Question
Which translation rule is applicable for the image below?
![](data:image/png;base64,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)
- Translation: 4 units left and 2 units up
- Translation: 2 units left and 2 units up
- Translation: 4 units left
- Translation: 2 units left
Hint:
The translation is the act of moving a shape or a figure from one location to another. A figure can move in translation up, down, right, left, or anywhere else in the coordinate system. Only the object's position changes during translation; its size stays the same.
We have asked which translation rule is applicable for the image provided.
The correct answer is: Translation: 4 units left and 2 units up
Now as we said that in translation, a point or a figure can move up, down, right, left, or anywhere else in the coordinate system. Any point can be located using a Cartesian coordinate system or coordinate system, and that point can be displayed as an ordered pair (x, y) known as Coordinates.
In cartesian plane there are 4 quadrants:
1st Quadrant
2nd Quadrant
3rd Quadrant
4th Quadrant
The sign patterns are in this way:
I- quadrant (+, +)
II-quadrant (-, +)
III-quadrant (-, -)
IV-quadrant (+, -)
Lets construct a line down to L' joining to the x-axis, and let it be L''.
So now lets consider point L and L'', we get:
L''-L= 4
L'-L''=2
So it is shifted to 4 units left and 2 units upwards.
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. Translation is 4 units left and 2 units up.
Related Questions to study
Which translation rule is applicable for the image below?
![](data:image/png;base64,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)
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. Translation is 6 units right.
Which translation rule is applicable for the image below?
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAQQAAAEGCAYAAACDwOsBAAAgAElEQVR4nO2deXhT55m373Mk2bKNbXnDOwYMZjVQQoAkEJYkLCFtCEnJJGmbNuk6bTppv860nW/STq9ZvmnTZaZNk0zWljQEAmELBAhLSNghQDCLbYx3sI3xKkuyLUt6vz8OOuzB4GPLkt77unz5WDp+zuPX5/x0zrv8HkUIIZBIJBJADXQCEomk/yAFQSKR6EhBkEgkOlIQJBKJjhQEiUSiIwVBIpHoSEGQSCQ6UhAknD17NtApSPoJUhDCHIfDwbPPPhvoNCT9BCkIYU5paSl79+6lubn5mu97nOWsf/7/8M2f/jeHGsFTspofPvcelW45wTUUkYIQ5mzatIm2tjZKSkqu+b45Zgj3LroPpaqQzfvKMA8fTX5TBY2+Pk40BPG6weWEjg5ob4f2DvB4tfd8XgiE5JoDcMywp9N+nroGJ+aoSHxuN0JRiUpIJmlAFKrSt7ksW7YMu93O5s2bmTx58jX3seZOYlbcQT7ZWsfhMUNRh00jvkWhrBXUOMhKB7MApwuiYuSnTHeoOQabN8HuEhibD7XHYFcJPP2v8KU0eO0T+M63IKGP8+qmIPhwNdZQWlJMVSskpaaTGKXgaj7HmQYr4+6exKA4qS03ppOqA9vYvKeA8hoX6SMH01n1GbvWlzD6R//Gvzwxieg+zKaiooK2tjYAVqxYwXPPPXfN/URXHJbkf2Ttf1rZerCCRY9NJG4b7HgbWkfCr38PkXvgPw7AL37U9ydxsHFyFfzyFZjzc3jlHy8IaA386GWISILC5fCBAs8EILduC0JHSxUbfvdNfnUgm3/8t3/m3myFhvJDLHvxBAuXvcbjUhBugJvTm17kX/50iCk/+AX/9mweJgDOkt74FiLZRkQfZ/Thhx9SW1sLQGNjI/v372fKlClX7adYTEwc5yPF2krGHY387LtZJJpg5ggoOAcDgH2roDiTPhW0YOTcbvjRP8Pwn8JXZ1xyN5UGjz0MA9NhTxn84B8hJgD5dfMqNpM4eBhpcankjFzMN742jyEAs2YxyLOCyMy+PpWDj7YTq3nuJ3/D++Tv+NY8vxgApDLzmw8hMgZe8lof5NPWxqpVq3C5XADU1NTw2muvXVMQwERDlYkWTwMPLcjDZjLT6QLrMPjCYIgHauvhh9+HyD78G4KOdlj1OhxLhV/cD9ZL31Ph9nGgKHB2IYzODUyK3X7c8zWfZO8nZ0ibPp5swN3airPTy8hHvsiIqL48lYMQ0cDWt97k/a48Hls4iQGX9ROYyRg/gqyUOPqy+2D16tUcOXKE559/nuzsbJ555hk++ugjjh49evXOXYK9RwSOOxN5dFw0wgU7VoHPBonJ2i7jvw13Z/fhHxCEOGpg5yYYPxlGp179vnLhBJjyJUiwXv1+X9BtQWgp3M+W5gQmfmEwZs6ze+NeSs64iEmM6/Nb3WBDNJTxyaflDJp6NxOzBlz1fh/3I9LS0kJDQwN/+ctf+MlPfoLVauW3v/0tf//3f8/27dsv2dNHh6uW07vtHCkWRKjRbFpu4pc/go/itDsDPxOmQ7Slj/+QIKOtAk7UQkq29ph1PcwB7JXt5iNDJ6cOHqTOo9B24gNe3H2A3Zap/Mu8eX1+Mgcjzpaz1JY5SB83kJgAKf+VPP7446SlpQHg8/mIiIjg2Wef5fz58zgcDgYMGAB0ULJ5JT/753Ectc/g28/BPyyEnb+DjtsvjyfPgxsTYYMkqzbceOWQorsLfD6wBviZq5uCcJYDGz9j4PSf8e//9E3UPYMZ5IhlYPzle3V1deFyuYiJicFsDt9ORqfTiaIoREVFoygQFZtMUnoM5R0uurxc1uoddgduxURsbFSfXVQ2m+2q14QQqKpKauql97LR5D/0DD+rhKeXwpSJYAJGPQBR6Z9/jI4OcLthwABQw3Qc0usFlwuio8FkgoRhcO+9sHovlLtgxIUe2I462FsEaaNh1MDA5ty9q7b6GJsLfdz+73eQCnSMmso01UTcJWfw6dOneeONNygpKSE9PZ2f/OQnDBo0qHey7qc4HA6WLl3Kjh07sFgsLF68mAULFmBKHcP8+yexdv3H7ClbyCN5sYDAdb6IXXuqSfvCVMbFRgU6/WvjhL37IH4k5GdqL6WOuP7uQsD27fDWW9DZCVOnwne/C5Fh1tt45gy88gqcOgVJSVob5OfD07+Elv+F3/wUpkyCaBUiYyB5EOQGWAygm4Jw9shuPuvI59+nDgHAmhB/WQ/p+fPnefbZZ9mwYYP+2qFDhxg2bBjh4uGqqioNDQ18/PHHOBwOALZt28a6deuYOHEi87/7c/5V+Ssr/+V77Bk9lqxoExEZI7htwniGZsUFOPvrIODoh7B5K4i74ew5yM74/MeDffvg61/XLgiA1athyxbtogiTUwFFgZIS2Lv34muHDsHGTZA6Cf5vOuz8CNxxEGmGnHwY2186ZMXn4hVNFbvErxeNFTGW6eLfVh0Qta6r99q+fbtAeyySX5d8KYoifvOb3+jt5HM1idNHD4qDRwrE8WMnRFldq/B8/j+gT8jNzRU+n+/qN3xCNJ8V4ugBIQoKhWhyCXGNvS7u7hPid78TQrv05delX9HRQuza1Wv/QsO4wR2CSnzGbXz3le18w2fCGhND9DU6xUwmOex4LYQQ7Ny5k5iYGHw+H6rJhMlkRhE+TTF8XrxeX7fmrAsh8Hq9vdI3s2jRIv785z9f8z3VDGYz4ANPF/ium6wAzOzdOxMYZXiOwU5Xl48VK/Zy9Oin+Hw9u146OzsZPXo08+fPNyi7iyhC9PxGrrGxkSeeeILNmzfrr6WlpZGcnNzT0CiKgtvtxul0kpCQYNgjiKIoNDY2kpCQgKL0vDtPURQ6Ozuprq6mvb0dgPT0dDZu3Mj48eN7lLeiKNTW1rJlyxa+9rWvGfoYpigKw4cPp7i4uMftoCiwZw/MmaPgdF58ffBgrXOxpygKdHS46ezsID4+ztBHkMbGJpKSEg2JpSjgcEB1NXg82mujR8P+/YIBA+hR3oqiUFZWxqeffsrixYsNyfcyjLrVOH36tPjRj34kkpOTBSAWL15sVGhRXV0t3n33XcPi+Xn11VdFe3u7YfGqq6vFjBkzBCDGjRsnNm3aZFjs2tpasWTJEsPiXcp1HxlukZ07hZg5s12oqluAEG+/bVhoUVJSJNatW2FcwAu8/PIfhMdj3APc1q1CREZqjwuPPy7E6dOGhRZlZWVi+fLlxgW8BMMGhHJzc/n973/PV77yFQDef/99zvh7lnqIEAKPX2oNxOiY7e3tNDY2AvCf//mfzJ0719D4wcK0afCznx0nL68G0HrbvV5jYvt8Ch6P8Y+oHo+xs6rOndNGWcxmNz//uY/cAE1FvlkMHyEeO3YsMTExtLe3s3TpUqPD92uqqqo4fvw4iqIQHx9/418IYSyWeh54wI7NpvWwHzgQ6Iz6Fr8r3ZAhzcTEuAObzE1guCCkpqYyZswYAJYsWaIPwYUDVVVVgNZ3EBsbG+BsAovbDfffDykp2vP0O+8EOqO+o6Pj4rBrfHwTFksYC4LX6+XJJ58kNjaWs2fPsnPnTqMP0S/xeDxUVlYCEB8fj9XaT+YoBwifDzIy4PHHtZ+3br34qRnqOBxQVKRtx8Wdx2LpDGxCN4HhgtDV1cXs2bPJzs6mpaWFP/7xj0Yfol/icrk4dOgQAAkJCWEvCKD1sD/xBMTEQHk5rFsX6Iz6hjNn4MMPtdGG5ORazOb2QKfUbXpllnlUVBQ//OEPAc2Vp6CgoDcO06+w2+3s2bMHRVFISkqSczPQ7hKGD4e5c7Xb6PXrtbn9oY7/TmjqVBg1Crq6ApvPzdArguDz+ViwYAE2m42ioiLWhcFHQ3V1NU1NTYwePZoxY8b0yqhIsPK1r2nfjx7VpjaHOuXl2vfMTEhO1oQxWOi1dWhZWVk8fuEB8sCBA/pwXKhSfuEsSE9PJyMjA18wnQW9zF13wdix2ifn1q2BzqZ38Xjg9Glte+BAsNmkIOgz6fwzqd5//322hvCZIITgyJEjgDbKkpaWhteogfcQIClJW/AE2krIsrLA5tObtLfDX/+qbaemQkKCFASd/Px87r//fgD27duH2x08wy83g9frZceOHQAkJyeTkJAg7xAuQVFg9mxIS4P9+yGUB55qa6GlRbs7uPNO4yZk9RW9KgiJiYnMmzcPgFWrVlFaWtqbhwsYjY2NHDlyhNjYWO68806EEGGz7Lu7DB8O/rU4GzeC3R7YfHqLigrt+8CBMGSIFISrmDlzJsOHD6eqqoo9e/b09uECQmVlJV6vl8TERPLy8uTjwjUYMABmzdK2N2y4+Jwdavgfh2w2SE+XgnAVo0ePZs6cOQC8+OKLtLa29vYh+5wTJ04A2oSkwYMHyxGG6zBzJsyYoU3cef/9nq3666+sXKl9t9k06zQpCFdgMpm47777SEhI4PDhw3z22We9fcg+5+OPPwYgNjYWm80m+w+uQ3Y23H23tv3SS1BfH9h8jMbphMOHtT6T61TF6/f0if3lXXfdxfjx4wF48803++KQfYbH42H37t0AepET2X9wfebN0/wRzp3TrNVCiepqbQ1HQgJcs95NENAngpCcnMy9996LoiisXLlSn/MfCtTV1eFwOLBardctliq5yNSpWgcjwJIlFw1EQoGKCm1WYnQ0BKu/cJ8ZZD/88MMMGTIEp9PJu+++21eH7XXKy8vp6OjAarUy3H+mS66LqmozF6OjtVmLhw8HOiPj2LdPu0OQgtANRo4cqd9Sv/rqq3R2Bs8KsM/j4MGDtLW1ERUVpS/7lnw+Dz6o3SW0tcFf/hLobIzDbzqel6eJQjBiuGOn2Wxmz549nDp16rLONYvFQm5uLhaLhXPnzvHf//3f3HbbbTecrKQoCm1tbZw/f57NmzcbNqSnqiptbW1s2bLllhciWa1W1q9fj9frJSoqSp+cdPbsWZxOJxUVFYZ0MCqKgtPppLGx0dA28DN16lQ2btxoWDyTyURVVRVNTU2cPXv2qjYwm30MGpTP0aM5bNzoZfnyk9hsFXi9n/9/UFWVpqYmmpubDW0Hf/tu2rTplnwlVdWHw5FCff0EIJLMzHI+/PAEQmjn+r59+zhx4oQhfUuKotDU1ERUVO/U8TBcEHw+HwMHDrzmfP4vf/nLrFu3joKCAtavX8+8efNQVfVzG8pf76ClpYVBgwbRZdDSMZPJRFFRERkZGVgsN2+fpaoqDoeDhoYGABYuXEh2drZuiJqUlERWVpYhJ62qqjQ3N3P+/HlD28BPfX09WVlZhsWzWCzU19eTkJBAdnb2VW2gqoLvfz+GTZvgzBmFAwcS+M53vHR0fP4Nq8lkQlVVOjs7DW0HRVEoLCwkMzMT9RbKTFksgmPHYnG7TZhMcMcdsWRmZqOqEVRVVZGSkkJKSoohHw6qqmI2m7H30syuXhGEYcOGMXTo0Gu+/+1vf5sf/OAHtLa2YrVaGTHic8oAXaC6upra2lpGjTLW3nvnzp2MGTPmlr0Lqqqq9E+U6dOnM3r0aABOnTpFTk4OI0eONCzXuro6KioqDG8DgLKyMvLz8w1xn/ZTXl5Odnb2dR+jxoyBL34RVq1SqarKIicnq1vVnSwWC06n0/B2+OSTT8jPz7/lu8XTp7X+A4sFZs5MJidHcxwvKCggNzfX0CpmMTExHDx40LB4l9LnVfcefPBBIiMjOXbsWNAPQZ44cYJz584B9MqFGsooCjz9tLa9Zw9cGLkNWlauhKYmiI2FnJxAZ3Pr9LkgpKen873vfQ/Q1LM+iGenfPbZZ5w7dw6bzUZmZmag0wk6br8dbrsNamq09Q3Bis8Hzc3a9mOPBTaXntLngmAymXjggQcA+Oijj9h7aQG8IKOkpASA+++/v9c6eUKZpCTw1xr5+GMI1rVvDQ3aCkfQfB+CmYAU6p4wYQJz586lo6ODXbt2BeWyaLvdrpu+jB8/Xlqm3QKqqi2LTkyEgweD16r93LmLdwjDhgU2l54SEEFISkriwQcfBLQ5CcXFxYFIo0fU1NTohWj8nYmSm2fUKHj4YW173TptbkKwsXs3HD+ubQf73LSACALA3XffzejRo2ltbWVfEBrtlZWVcfrCGt7BgwcHOJvgJSYG7rkHIiNh2TIoLAx0RjePfyb+rFnaOoZgJmCCkJeXx/Tp0wFtwVNvjav2FkVFRdjtdm6//XbS0tICnU5Qc8cdF1cHrlsXXMuiOzsvrtq8/Xa6NXTanwmYIFgsFubOnYvNZmPv3r1BtSza6/Xqw43jx48nOljnqfYTBg26KAjvvKN10gULra0XBWHoUDAbPrOnbwmYIADMmjWLiRMnAvDyyy8HMpWbwm63U3HBK2vYsGGyKIsBPPKIZjlWVhZczswVFVrtStAEIdgJqCDYbDZmz56NqqqsXbtWr43Y3zl//jxHjx4FYOjQobc03VVyOZMnw4QJ2vYLLwSP09Dp05qxalpa8K5wvJSAn8mLFi1i0KBBuFwu3n777UCn0y2qqqooLi4mKSmJIUOGBDqdkEBVYdEibZXg8eMQLNNT/FWa7rpLM1YNdgIuCKNGjWLq1KkAvP3227QFwbiTf7hx/PjxpKenBzib0OH++7XJSnY7LF8e6GxuTEfHRUEYNCh4lzxfSsAFAeCpp57CarVy9uxZPvroo0Cn87l4PB69StOgQYOIj48PcEahQ2IifOMb2vb27ZolWX+mrQ2OHdO2MzODf4QB+okgzJgxgyFDhtDS0sIrr7wS6HQ+l/b2dr3K86BBgxgwYECAMwotHntMm5tQWtr/q0XX1GjCBVqHaCjQLwQhIiJCrxZdWlrar4cgW1tb2bVrF4ChS1olGsOGaY8OnZ2waZNm2d5f8d/BTJwIoTJZtV8IAmgLhBITEykqKuL9998PdDrXpbq6mtbWVoYNG0Z+fn6g0wk5zGb46le17cOHtdJv/RV/laaMDK3KcyjQbwQhIyODJ554AtB8Chv66ewUf/9BWlqa7FDsJe64QxuC9N+S98eZix4PnDqlbaekaIVZQoF+Iwhms5lHHnkE0KpFb/c/nPUzPv30U0Cr8iwFoXdISoInn9S2t2yBCxrcr+jogDfe0LbT04N/hqIfw/8MRVFoaWmhubn5pvwETSYT6enpzJ49m+3bt7Nz505mzJiB1WqltbUVt9tNW1ubYW7NZrMZj8dDY2Mjkd3sHvb5fPooiNVqpaurixb/QvgLREZG0tHRQVtbGy0tLYaUdVNVlZaWFrq6urDb7YYvF4+Pj6ehocEwC7WIiIgetYHFAmPHmkhOjuPgQRNbtnh49FE7oGC32+ns7DT0XFBVFa/XS2NjY7cmmakqnD4dhdMZQ3KyYMwYB05nB+3tl7dfZGQkbreb1tbWm74erofJZKK1tdVQu7tL6RXX5d27d3Ps2LGbdplVVZWcC/5Tb7zxBikpKQwdOhSn04ndbmf16tWGlUlTFAWHw8HmzZu7dRL43W4LCgqIjo4mLi6O1atXX3Vx+k1hm5qaOHnypGFOu52dnbS0tLBmzRrDS8XdeeedbPB7iBuAqqo0NjZSV1dHSUnJTbeBovhwu22MG3cP27fH89JLzXi924iN7cDhaMflchl6LgA4nU42bNjQrQtNUQRHj44GpmC1dlFVdYjVq0/j8Vx+OamqSn19PXv27MFqtRp2LrS1tfWeQ5cwmBUrVojS0tJb/v2CggIxcuRIAYglS5YIIYSorq4WS5cuNSpFnZdeekm0t7d3e//Dhw8LRVFETk6O2L9//3X3W7NmjSgsLDQiRZ3a2lq9PYwmNzdX+Hw+Q2Nu2LBBFBQU9CjG228LoShCxMYKceyY9lpxcbFYtWqVARlezgsvvCA8Hk+393/lFSFAiGnThGhpuf5+y5YtE5WVlQZkeJGysjKxfPlyQ2P66Td9CH7GjBnDrAt1w3/961/jcDh67fboZjl06BBCCOLi4qQHQh9w993aV1sb9LdiX2+9pX2Pi4NQmpvW7wRBVVXmzZtHUlISJ06c6FdzEnbu3AnAgAEDGBgKE9f7OVlZl1eLbmzU3JoDjcMBJ05ofQl33RXobIyl3wkCwLRp0xh7wa3ytddeC3A2Gh6Phz179gBafpK+Yf58rVp0QwNs3qxdhIGmqkqrwWCzaaYooUQ/aN6rSUxMZM6cOaiqyurVqykrKwv4EuPa2lqcTieRkZFMmjQpoLmEE1dWi+7sDPxdQlWVVuU5Kio0ljxfSr8UBIBHHnmEQYMG0dbWxjvvvHNL5daMpKysTFZ5DgCKoi14io7WjEg+/VRgNgd2ptLOnZowRUVBdnZAUzGcfisIeXl5TJ48GSEES5cuDbhV+8GDB7Hb7VIQAsC8eRcfG95804zZHNhlhR9+qH0fNSo0ljxfSr8VBIBvfetbWK1W7HY7p/zzRAPE3r178Xq9jBkzRq5w7GMSEuDLX9a2jxyx0diYG7BcGhvB5dK2L9QbCin6tSD4rdqFEBw5ciRgebhcLurq6gC45557ApZHOPPoo9r04NZWG6dOBW6t8dmz4HRqnZuheKPYrwUhIiKCb33rW4BWNu24vxpGH1NXV6c7OcmiLIFhxAjNYg1MHD0aidMZmDxOn9YcnSwW7TEm1OjXggDwwAMPEB0dzYkTJwLmuVhUVKQXpZWCEBhUFb7+dW17/34IVG2fNWu0sm0JCaFjinIp/V4Q0tLS+M53vgNcrLbc1xw9epRz586RlJRERkZGnx9fonHbbdq4f12dNiehr5dFe71aHQaAv/u7vj12X9HvBcFsNnP//fcDsG3btoBUi/aXbJs/f76s8hxAUlIudi5u367VcOhLLq3yPGZM3x67r+j3ggCQm5vL4MGD6erqYvfu3X06BNna2qpXeR43bpys8hxAFAXuuMOL2ezm0KG+rxZ97hw0NWnbuYEb6OhVgkIQBgwYQF5eHgAvvvhin1aLrqmp0QvIjBo1qs+OK7k2aWmtjBqleZetXt231aJ37QqdKs/XIygEQQjB5MmTuf3223G5XPqagr6gvLyckpISQFZ57g9ERraQn1+KzQYrVvRttegL5TiYMyd0LNOuJCgEoauri7y8PO644w4AXn/99T4r6FJcXIzD4WDKlCmkpqb2yTEl18fj8TB5coe+qGjNmr7pXOzouFjU9QtfgFAt5xkUguDz+YiPj2fevHkkJiZy8ODBPpmodGmV5/z8fGJiYnr9mJLPx+PRbtf91aKXLeubatF2u9aHANr8g1DxULySoBAEgI6ODu655x7GjRsHwP/8z//0+jHtdrvusjx8+HA5wtAP8N8NLF6szQMoL7+4tqA3KS+/OPchVDsUIYgEwev1EhERwZw5czCZTHz44Yf6xdpbnD9/Xr8TGTJkSL9xbgp3urpg3Djt1h3gT3/S7hx6k7Iy7U4kOzv0ljxfStAIgp+HH36YzMxMHA5Hr89crK6upqSkhNTUVIYOHdqrx5J0H7+36iOPaEuQi4qgt/uZa2q071OmhEaV5+uhCGFsl8zatWspLi4mJibGEJdZ0DqSOjo6iI2NxWQy8dprr3Ho0CEyMzP58Y9/jNVqvWkHXkVRaG1tJTY29pqf/IqisG/fPv72t7+Rl5fH1772NRITE29ope13c46IiCAiIsKwNvB6vbhcLuLi4gyL6aeqqsrQsnSKouB0OjGbzURGRhqWr6IouN1u3G43cXExOBw2/uu/HqapKYoZM6p59NG1eL0CuPk7udbW1msW7lUUQVdXNGvX3s+OHenMmlXJl760FYvFyY0sSf0OyVarFbOBnQ4ul4u8vDwWLlxoWEwdo11bV6xYIU6fPi2EEMLn8/X4SwghKisrL3Nd3rZtm4iIiBA2m0289957t3QsIYR48cUXhcvluur3hRDC7XaL5557TgDiySefFG1tbd06jhBCrF69WnddNqoNLnVdNiLmpbGHDRsmvF6voTHXr18vjh49ami+QghRVFR0ieuyT/zqV5r78dixQlRU+IQQtxb3hRdeEF1dXdd4zyfq631i+nSfACGef157rTvHEUKId955R1RUVBh6LpSVlYl33333lq/Rz6NXHhn8n7iKovT469J4fqZNm8bw4cNpaWlhyZIlt3SsS3/nyt8HrRPz4MGDAGRnZ+seCDebr1FtcGX7GvUF2jwPo2Ner22NPRcUFi+GAQO0smrvv68At96+135PobZWYedObb/cXO217hynN9rBj+ilsdag60OAy6tFFxUVcfjwYcOP0dLSold5lv0H/ZdhwzSjErdbG23ojekpl1Z5DvXJqkEpCKAtNEpOTqa4uNjQqkN+qqurcTgcDB8+nDGhupIlBDCb4UKNYD79tHfWN/gHs9LTQ6fK8/UIWkFIS0vjqxfqhh84cIDz588bGt8/pDlw4EBZ1LWfM2UKTJoEtbXaKkgjK915vdooBmirLRMSjIvdHwlaQbBYLHzxi18EYP369XoRVqPwV3mWgtD/SU6Gxx/XtjdtgooK42K3t8Prr2vb6ekQ6otdg1YQQFuO/OCDDwKwZ88eOjo6DInr9Xp1gUlNTTV0yEhiPIoCM2Zok4YOH9ZWJRrF2bPaOoa0NJg+3bi4/ZWgFoSkpCTd9HTZsmWGzVysr6+nsLCQuLg4WaUpSBgxAu67T9tet04rt2YE/ruNpKTQ9FC8kqAWBICZM2cyevRozp07x+7duw2JWVVVhcfjwWazyRoMQUJMDMyapXUybtgARllmXDDLIi5Ou0sIdYJeEPLz87n7QkXQ3/zmN9jt9h7HPHr0KD6fj7i4OIaEopNmiDJrllZ8taMDVq0yJubf/qZ9t9lCv0MRQkAQABYsWEBKSgolJSUcOnSox/E++eQTAGJiYkhJSelxPEnfkJl5sVr0yy9f9C+4VdratDsEk0nrowgHQkIQ7rrrLt3e7JVXXulRLI/Hw/79+wHtcUQSXCxYADk5mvdhT6enVFdrE57i4rRJSeFASAhCQkIC8+bNw2Qy8caP+qkAABjASURBVMEHH/Soc7Gmpob29nYiIyO57bbbDMxS0hdMmaJ1MIJ2u9+TZdGVlZogREVpIhMOhIQgACxevJjMzEzsdjt//etfbzlOWVkZLpeLyMhI2aEYpDz9tHYRHzmiFXW5VT76SOuPkIIQhOTm5upDhCtXrsR5i7W+Dhw4gN1ul4IQxMydC0OHahWW3nzz1uN8/LH2PT8fIgNbcLrPCBlBAPjmN7+JxWLhzJkzt7y+wV/lecKECdJDMUiJj9cs1kCzPSstvfkYDQ3o9SMv1AkKC0JKEKZNm8a4ceNobW1lxYoVN71E1Ol00nDBsXPWrFm9kaKkj1i8WJvBWFqqTWe+WWpqQrvK8/UIKUGwWCx6HciTJ09SUFBwU79fV1enz2OQRV2Dm+HD4bHHtD6AbdtufuZicbFWts1sDo8Zin5CShAA5s2bR2xsLCdPnmTFihU39btFRUXU1dUBskpTsGMywVe+om3v3n3znYsbNmiCkJISPh2KEIKCkJ6ezjPPPANoKxZra2u7/bvHjh2jvr6e9PR0srOzeytFSR8xZYq2IKm+HrZs6f6yaCEuGq185Svao0e4YPgyPrPZzN69eykpKblp49NroSiaUeX58+f58MMPb2hyqqoqERERAOzYsYM333yTyZMn09XVddV+DoeDLVu2YLFYUBRFn6E4fPhwtm3bdkuFXU0mE2fPnsXlclFZWWlYGzidThobG7vVBjfL1KlT2XQrD9rXwWQyUVVVRVNTEzU1NYa0AWj/s6amJpqamm7YDoqieRnk5Axh586RrF8PY8Z8SmpqPV6vcsW+Wvtu3rwZs9lHc/NASkvHAVYcjjI2bSq+pepQJpOJ+vp69u3bx8mTJw2xPVMUhaamJqy9VDrKcEHw+XykpKSQkZFhyImgqioNDQ00NzeTnZ191YV9JSaTiTlz5rBv3z42bdrEsWPHuO+++4iKirosH5PJRGFhIRkZGVitVpqamnC5XIB2gdyqC7HFYqGmpobExESysrIMuXhVVaW5uZn6+vputcHNcv78eTIzMw2LZ7FYOHfuHAkJCYa1AWj/M0VR6Ojo6FY7RETAokXxfPwxnDgBZWXJTJhgAZTLLnBFUTh58uSFcwGam+Ow27UPg0mTBpCVlXlLpisWi4XKykpSUlJISUkx7HowmUyGrNm5Fr0iCMOGDTPUh7C6upra2tqbeq5fsGABmzZtYu3atfzqV7/Sq0dfys6dOxkzZgxWq5WioiIcF3qeZs6cqVeIuhVOnTpFTk4OI0eOvOUYV1JXV0dFRUWv9G2UlpaSn59/TUPXW6W8vJzs7GzD7ecsFgtOp7Pb7ZCTo81LeO01KCwczNCh2srIK/nkk0/Iz8/HZDLx0UcXbdPmzh1IevqtF2IoKCggNzfXUJv7mJgY3QDYaEKuD8HP7NmzGT9+PO3t7Wzfvv2G+5eWllJ4oZRwVlZWb6cn6SOiouCeeyA6GpYv1+4UrodfD/1VnufPh9jY3s+xPxGygjBixAimTJkCwKuvvnrDatElJSW4XC7uvPNO0sJh4XsYMW0a+JelvPfe9fdT1curPIfTDEU/ISsIJpOJ+fPnk5SUxOHDh69r1a4oCl6vVx9uHDNmjJyhGGJkZWkjDqDdJXyeH6/dDhdOBYYMAYul9/PrT4SsIADce++9+jPsb3/722vuo6oqdrud0gvzW2WV59Dk0Ue1CUaVlfDBB9ffr6zsoidjKFd5vh4hLQgDBgxgwYIFmM1mdu7cqV/0l+IfxfBXec7JyTG0c03SP5g06eJjw5//rFWQvhYVFdqEpCFDwmtCkp+QFgSAhQsXkpaWRmtrK3/z+2FdQXV1NaWlpaSnp5Mbjh8LYcIjj4DVqrkgXenM7J+3cPas9vNtt4V+UZZrEfKCkJeXpzsfvffee1eN33o8Hqov1OoaNWqU7FAMYebP16YiNzfDypWXv6co0Nl5sWxbVpZWMzLcCHlBgIvLoqurq9m8ebP+uqIodHV1UVZWBmhFXW02W6DSlPQy8fFwYe0bu3ZdXtBFUbQORX8puKwsbWJTuBEWgnDHHXcwevRoWlpaWLZs2WXvtbe3s2/fPkATBDnCENp8+cva3IKTJ2Ht2ouvK4o2urB3r7YwKlzr+4aFIEREROgLnk6cOKGXaVMURa/yrCiK7D8IA4YOhQcf1LwWt2+H1lbtdZ9PG4EAmDABwnX1e1gIAsDcuXNJTU2luLiYjRs3ApogVFdX43K5GDZsmKzyHAaYzfB3f6dt798P/hnAPt/FR4i0tPDsUIQwEoTU1FS9WvT+/ftpbm5GVVVZ5TkMmTwZ7rgDzp2DHTu013y+i9Oak5PDoyjLtQgbQbBYLNx/wRxvw4YNfPzxx5hMJr0GQ0pKihSEMCEl5aLn4vr12qOCx6PoVZ4zMrRpzOFIWP3Z48aNY+HChYC20rGpqYkdFz4i0tLSbsn/QBKcTJ8OgwbB0aOao1JzczY+n0JaWvhUaboWYSUIl1aLfueddygsLKSsrIz4+Himh0Otb4nOqFFw773a9qpVUFmZDigkJmpCEa6ElSAAzJgxg7Fjx1JbW8vJkyfxer3Ex8fLGgxhRnQ0zJ6trWbcuBGKizXLvLg4COcnx1sWhNraWgoLC/H0pFZWAMjPz+fOO+8E4LPPPgMgLi7OUEMXSXAwezZMnQouFxQUJAMK8fFapedgo6uri8LCwhsu878RNyUIXq+XY8eO8f3vf59/+qd/wmq1YjYbbrrU68yZM4fExETdMs1kMvWaR52k/5KefnFZdHu71n8UrI8LFouFhoYGFixYwPPPP8+5c+duycPxcwVBCIHT6aS4uJjly5czf/58xo0bx/Lly3niiScYMmTILf8BgaSxsVG3SwPNfv11fxezJKyoqbn8561btU7GYGT69Ok89NBD/PSnPyUtLY2nn36adevWUVlZidvt7laMa368CyEoLS1l27ZtrFmzhh07dtDZ2akrzhe+8AW6urpYt27dZSpkMpmoqamho6OD48ePG+Yy63A4qK+vZ/369T0y7FQUBZ/Px7vvvntZA3V2dvL222+TlZWFxWLpkRmmyWSiurqa1tZWQ52nXS4XDQ0NPW6Da+F0Olm3bp1h8fyuy/X19VRUVBjqutzS0kJLS0uP28Fk8lJfn86hQ7cBFxctlJfDb397mvb2z3A6e+aOYjKZqKurY9euXQwYMMCw66GtrY3Gxsar2sBkMpGamsqkSZM4ePAgb775Jm+++SZxcXE89NBDzJ07l9mzZ5Oamnrd+NcUBI/HQ1VVFSUlJQCMHDmS48eP6/0FpaWlvPvuuyiKctkf6fP5yMrK4sSJEzidTkN8BYQQREdHk5iYyMGDB1F7OEDst0m/kvr6etatW9fji83n85GRkYHD4aCtrc2wNrBaraSkpPDpp5/2uA2uxOl0svLK5X89wOfzkZ6eTnt7Oy0tLYblK4QgNjaW2NhY9u3b16O4iuKms3MSLS1juVQQTCaoqzvF22+/g8cT3aN8fT4f2dnZnDhxApfLZdi5EBMTg81mY//+/Ze1gdlsprm5mVOnTumv2Ww2RowYQWNjI4WFhYwfP56BAwdePxdxA9rb28XJkyfFK6+8In74wx+KnJwcMXDgQLFjx45r7r9ixQpRWlp6o7A3RVVVlVi6dKlh8TZv3izS09MFIACRmJgoVqxYYVj8NWvWiMLCQsPiCSFEbW2tWLJkiaEx/eTm5gqfz2dozA0bNoiCggJDYwohRHFxsVi1apVh8f70JyGio4XQyrMIMW2aEMXFhoUXy5YtE5WVlcYFFEKUlZWJ5cuXX/O9119/XaiqKiZOnCh+8YtfiPXr14uysjLR2dnZrdg37BG0Wq2MGjWKUaNG4fV6eeqpp1i1ahXPP/88SUlJjB07tqei1+fMmTOHtWvX8utf/5oJEyYwdepU7vUPSkvCiqefhrw8+OMfy5k3bzCzZilcw7E/KNi0aRNr1qzhj3/8I/PmzWPo0KE3fVdyU0MEJpOJ8ePHk5+fT1VVFZ2dnXi93qCc4Xf77bdz77338vWvf12OMIQxUVEwZw4UF2/le997KijPZQC3243NZuOVV17pkcnPLY0ZqqrK4MGDEUIEr/+gr5P2tlYqKs+QODAFk9tFlymGxKQ4IoL0T5LcOhazK9Ap9IiIiAimTJnS4+uxR709QSsGgLP2JEc3/YUJkx7nTxv3sWfVy/z8Bz/nrzvLMbZQmqS/4u2Es6fgk+1QdiadyhKFw4eh3q8NHjhfT9CcD0Zcj2E3ddlPTOZIkuNiiB5+P1/+8ly++L3vMiPyOL/6j7cobDVmmEzSvxE+KFoPTzwI24+nUlcBq/8Av/gj1Amo3wk/fgmawuh0CFtBoOMUZSXnSb1nMsMtAComRdDl7sRjwHixpP9jjoL0OLAMhtFjC7hznuDhWbDhRVhfAkXboTMBYsPoKgmjP/VyPKVHOd2scN/00UQB7af2sLZY4b5F8xhhC86OJcnNs2crqKMhI0G73fa0g9kKsWY43wrfng89m40QALzNnNi9gl8++mOWf1bFZ0uf50f/8L+ccNz4V4NvIYJBlB/9lGank9J1f+DHG+1UVDrI+9Yv+cHiu5A2q2FCHXxSDiMWQJwlAnsFrNwGQ74Is4aC83uQHoxrG0zxDL99OhOzX+U3b/yFH96/iJ/930xs3VC2MBWEcxxYvwdH4lie//3/Y0R0BD6hYDKbUIO3n1RykzSUQmU9eArgI/sCjm9WyXoQ3ngcBgJ0r+J8P0QlIiKN8XeNofJ1GxPvHUtqN6/08BSE5lI+KYPEnMHkWC2YzGbkQ0L4UfwJlMfCy7+Hmg9X8tQ3foAapPMQrsZLe7uFpLNtuG6iSyws+xDsRYcpaE4nJycbS1i2gIROOFgISeNhdCr4usyEUldyV+VBCjrjuUMtpLCsiZaz5+nOescwuxwEHU3HWfbGckpON+Jx2mlwh9GYkkTHXQefFcPYL0B6JHhD5TRwFPO///Er/nXFWSY+/CRzpjXx59+v5HSHSnfWbobdI4M5KoN7nvkDH3zTygdbPyA6pD4XJN3B54IP/gY7DsCEaVDlBJ8CIdF9FJnG3fMeoDMpl6FxNlJ/9gcy662MHJrUrb8vzARBwRyVSO64RHKBI0d2YQ2zeyQJKFa493uw9+sQEQPx0YAgND4aLPGM8te9B+LSRzDlJjwiw0wQLickTgDJTaOoMCARwrC48w2Rn48SiURHCoJEItGRgiCRSHSkIEgkEh1FCGOX9q1du5bi4mJiYmIMcZkFzfS1o6OD2NhYw2IqikJrayuxsbGG+jr4XaIjIiKIiIgwLF+v14vL5SIuLs6wmH6qqqoYZGBBAkVRcDqdmM1mIiMjDf2fud1u3G63YS7GflpbW4mPjzcsHlx0SDa6fonL5SIvL0+vU2okho8ydHV1sWjRIoYNG2aI/baqqlRVVbF7924ee+wxQy29X3rpJZ588kmioqIMO7lUVWXNmjWMGDGCUaNGGdYGtbW1bN26la9+9auGtQFoJ21eXh5FRUWGCaOqqmzYsIHs7GzGjRtn6P+suLiYkydP8tBDDxka94UXXuA73/mOoRZqqqqybNkypk6dyuDBgw07F8rKyjh06JABGV5Nrww7+q2hjbLfvvRENdKCXFEUVFVFURTD7xL88fp7G4Bm7e1vB6PojTbwx/XTG+eC0W3rjwvGngtG3yX6kX0IEolERwqCRCLRkYIgkUh0pCBIJBIdKQgSiURHCoJEItGRgiCRSHSkIEgkEh0pCBKJREcKgkQi0ZGCIJFIdKQgSCQSHSkIEolERwqCRCLRkYIgkUh0pCBIJBIdKQgSiURHCoJEItGRgiCRSHQMd11es2YNtbW1xMfHG+L7pigK7e3ttLS0kJGRYZixpqIoVFdXk5GRYaiPnqqq1NXVERMTY5gzsKIodHZ20tjYSGZmpqEmqwC7du1i2rRphsVTVZX6+nqsVqvhTtlOpxOHw0FaWpqh50JVVRVZWVmG+kqqqkpNTQ02m80wI19FUbDb7aSmpvLQQw8ZkOXlGG6y6vV6ue2228jJycHr9fY4nt9x+OjRo9x333243d2pcn9jzGYzy5cvZ9q0aURGRhoSEyAiIoItW7YwePBgcnNz8Xg8PY6pqirnz59n//79hraBnz/96U8899xzhsWLiIjgo48+IjU1lZEjRxrSBgAmk4ny8nLKysoMbQdVVVm+fDkzZ8409MMhIiKCDRs2kJ+fT2ZmpiHXg8lkoqqqisrKSgMyvBrDBUEIQXJyMqmpqYbF7OrqIjIykuTkZMNiAlgsFtLT07FarYbGjY6OJiEhgYEDBxoatzfaAKChoYH09HRDPx1jYmJ6pQ1aW1upra01vB3MZjPp6emG2rADWK1Ww68Hl8tFeXm5YfEuRfYhSCQSHSkIEolERwqCRCLRkYIgkUh0pCBIJBIdKQgSiURHCoJEItGRgiCRSHSkIEgkEh0pCBKJREcKgkQi0ZGCIJFIdKQgSCQSHSkIEolERwqCRCLRkYIgkUh0pCBIJBIdKQgSiUTHcAs1VVWpqqpCCGGYp2J9fT1Op5Py8nK6uroMyFLzpuvs7OT06dNEREQYEhM0Wza73U5NTQ0Wi8WwNmhqatKts4xqAz/Z2dmUlJQYFs9isdDS0oLFYiEmJsZQT8Wamhra2toMbQdVVXG73ZSUlBjqqWixWHA4HFRXV+N2uw0xhfUbtxqZ56X0iiBUVFTQ2tpqmMus32n3+PHjhlxgoOXZ2dlJcXGxoT56JpOJlpYWhBA4HA5DTgJFUXC5XLhcLkPbwM/gwYM5efKkYfFMJhPNzc243W7a29sNc0dWVZWWlhZaW1sNbQdFUXC73RQWFhrqK2kymXA4HFRUVNDQ0GDY9dDc3ExcXJwBGV4DYTArVqwQpaWlhsasqqoSS5cuNTSmEEK89NJLor293fC4a9asEYWFhYbGrK2tFUuWLDE0pp/c3Fzh8/kMjblhwwZRUFBgaEwhhCguLharVq0yPO4LL7wgPB6P4XGXLVsmKisrDY1ZVlYmli9fbmhMP7IPQSKR6EhBkEgkOlIQJBKJjhQEiUSiIwVBIpHoSEGQSCQ6UhAkEomOFASJRKIjBUEikehIQZBIJDpSECQSiY4UBIlEoiMFQSKR6EhBkEgkOlIQJBKJjhQEiUSiIwVBIpHoSEGQSCQ6UhAkEomO4SarAJ2dnXR1dRnitut3R/b5fPh8Pjo7Ow3IEMxmMz6fj/b2dgBDDDABIiMj8Xg8uN1uw9rAbwhrdBuAZtoZGRlJe3u7YQajl7aBx+MxzB3ZbDbjdrvxer2GtoOqqvq5YKThbmRkJF6vl87OTj3vnuK/How0g70URRh1JVxg7dq1nD59mgEDBhjmMut2u3G5XNhsNsMuXEVRaGxsJCEhwdDGVRQFu91OREQEVqvVsHw9Hg8Oh4OEhATDYvopKSlh+PDhhsVTFIW2tjbMZjNRUVGG/s86Ozvp6OggPj7e0HZoamoiMTHRsHig5dvS0kJ0dDQRERGGXQ8Oh4Pc3FwWLlxoQJZXYLRrq3Rdlq7LQkjXZT/SdVkikQQtUhAkEomOFASJRKIjBUEikehIQZBIJDpSECQSiY4UBIlEoiMFQSKR6EhBkEgkOlIQJBKJjhQEiUSiIwVBIpHoSEGQSCQ6UhAkEomOFASJRKIjBUEikehIQZBIJDpSECQSiY4UBIlEomO4yep7771HfX29YYaoiqLgcrlobGxk0KBB+Hw+A7LU4paVlTFo0CBDnXZNJhNnzpxhwIABxMXFGdYG7e3t1NfXM3jwYMPawM/OnTuZPn26YfFUVaWmpobo6GhsNpuh/7O2tjbsdjvZ2dmGuBj745aWljJkyBBDDXdVVaWqqorExERiYmIMOxdaWlpISUnhkUceMSDLK+IbLQj+f5iRKIqCyWQyxNL8UiwWi2EW4Zfit3g38sLtrTYAePjhh3nvvfcMjdkbbQDaRaaqalCdC16v13Cn7Li4OGJjYw2NCb1QlyE2NrZXEpX0Hg0NDWRkZPSa178keJB9CBKJREcKgkQi0ZGCEIY0NTVRU1Nz2WuKouDxeDhz5gwOhyNAmUkCjRSEMERVVd566y3Wr1+v/+x2u3njjTd4//33iYmJCXCGkkAhBSEMsdlsJCcn89RTT/GHP/wBl8vFM888w5///GcmTpwoOxfDGMOHHSXBQXNzM4sWLWLHjh36aw8//DArV64MYFaSQCPvEMKUhIQEFi9erA8Rp6en8+Mf/zjAWUkCjRSEMGbRokXk5OQAkJmZyZ133hngjCSBRgpCGJOamorNZgNg7ty5Ac5G0h+QghDmfOlLXyIuLo758+cHOhVJP0AKQpgze/ZsYmNjGT16dKBTkfQDpCCEOXl5eTz11FMkJCQEOhVJP0AOO0qorq4mOzs70GlI+gFSECQSiY58ZJBIJDpSECQSiY4UBIlEoiMFQSKR6EhBkEgkOv8fCOW+ojZTGp8AAAAASUVORK5CYII=)
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. Translation is 6 units right.
What is the pre-image of the points (12, 7) if it has moved 4 units to the right and 3 units up?
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. So the algebraic representation will be: (12,7) → (8,4).
What is the pre-image of the points (12, 7) if it has moved 4 units to the right and 3 units up?
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. So the algebraic representation will be: (12,7) → (8,4).
An algebraic translation when an image is changing its position 4 units to the left
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. So the algebraic representation will be: (x, y) → (x - 4, y).
An algebraic translation when an image is changing its position 4 units to the left
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. So the algebraic representation will be: (x, y) → (x - 4, y).
An algebraic representation of translation of a point 6 units to the right and 3 units up
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same.
An algebraic representation of translation of a point 6 units to the right and 3 units up
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same.
The image of the point (1, 2) after moving 5 units right is
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. The algebraic representation is: (1,2) → (6,2).
The image of the point (1, 2) after moving 5 units right is
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same. The algebraic representation is: (1,2) → (6,2).
The polygon before translation is
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, and its size remains the same. The polygon before translation is Pre-image.
The polygon before translation is
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, and its size remains the same. The polygon before translation is Pre-image.
If the image is moving right, the translation is for
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same.
If the image is moving right, the translation is for
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same.
In translation if the image moves vertically, then it moves
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same.
In translation if the image moves vertically, then it moves
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same.
In translation if the image moves to the right, then it moves
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same.
In translation if the image moves to the right, then it moves
In this question, we used the concept of translation and found out the points according to the condition given. We also understood the concept of the cartesian system and the coordinates. In translation, only the position of the object changes, its size remains the same.