRosx0IiCiGGIaRAxMydcjES1vx7DUTDZMIwh+s8LZv395cF2EEINTImMEKjs/EiRON4YFVjUD7gW/Cy4ycMWNG04kdYSPuSGXhalKJWD1+CC/WnuPaJXRVgNmbQYKg0KhYw8GCm0PD5M+fPy5WjKDT+ZntuXf+RcQQjlDF3QE3HFHNmzdvojgr19+sWTMzybndb6AwUAj/DBgwwM4RYxVQj1jRiHHFihXNNgPaC1gSiC2vWTJ5DR482ORjeRCPp588+uijpp28Ci91j4uKRYgFzfU3btw4UVwZEaMOmZSDfW4UrwmLFlHgnrhuBjAQp6ZMyseSx8qiDCwrLyDi1CF9jOueMGGCvedfaC+MACa4UD5mFR/qsHnz5qYcysNNxxsCQlLcH/fPhMBxbLdr187sDwS0AbGjbpiIWQPCW2Z7zJgxxhPC2EA0CRUQKgpWeDkv14WHs2fPHuPx0CZsO6AdaBMGDtfjvIma3PgivDQSMyI3iSuSEDo1ooU144fwEp9D9OjcSQXgGdyPPPKIGSChxHFwRen0PXv2jBNVLE2sXBZYAJeJOuCjG0w2XnDO1b17dzvnv+CGMdgrVaoUssAzMIkXYwHEj2/iEuNeUjaJ/fzLYAgVJi0GKR4PccrSpUubODKhDAfCOUw0CJVX4WXQMlDxgLBEGdDEOxMu+IITw3/ppZeCqktCCtQfHhZ/ywTJx1QYuAggE9iWLVvMwMaLoH96CaEwESOoTPyUh8Di4juWOpMxcXTaymuMHOhjjFlisNQhYQDa7JtvvjGhgC5dusTFeLkW/h/s2sbWrVulXLly5hwYAOgDYS8E04HJjPYJRXjRAq4Jy50yOHeaNGnM+EwI7YnxRFjC69h1wxfhxSKjgXAVnacJ4sPAI+Tgl/BOmTLFVCwuUHywsuj0ziLOq6++ao6LvyIcCDQgYoQbtH79ejv3XwuDTkn4Api1OT/HYsl5wSnPbSLr16+fsUSI8YYKkwUiRxgovuBgZeBuIX6sJLN4ihXipd2mT59u6oVQFFCHbOOlOLFpykTEkkN4CSFwfiemi+CyTVshGog/bigQFsBqxbIPVHgROcQPQWDAAq4x4spCF3WLCLPOAcTpERbH5Q0FQhrcA+sY4Cw6MfEDoTbCG/fdd1/c0yleILzF+ZmYAOuabQwPZ62BiYSxRIyefcHcH3VNX2MM4bVRj8SMmZzjPyXhRXjxcPAy6LvO0094QJyTODmGmtNHMD4IfbDAF2w5geCL8DquFa6bmxuP8BHEZlB5XThxgwUzXH7ihfEhzsV1IWKILu4SMSNn5TlQEFRigcSj4rv9WM64YQhTq1atTByKQewsvHkBa424aEIB57x0Qu4L9ylUaCvO4UwaDogtIRmsacQEFwwrIGGMORiI9WM507Gx4B988EEzABBkp79gSRUpUsS4lY4HESq0F+2AdUgYhac4aCNivQg9bcm9E7/EC8KTmTZtmv3XgYEHxOTHNSNGWG558uQxYstkSV/DEuR+WXzlOCduHgo8CsU1Y70752TRk5gysGDEfqzg5IC4NNYhVj0L5HgpeIvElBkDiDzXQriKBVhSMB8vRxQRbDw3+iJtgcVJCC2+hjiLfIQwgxVExJVrpN8R2nr88cdNmzD+8eycJypoP+dJHiY4r2PXDV+EF8uLgUSQ3Q3EA/Med8xLTNINGglLG4s6oaDiMmARICRcX2xsrKnwYMFiIv7DPSSM0zE7EzPCmr/rrrtMXXi1dlm0w+3GGk0InZvFKNzAYJ7OiA915gxeYvPxIQTBhIXoMxC4Z68WFBYST09wT4gcVhmhi/iLoHhKWJG4tF4sQ6A8QjWIBW4mgsjAc9qFGP0zzzxj9jGZcqybwXAp6Ft4VAgQ94SwMpE4sVWsLPokBgHC//nnn5v8UOH6sNSYNCiPeLjjDSEUTKD0ca+xeAcmWjxJ6pCnkhBWysf7Y/LC2CJ8wz5EKxQjAAHHIGJ8og30yYQeM5YqTzpgMAU7dqkznuzAMKMvc73xvSmef8bqZYJhEsOL8Dp2k8IX4UXwcD0ct9ENRIL4l9egvxu4CZdaHEEsvXxFjPvi77lPt9mQgU4ZwVrSSYE1QCdzeymCjs8+4pihwj3QHpwnKUvWsQqSE4SWfpJUPbEf7yjQl0EuB+ejz7n1DeqYfaFOXg78fVL3RF+nDpNadwgF2p3rThiHJJ/r8OKZuHGpNqOd2Jdw0TIYGFuMHbcQJbCf9iOFWg5imtR4cvrBpfQjOfBFeBVFUZSkUeFVFEUJMyq8iqIoYUaFV1EUJcyo8CqKooQZFV5FUZQwo8KrKIoSZlR4FUVRwowKr6IoSphR4VUURQkzKryKoihhReT/AE4wDbZUjo9CAAAAAElFTkSuQmCC)
Here is the interpretation of the box plot.
The first point on the line on the box is the minimum value of the box plot.
Find the minimum value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot.
The first point on the line on the box is the minimum value of the box plot.
The box-and-whisker plot displays the number of inches of snowfall last year for 14 cities. Each city had a different amount of snowfall.
![](data:image/png;base64,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)
What is the median amount of snow that fell?
Here is the interpretation of the box plot .
The vertical line inside the box represents the median value of the box plot.
The box-and-whisker plot displays the number of inches of snowfall last year for 14 cities. Each city had a different amount of snowfall.
![](data:image/png;base64,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)
What is the median amount of snow that fell?
Here is the interpretation of the box plot .
The vertical line inside the box represents the median value of the box plot.
Find the first quartile value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot .
The value of the first line of the box is the lower quartile (or) first quartile of the box plot.
Find the first quartile value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot .
The value of the first line of the box is the lower quartile (or) first quartile of the box plot.
The first step to draw a dot plot is
The first step to draw a dot plot is
Find the maximum value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot .
The last point on the line after the box is the maximum value of the box plot.
Find the maximum value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot .
The last point on the line after the box is the maximum value of the box plot.
Find the minimum value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot .
The first point on the line on the box plot is the minimum value of the box plot.
Find the minimum value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot .
The first point on the line on the box plot is the minimum value of the box plot.
Find the maximum value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot .
The last point on the line after the box is the maximum value of the box plot.
Find the maximum value in the box plot below.
![](data:image/png;base64,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)
Here is the interpretation of the box plot .
The last point on the line after the box is the maximum value of the box plot.