I analyzed all of my data from my experiment and I calculated the difference in Na, Mg, and P from the top of my samples vs. the bottom of my samples. The Mg and P have small differences in the samples with no MgCl(sample 1) and 50 mM MgCl(sample 4). They have much larger differences with 5(sample 2) and 10 mM MgCl(sample 3). The Na has an odd trend.
Here are the graphs of Sodium 589.592, Mg 279.553, and P 178.221. When finding the differences, I took the absolute value. The error bars are too small to be seen. The y axis has units of mM.
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAeMAAAEjCAIAAACO/f7bAAAaCElEQVR4nO3d72vb2J7H8fxd/hPKPOiTcuGWhemDqwfLXNjtfdJlacokM840LMaUTllyKYFtRaCFDUuph8H0J8UMIQSa0oapCaGYkpQWpzQmwRijfaD46yP5yJZsyTqS3i8u7L2pLB1lyScnX311zoIDADDbguM4d+/eLQMAzHP37t3zpC6Xyyn/vgAA6Lj5TFIDgLlIagAwHUkNAKYjqQHAdCQ1AJiOpAYA05HUAGA6khoATEdSA4DpSGoAMB1JDQCmI6kBwHQkNQCYjqQGANOR1ABgOpIasWlWSwsLCwsLC1bN/5VStZnq0IBsI6mLSAJ0IdYcHU3qmjW4hHxpzvy3GnjPIwdqvin+Yybe1NRX15x5+L3kl18BkdRF4/+Bj/Hn3sQ5dcDtekcU5qCgY8am9UxXH545dOAjt0jqYtFOcmtWUkmdvsENj7k/za+TkW+TfEGOCfXnQoirhzmz7/9BarQb9K1GkkjqQhmNhThlM6m1837frcj3Tb0z7RejXn2qM6tzbIO+10gQSV0ooZM6TNXWe5BVC1X90KZ58GFWbfQyI9cedzMRktr/Z8bwY/oiTojSzsSrT3lmZVZNUhcDSV0ontALEQNj0jrwqFiTulQardBqvxYUhVGqH4NRjWT3hDwNTstZkzrgzMqIqVQXBEldMKMB6/tZ10y7h58ZDVz5krZ4OnNSK1/0TvP99eOgtNT+QhmJN+1Rmil2wGO+iUkdfPVpzsyMuoBI6uLRdRKMFBW8Yeb/8vjabpxJrW2SUD47qVAQvm1ibBdc4GnG52WIq0c+szJOJtTFQVIXlb6nOuhZlu/r+sMSqFPPnNR+2pwLF+e+KLdqISorYa4e6czkdEGR1MXmq9EG5p43JCfNvA1O6tF6w2ghR1vvGfO9ixKZoZr7gs5Me15xkdSF58m/cHPqgCde2Uhq3+ADThCiSyb6lHr06hHOTGteoZHURedNqpC5pc2xaHVq5ZOaWe085tTjOvAmJ7Xmc2H6yUP8Bhh/78R0MZHURdKslgInaiMdFmPe2NN8Sdv0HO31vwSSulktBU5MR5tWdN0XclRN+9fD2JaNMFePemaK0wVFUhdJcJ+Bdobr55nM6RrQBp3OY9f9GNfskERST7yXMQPSvOGt/3ffefwV8DFXD3Hmca3rZHdBkNQFM5oeE98+DIyDkXm0+mah94iAR4/+DyZR/Ri5l0k9ytrDwnxHdNWPyVeffObxjXwkdSGQ1ABgOpIaAExHUgOA6UhqADAdSQ0ApiOpAcB0JDUAmI6kBgDTkdQAYDqSGgBMR1IDgOlIagAwHUkNAKYjqQHAdCQ1AJiOpAYA05HUAGA6khoATEdSA4Dp4kpqd6s39rcHgPjFk9TNaqlUrVokNQAkII6kblZLC1bNqZHUAJCEGJJ6kNAkNQAkYuakHubz5KS2bbs8sLq6WgYQjm3b0/x4Ii/KMyZ1zVrwKlWbES4MAJho1qRWRKt+kNQAEBJJDQCmizGpp7kwAGAikhoATEdSA4DpSGoAMB1JDQCmI6kBwHQkNQCYjqQGANOR1ABgOpIaAExHUgOA6UhqADAdSQ0ApiOpAcB0JDUAmI6kxrw13n26tr794OVB2gMBMoOkxlx1e/2LS08uLNYvLNa3339JezhANoRK6ma1FLxL4vAfFxYibPpCUhfTZuODG9MXFuuXV190znppjwjIgDBJXbPOA7hZLY1mdbNaCrvL7eiFUTTWrYYk9YXFemXzbdojAjIgUvWjZmkm1SQ1wtp+/8UNaCmAUAMBwohW/dAVN9Tqx4Tih23b5YGVlZUyCuZffnzopvP3P258/+PGeWrfqC2XV9Memuls257xRx2ZVo4yp25WS+PSWFscGX9hFMfR8anMo/cPv3V7/SuVV9RAgDAiJXVA/SPkv+oujOJY++1PN5evrm25X9k9aEt2N959Snd4gMlCJHXNkvitWePm1OP/VXthFES3179UfjYayrcf7UkfSPukm+IIAZOFmVMrlejhlHkQyzVr2KMX5ckiSV0oj7daksjdXl++rtZAbj58k+IIAZNFrH7EfWEUxA93/nDj+P7Tfd8/qTWQ57uHqQwPMBxJjcRJFl9ceqItcVADAcYjqZG45Y3X4+sb3V5f3oihBgKMIqmRrPZJV23OCzpsr/VVDqvvfJznCAHzkdRI1nq96ebvD3f+CHnkpfIzaiCAiqRGgrq9/uXVFyFnymoN5Pq9nfmMEMgEkhoJqu981DbnBaEGAmiR1EiQNOet18O22lMDAUaR1EiKTJCDmvO0ur2+5Ds1EMBFUiMpNx++cQN3eeN1pA/uH36TZVGpgQAOSY2EtE+6kra7B+2oH7//dF/m40fHp0mMEMgQkhqJkKid2JynpdZArq1vxz48IFtIasRPbc57vNWa7iRqDWTqkwD5QFIjfs93DyM15wWhBgK4SGrE7+ralpuwa7/9Oct5ur2+nIoaCIqMpEbM9g+/ydsrs0+EW5871EAAkhoxq2y+na45L8iDlwdSA2l97sRyTiBbYkjq4ZYw7PlSeGpz3vb7L3GdVmogsgcjUCizJ3XNOt87MdLW5CR1Psn8d7rmvCBqDeTBy4MYzwxkQozVjyg7k5PUOSXNeZuND/GemRoIiizO6sfEfclt2y4PrKyslJEv/1i+44bpd4u//1T+Jfbz/+XGpnv+v9zYjP3khrNte7ofT+RDOb45dbNaCpHW3gsjT66tb8fSnBfk6PiUGgiKKcakjlb/IKlzRm3OS6468XirRQ0EBTRzUtcsCeeaxZy6uGR/8bia84LIzP2HO3/M8gIkkCGzz6mHTXp06RVW56wndYnGu0+JXkutgdx/up/otQBDxFr9iH5h5MNm44MbnVcqr+ZwObUGMma/cyA3SGrE4ErlVULNeUGogaBQSGrMqvHuk8xwO2e9+Vz06Pj0UvkZNRAUBEmNWV2/t5Noc14Q2fj84tKTvdbXeV4amDOSGjNpfe5Ic978S8byS8K61aAGghwjqTGTtd/+THH96PZJV2og6/XwnUdAxpDUmF63159bc14QqYFcWKxTA0FekdSYnjTnXV59keIwqIEg90hqTM+61Zhzc55W+6Qra/hRA0EukdSY0vb7L9J60T7ppjsY2WOXGghyiaTGlJY3XrvJWNl8m/ZYHMdxbj58I+9JUgNBzpDUmMbR8WmKzXlaag3k9qO9tIcDxImkxjSkOc+ojQ3VGsjuQTvt4QCxIakRWbfXly7mtJrzglADQS6R1IhMlrK7vPrCtDSkBoJcIqkR2Q93/jB5aSRpSqEGgtwgqRHN7kHbnOa8IJXNt1IDmdvyfkByQiX1cFsXza4uyp4vETbnIqmzSprzbj58k/ZYAnXOelIDMaSJEJhFmKSWrRKb1dJoVjerpSi7cnkvjGxpn3RNa84LotZAtt9/SXs4wEyiVT90m4+T1AWyXm/KTitpj2UyqYFcXn1BDQSZFimpdUHtqX5MKH7Ytl0eWFlZKSNTfir/cvFGzc2+f1teS3s4ky2XV2XA3/+4kfZwZmLb9vQ/5ci+cvik1ua0SlscGX9hZIisL2pgc14Qef5JDQSZFjapm9XS5MeFE7N85MLIEGnOy9Z6dbcf7VEDQdaFSuqaFaqrI+Rh6oWRFXutr+Y352l1e33ZOt3kfhVgjBBJ7WnDk0a9QSzXrJF/inBhZIW8pb288TrtsUSm1kCe7x6mPRwgsgh16iQujExon3RlF66MvvWn1kCy9TcB4JDUCOP+0/0MNedpUQNBppHUmKDb68v7fo+3WmkPZ3rUQJBdJDUmkEWfM9ScF0Te3KEGgmwhqTHB1bUtN93Wfvsz7bHMqtvryy691+/tpD0cICySGuPsH36TisHR8Wnaw4mBtBteWKzXdz6mPRwgFJIa48jSGVlszgsiNZBL5WfUQJAJJDUCqc15eXoVmxoIMoekRqAHLw+y3pwXZK/1VX4JUQOB+UhqBJLmvM3Gh7THEj9pEqcGAvOR1NBrvPskC31kvTlPq9vry5pT19a30x4OMA5JDb1r69u5ac4Lsn/4TWogmX6pB7lHUkNDbc5rfe6kPZwESQ3k4tKTfLQhIpdIamjIekZ5as7TogaCTCCp4dc560lNoPHuU9rDSRw1EJiPpIbfZuODG1tXKq/SHsucSD8iNRCYiaSGn6wOmsvmvCCyvAk1EBgohqQe7gnDni/ZpzbnFWrXwdbnjtRAHrw8SHs4OXIeEKVq0/vfU1Ozwu8iaIzZk7pmnX/bI21NTlIb6vq9ndw35wVRayD57niJj3fvPglAJQzUXDQjI8OPItRG3/MRZ/UjytbkJLWJWp870py3f/gt7eGkQGogV9e20h5LJjSrJfmhb1ZLo9NlNewMCb6iJ/XkoLZtuzywsrJShmH+tnTfzam//vi/aY8lHdd/rny3+Lv7TfjXpfW0hzNk2/bUP5nb77/Is4dY/nOl8mqwWIqa1M5wI+zzNFRm3CXLKnm3xh5ulu2Zc1uW8qWAY6qD83om8b4jNZ8dd4aR49U/F6zq8D7lHpW7114r9ODDKMeV1JEm1LNfDrHr9vqFas4LIq0vuamBxBvT8s1xHGckqSUHZN4aMKdWPzec49YsdVI+6ZhhiWV07qv/rOM7w/CD+uOV80rANatWqeS5rPaz4QcfTjxJPcUfCSS1aSShLq++SHssKZM36fNRA5H6e4z/uf1oz3EcbVIrc2onMKmH8021GcGbqROPUae0o/NmzWe9Y1RPoT9eHfz5p5rVklU7fzh3/iXtZ8MPPpwYklr5YyACkto0smRzoZrztI6OT+XPi/tP99MejslGqx++7AxOak1ojCT1+GMGF9fMFMfVogOSWnO858TuITXLDWerNvpbafIAUkxq77Pf8PN5ktoo2++/yF+1LAHqOM7jrZZ8Q4r5cDUcT94oZYUQ1Q9NWHjjbeIxcnFt9SMwjLzDlOqH7njPgNwq+uB3g1Wtloa3OPLZ8IMPJ7Y6dVQktVGWN167wVTZfJv2WEwhNZAf7vyRy3Vf4xDQpTcxqR1vfSBopj3+GCXsxj5R9P3RP3xu6R/y6PHnX3T/t6/AHfKzkwcfBkkN5+j4tODNeVrUQGAOkhrO2m9/5ukBWoyogcAQJHXRdXv9S+VnNOcFkZc2qYEgRSR10cm08fLqC5JoVPukK7/J1utpLleBIiOpi07W0acUG6S+81Hq+Hutr2kPB0VEUhfa7kGb5rwwpAZi3Wrwlwfmj6QuNGnOu/nwTdpjMRo1EKSLpC6u9kmX5rzwqIEYIWIbcrgzxrJenqz/nAiSurjW603pakh7LNlw8+EbaiBenjdfxiZVTCuIahYa8Yt2lbBroLp36rtF94tj35CPCUldUN1e//LqCzd3BitYYoL2SVe+aQXcaUHH95rgmKRKKKkHpo3J0J9rVkslyxpdj8qy1LciE4tqkrqg5G95mvMieb57KDWQ3YN22sNJnTep1XU+PTNcz1rP3pU9NO9bj1l+eiQsB3wp6R9A0JnV1ZrVA0rVZnP4X+X2av734a2a9wXxxKKapC4oac7j+VhUUgO5UnlV+F9yuuqHujjRMLzGx5hnTX7d8tPKkkoTk1o/AN2y1P69w5QLKr9j1BWsPYtXe7+Q6KSapC6ivdZXmvOmptZABss0F5Z/In2+XvMwr9Sk0y8O6p38Tlp+Okz1Qz8A3Vk0y5oO/qv/TwVlfVT//1XPkNRTRZK6iGRWuLzxOu2xZBI1kAFPcLr/wxvJY5N6mGy6PJ02qQMGoD1LQMCPSerzf5ODmVMjGe2TriwRV+yUmUll8y01kNEdb8+3RZGcU/YZ0cSYZ23U4KSepfoxHIBuWeqROnWIpB5UfLQLmaae1DUrqAnHU6gKP0ySOi33n+7TnDe7zlmPGkhgl96wqKGEhmetZ9/HpYViwvLTsjOWX+ATRe0Dw6CJdKik9u4SoD9B7MIktfsLKKgEM2UnOkmdCrU57/FWK+3hZJtslHOp/CztsWCigByNL14N6afOXlLvHrSv39t58PIg6QtliBRYac6Lhbu0N+/iZ0FQkMYVsIkGdTxJPc3LQXNIamlEW9543TnrJX25TLi6tsWLG0DmzJ7UQ+M2mXQcx3Fs2y4PrKyslBNmLf2PPKC/dOP/Fn/+r6SvaLj//Lkq3xC+G9li2/YUP97IjXKMSR2pm3DS5eIh+065xcSCL6wj7Qo05wHZEmdSKw05YS88B/Wdj9KUdnHpyfPdw/lc1zRqc972+y9pDwdABGGS2rtRvK8jUX3HKPqm6POxe9CWxYUL+/70g5cHNOcBGRV+Tp3Ihefm6PjUutWQsF7eeF20zgdpzttsfEh7LACiKUpSO47TOevJHkvu1LI4S1403n2S+k/RfkUBOVCgpHbdfrQnYX159UVB9jq5tr5Ncx6QXYVLasdxHm+1JKyL8Ixx//Cb3G/rcyft4QCIrIhJ7Yw8Y7z/dD/FwSRN/oygOQ/IqIImteM4rc+dK5VXEtY3H77JZQG3c9aT5rzGu09pDwfANIqb1I7jdM56UsC9sFi/uraVv2eMm40Psjhn2mMBMKVCJ7XjON1eX33GeKXyKmfPGOXvBprzgOwqelK7ZOLpPmPMTZVAbc5jjSogu0jqc9vvv6jPGPMxA5X+cZrzgEwjqYf2D7+pzxgrm28z/Yyx9bkj95Kzkg5QNCS1R+esJys4u88Ys1s0kHUEr61vpz0WADMhqf26vb6sDuo+Y8zi2yLdXp/mPCA3SGo9WXnOXdg6c8uEyjPSy6sv0h4LgFmR1IEa7z7JtDRzzxhl4cBsDRuAFkk9ju8Z4+1He2mPKBTZM/vi0pP8vcsDFBBJPUH7pCs757pP58x/xri88VraV9IeC4AYxJPUNSviji/ZSWrHcbq9/s2HbySsrVsNk58xHh2f0pwH5MzsSe1u0xVls1vlwhly/+m++oxx96Cd9oj0pDnv6tpW2mMBEI+4qh/5T2rHcZ7vHqrPGB9vtdIekV+315c3LWnOA3Jjrklt23Z5YGVlpZxB//HzrYs3ahLWf1u6n/aIPP6+9M/zZ4k3aj+Vf0l7OIiNbdsz/Hgi88rMqaM6Oj5VnzFev7djzjNGGVi+90YAioaknka315f+CvcZ49HxadqDcnYP2jTnAblEUk9vvd5UnzHutb6mOx755XHz4Zt0RwIgXrMndbNaWhgKHdc5SGrHceo7H+UZ48WlJ/Wdj2mNpH3SpTkPyKu45tRTXjgH9lpf1YWt01oJWib4P9z5I5UBAEgOSR0D3zPG5Y3Xc17YutvrX1594V49xXk9gISQ1PHonPVkgxV3YjvPZ4z1nY+ycl6mdz8AoEVSx0neD3RDc27PGGVGv16P8lQXQEaQ1DF7vNVSnzE+3z1M+op7ra805wH5RlLHb/egrT5jTPolFFk9annjdaIXApAWkjoRrc8dWcvfbXBOqHzcPunKFN7YRaMAzIikTkrnrHdtfVt9xphEaUJW+KM5D8gxkjpZtx/tqc8Y430nRW3OM3BhPwBxIakTJ5vPug/9YlyM9PnuIc15QBGQ1POw/f6L+ozxwcuDWE57dW0r3RcjAcwHST0nrc8ddfPc2Z8x7h9+k7OZsJIfgOSQ1PPje8Z4dW1rloWtK5tvac4DCoKknqtury8Je2GxfqXyarpnjGpz3vb7L7GPE4BRSOoUqM8YL5WfTfGM8cHLA5rzgOIgqdPRePdJfca42fgQ6ePSnBf1gwCyiKROzf7hN/UZ4+1HeyGfMTbefZKeP5rzgCIIl9Q1K3hPF8+eL1Yt2oULrn3SlU67C4v1a+vbYZ4xymNJmvOAggiR1M1qaRDQyn9V/znaDorqhdHt9WWJJfcZY+tzZ8zxanPe+CMB5MbkpG5WS8pUeXRnW5I6BvKE0H3GOGatJXk9neY8oDhCJbWSxNqkDlv8sG27PLCyslKG4t+X//u7xd8lr/++9M/RY5bLq3LMP5bvzH+QSItt27P/tCO7yjMntefIou1NHq/9w2/S1OE+Y/QdIO19VyqvUhkhgFSESmpv9SN44jwuxvUXhk/7pKtunut7xii9IjTnAYUyOaknPVEcqlkRmj9I6iDdXn9547WEtXWr4S7roTbnzfIaOoDMCZHUnlK0JPEglocNfLoWvkkXRpD1etP3jFH2Pqc5DyiaUEmd3IUxxvPdQ3XzXAnueLcjAGA+ktpoe62v6jNGt3Kd9qAAzBtJbbqj41P1GWOMW8YAyAqSOgM6Zz33PcabD9+kPRYAKSCpAcB0JDUAmI6kBgDTkdQAYDqSGgBMR1IDgOlIagAwHUkNAKYjqQHAdCQ1AJiOpAYA05HUAGA6khoATBdHUg+3fYmw6QtJDQAhzZzUoXdZ1F4YADDRrEk9snN52KgmqQEgpBiSWsnmCUlt23Z5YGVlpQwgnFu3bk3x44ncKM8zqUcvnA/ci5m4F+RGDEntrX4M/0eYC+cD92Im7gW5MWtS80TR4V5Mxb0gN2ZOajegz4WdUDuO8+uvv053OQNxL2biXpAbMSQ1ACBRJDUAmI6kBgDTkdQAYDqSGgBMR1IDgOlIagAwHUkNAKYjqQHAdHlO6poVbXMDYw3fAs3+3eTpXhzHGdxQhLdzgSnkNalr1sKCVYuwtp/BatY0C6uYqWadZ1oO7sVxzteSrIZfmAyYTl6T2pWPpB7K0f3k4lbOV5KMsIQkMB2SOkPycDtS/chBtg0SmqRG4kjqzMjVzbiJnel8G+YzSY3EkdTZ4N2xIRcy/v+cmrXgleWbgfFI6gxwH4+mPYo4yMPRPN0Uc2okL69JrWxvkPXpjvdWsn0v6s1k+0ZUJDUSl9ekBoD8IKkBwHQkNQCYjqQGANOR1ABgOpIaAExHUgOA6UhqADAdSQ0ApiOpAcB0JDUAmI6kBgDTDZO6UqmUAQDmqVQq50kNADDZ/wPF7qcUFMSUEAAAAABJRU5ErkJggg==)
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