Question
The x-intercept of the equation 2y + 3 = 2x is
![2 over 3](data:image/png;base64,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)
![3 over 2](data:image/png;base64,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)
- 6
- 1
Hint:
An x-intercept is a point where the graph of a function or relation intersects with the x-axis of the coordinate system. To find the x-intercept set y = 0 and solve for x.
The correct answer is: ![3 over 2](data:image/png;base64,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)
Related Questions to study
The difference between x and y-intercepts is
![](data:image/png;base64,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)
The difference between x and y-intercepts is
![](data:image/png;base64,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)
x-intercept is same as the y-intercept and sum of the intercepts is 2. The equation of line will be
x-intercept is same as the y-intercept and sum of the intercepts is 2. The equation of line will be
x-intercept is twice of y-intercept and the sum of the intercepts is 6. The equation of line will be
x-intercept is twice of y-intercept and the sum of the intercepts is 6. The equation of line will be
The slope-intercept form is
The slope-intercept form is
The x-intercept of the line 2x + 3y = 10 is
The x-intercept of the line 2x + 3y = 10 is
The difference between x and y–intercepts is
![](data:image/png;base64,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)
The difference between x and y–intercepts is
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAPAAAACpCAYAAAAV1LCtAAARpklEQVR4Ae2dCdBNZRjHrVknCSW+kZaPhj5RI4mYNIUWI6MMJhWhfaqp0CjGkJZpGFtKKm2TNZXKIEtINaQohfaI0lgrLXia/zPz3u53u/d+313OPec85//O3O/cs73nff7P/X3vet63gjBQASoQWgUqhDblTDgVoAJCgPkjoAIhVoAAh9h5TDoVIMD8DVCBECtAgEPsPCadChBg/gaoQIgVIMAhdh6TTgUIMH8DVCDEChDgEDuPSacCBJi/ASoQYgUIcIidx6RTAQLM3wAVCLECBDjEzmPSqQAB5m+ACoRYAQIcYucx6VTALMCjR4+WcePG0cNUwLQCZgGuV6+eFBUVmXYejaMCZgEuLi6WkpISepgKmFaAAJt2L42zrgABtu5h2mdaAQJs2r00zroCBNi6h2mfaQUIsGn30jjrChBg6x6mfaYVIMCm3UvjrCtAgK17mPaZVoAAm3YvjbOuAAG27mHaZ1oBAmzavTTOugIE2LqHaZ9pBQiwaffSOOsKEGDrHqZ9phUgwKbdS+OsK0CArXuY9plWgACbdi+Ns64AAbbuYdpnWgECbNq9NM66AgTYuodpn2kFCLBp99I46woQYOsepn2mFSDApt1L46wrQICte5j2mVaAAJt2L42zrgABtu5h2mdaAQJs2r00zroCBNi6h2mfaQUIsGn30jjrChBg6x6mfaYVIMCm3UvjrCtAgK17mPaZVoAAm3YvjbOuAAG27mHaZ1oBAmzavTTOugIE2LqHaZ9pBQiwaffSOOsKEGDrHqZ9phUgwKbdS+OsK0CArXuY9plWgACbdi+Ns64AAbbuYdpnWgECbNq9NM66AgTYuodpn2kFCLBp99I46woQYOsepn2mFSDApt1L46wrQICte5j2mVaAAJt2L42zrgABtu5h2mdaAQJs2r00zroCBNi6h2mfaQUIsGn30jjrCoQG4GPHjsnLL78sb7zxRrl8UlxcLCUlJeW6lhdRgbAqEBqAf/vtN2natKlUqFBBxo8fX6beBLhMiXiBAQVCAzC03rZtm3Ts2FEh7tu3r+zZsyelCwhwSml4wpACoQIYuh8+fFjuvPNOhbh58+ayYcOGpO4gwEll4UFjCoQOYKf/M888I1WrVpUqVarIzJkz3eHYlgDHpOAXwwqEFmD4ZP369YJcGPXi22+/XXNn56tmzZqxEcuJwa1ZBUINMLzy66+/CurDgPiiiy6Sr776Sg4ePKgNXueee65Zx9EwKgAFQg+wc+Ojjz4qlSpVkoYNG8qZZ56pQNevX19WrlzpLuGWCphTwAzA8Mxjjz2m4CI3dp8GDRrIjz/+aM5xNIgKQAFTAN91110xcB3A2L766qv0NhUwqYApgO++++6kAE+ePNmk82gUFTAF8ObNm6VWrVr/g7hGjRqCbicGKmBNAVMAwzlr1qyRbt26aR8xGrMwdrply5YKdWJXkzVn0p7oKWAOYOdCDORo06aN7u7bt0/69++vEHfo0EG2b9/uLuOWCoRaAc8APnTokPbJHj16NO8C/fPPPxo3hlWmCskGcqCrCY1aderUkUWLFqW6lcepQGgU8Azgyy67TFq0aCGALT4cOXIkfrdc3xPv2b9/v9StW1eGDh2a8v5UQymXLFki6FoCyKNGjUp5P09QgTAo4AnAKKICkJEjR8Y0mDJlig57rFevnvTp00d++OGH2LlUXzAI44orrhDcg+Lw9OnTY5f269dPqlevnvKNpFQAIwI8u0uXLprGXr16ya5du2Lx8gsVCJMCngA8YcIEheP9999XLfAiPoBGjokuHXzv3LmzJOas8cL9+eefCu8DDzwgiK9ixYp6HxqpEObOnav72CYL6QDG9X///bfcd999Gsdpp50m69atSxYNj1GBQCvgCcDINatVqyZ79+5V49FwVLNmTcGsGgg9evRQcL7++uuU4gBujGl2AUVygD9r1iw9tHXrVt3Hq4XJQlkAu3tefPFFTRvinjZtmjvMLRUIhQKeAIy6b+PGjVUA1IHxHV05LowYMULhW7t2rTuUdguYASQg27hxo16LlmX8U0CXUbJQXoBx76ZNm/TNJcQ/ZMgQwewfDFQgDArkHeDff/9dXyho166d2o+W4lNOOUUuuOCCmB5jx45VGF1xOHYixRfUpQHXbbfdFrsCrdyoG2OGjmQhE4BxPxrGbrjhBn1O27Zt5csvv0wWLY9RgUApkHeAAWxRUZG0bt1aDUVds0mTJoJ6pgtuyOPHH3/sDqXcolgLeLt27VqqRRsAn3jiiXkD2CXA1d9r164tCxcudIe5pQKBVCDvAMPKVq1aaVeN6wMGfIBw586dKgJmi0Q3EIqqqAePGTNGt4kKzZ49W+/r3bt34iltfcZsHFddddX/zuFApjlwfCQrVqzQYj/SHN+SHn8Nv1OBICjgCcDXXHONVK5cWXbs2KE2rlq1SjAeGUVpwA0wXJfQjBkzdB8t1fHhl19+0eO4Fi/mo9sHxeWHHnpIL8O4Z5xDfTpZyAVgxId/Nq7hrGfPnrJ79+5kj+ExKuCrAp4AjDmqANfixYtjxqHxadiwYYJX/lavXh07DiBx7ZYtW2LH8AUt0MiZkQPiHtR/8XHzX7lnLFu2rNR9bidXgBEPShDoxkL6UA1gV5NTl9ugKOAJwD/99JP+6AcNGpTWTuSyGIwxfPjwtNclnkR3FKbPQSPWH3/8kXha9/MBsIv4lVdeiXU1YUAKAxUIigKeAAzj7rjjDmnfvr0OmEhlLOavQos0GroyCZgHC28aPfHEEylvyyfAeAhKCGeffbb+Yxo8eLCgEY2BCvitgGcAwzCMpnKDN/JpKIq2f/31V9oo8w0wHnbgwAEZOHCgQoyupsRif9oE8SQV8EABTwH2IL3ljtILgN3DJ06cqBBj8oB58+a5w9xSgYIrQICzlBwvWqC/27WEe1HSyDJpvC1CChDgHJyNxrrLL79cIcb4b85+mYOYvDUrBQhwVrL9dxPq4w8++KBC3KhRI3nvvff+O8lvVMBjBQhwngTGqLHjjz9eQUYdmYEKFEIBApxHlfECxHnnnacQ48WI+Nch8/gYRkUFYgoQ4JgU+fmC8d0333yzQowXOjDkk4EKeKUAAfZI2alTpyrEGGmWatYQjx7NaCOkAAH20NmYUqhp06YK8v333+/JoBYPk8+oQ6AAAfbYST///LNceeWVCjG6nMozmZ/HSWL0hhQgwAVy5ujRoxVivFLJJU8LJHoEHkOAC+jk+fPn66TyGL2V7kWMAiaJjwq5AgS4wA7ctm1brKtpwIABgsn5GKhAtgoQ4GyVy+G++K4mzFDy6aef5hAbb42yAgTYR+8/+eSTOvXQcccdJ4lTCvmYLD46RAoQYJ+dha4mzNiJejFm60xcS8rn5PHxAVeAAAfAQZha6Oqrr1aIL7nkEvn2228DkComIQwKEOAAeclNeF+/fn1JNVlfgJLLpARAAQIcACfEJ+H111/XCetRpMZ6xgxUIJ0CBDidOj6d++abb+TCCy/UInX//v3Z1eSTH8LwWAIcUC9hQkCsvIicGAvDffLJJwFNKZPlpwIE2E/1y/FsrFxRqVIlqVq1qmApVAYqEK8AAY5XI6DfP/roI50HG7kxVqlgV1NAHeVDsgiwD6Jn88g9e/ZIr169Yl1N6RZHzyZ+3hNOBQhwyPw2btw4hRhdTUuWLAlZ6pncfCtAgPOtaAHie/PNNwUAo0gNoBmiqwABDqnv0dXUoUMHhbhPnz66XnJITWGyc1CAAOcgnt+3Hj58WBu1kBM3b95c1q9f73eS+PwCK0CACyy4F4979tlnpVq1alKxYkXBd4boKECAjfh6w4YNmgsjN7711lvLXL0xG7N37dqlY7QxyMTPgHS8++67GS9L62eavXo2AfZKWR/i3bt3r/Tt21frxVgAffv27XlNRdeuXaVu3bqlFlXHWs1YIypdwAQGuGbHjh362blzZ7n7srF2NO6LnyQfy9fgH9XMmTPTPTYS5wiwQTc//vjj+gM/4YQT5J133smLhd9//73Gee+992p82L/22mvlpJNO0pFi+IeRamaRESNGSM2aNbWYj6J+jRo1BFMLlRUWLFggZ511lmDCA0wGOHnyZL3lyJEjcsYZZ0ibNm0iP1UvAS7rVxTS8wD35JNPVujwmmKu4emnn9a4li5dqlGhrn3jjTcKJiRwuT6mz00WsMwMwP3www8FRX00tqEBLl347rvvFFy81LF27Vrp1q2bPv+DDz7Q29w4cbTGRzkQYMPex3KnnTp10h8+ckuM5so2XH/99dpI5ua1Ri7oAt5dRpH2/PPPd4dKbQE6SgOZhClTpmicb731lt6GQSt4xqhRo3R/1qxZuv/aa69lEq25awmwOZeWNgh1SBR78eMvLi4WjKvOJlx88cVa/42vi7p43PKqw4YNc4dKbQEwnt+4cWMpKSmRhx9+uMwc2KUZOTYCiueIY8iQIbq/fPly3X/kkUdKPStqOwQ4Ih5//vnntUiKrqZsGn/Qz4xPfM4L6VC8rVy5sjRr1kzQoJUsrFq1Sp566imtw6LeChDHjx+f7NLYsXvuuUevc69RbtmyRfcHDx6s16xZs0b3XY4cuzFiXwhwhBy+ceNGbRQCQLfcckuZuWC8NFg2taioqNQ9yBXRKo269hdffBF/ecrvn3/+uYJ36aWXprwGJ0aOHKnXuQXTUfdFutEghrB69Wrdx4oXUQ4EOGLex0Ty/fr10x9/x44dBWsalyf06NFDc3CXywLYU089VVuHE1uf0Vh13XXXaQMX4sa1KMojTJo0SZ+Nxd4QXnjhBUGueujQId13f95++229bvjw4drSjOsBMIrOCAsXLtT96dOnu1siuSXAkXS7iOtqqlOnjixatKhMFVC/BUCuSItGLexXqVJF69bInbESI/p7J0yYoOfGjBmj8Xbu3Flz70aNGunxLl26CAZjIOAfA+JBg1t8wDvPaHjDuYYNG2pX1U033RTrNnLpRyt4lAMBjrD30bKL/lVAgoaodAEjn3Ad6rIIKNIi90R30rRp0/SD3BA5KVZkxDkMwEBAn/FLL72k16xYsUKP4c+xY8ekRYsW0r59+5QDO9AdhvhdUdrdjCI4iu8YJBLlQICj7H0RzfnQwgw4e/bsGcsZE2VBv22DBg2kXbt2cvTo0cTTWe3Pnj1bn7tp06aM7se82Ujv0KFDM7rP4sUE2KJXM7QJ9VNXRMYqEevWrUsaA3JbFH8PHDiQ9HymB5GLI2fPNCAXx8ivrVu3ZnqruesJsDmXZm8Q1meqVauW5m5Yt4kh+AoQ4OD7qKAp3Lx5sw62QBEVgyZ2796tC69hOCSGZLpW6IImig9LqYBZgDHooHXr1ikN54n0CrixxmgBBszug5cLchmSmf6pPJupAr4DjMYRtDBitE4+P+jWOP300/MaZz7TF+S4UAdG94zr4nHwuu2gQYMio+v+/fszZaqg1/sOMF4rcz8Mbv/L6ahFMLQI+syfvgOMwfEYp/vcc8/l9YPhfciF8x1vlOKbOHGijr5K/GeClxPmzJkTCW3RBhDk4DvAXomDuhrrwLmri9bo2rVrlyolnXPOOeUegpl7ChhDOgXMAoxX5/DqGkPuCqBlGiUP9L9iRJUDeurUqblHzhhyUoAA5yRfNG/+7LPPpFWrVporDxw48H8vIkRTFX+sJsD+6B76p6LtAvCifty2bVtBLs1QeAUIcOE1N/VE93ogJq2bP3++KdvCYAwBDoOXAp7GlStXSpMmTTQ3du/5BjzJZpJHgM240l9D8H5v9+7dFWJsE9/v9Td1dp9OgO36tuCW4TVDzFGFejEmsMPsGfl69bDgxoTkgQQ4JI4KUzLnzZsn1atX16lkMYUPg3cKEGDvtI10zJh6x00CH2khPDaeAHssMKOnAl4qQIC9VJdxUwGPFSDAHgvM6KmAlwoQYC/VZdxUwGMFCLDHAjN6KuClAmYBxlQwmGGRgQpYVsAswJiEza1kZ9mBtC3aCpgFONpupfVRUYAAR8XTtNOkAgTYpFtpVFQUIMBR8TTtNKnAv+vuz94gpikLAAAAAElFTkSuQmCC)
The y-intercept if the constant of proportionality is 0.2 is
The y-intercept if the constant of proportionality is 0.2 is
The sum of both the intercepts in the equation 4x + 2 = y is
A y-intercept is a point where the graph of a function or relation intersects with the y-axis of the coordinate system. To find the y-intercept, set x = 0 and solve for y.
An x-intercept is a point where the graph of a function or relation intersects with the x-axis of the coordinate system. To find the x-intercept set y = 0 and solve for x.
The sum of both the intercepts in the equation 4x + 2 = y is
A y-intercept is a point where the graph of a function or relation intersects with the y-axis of the coordinate system. To find the y-intercept, set x = 0 and solve for y.
An x-intercept is a point where the graph of a function or relation intersects with the x-axis of the coordinate system. To find the x-intercept set y = 0 and solve for x.