Program Description Detail

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{
    "id": 293652,
    "description_type": {
        "id": 5,
        "name": "Source Catalog Curriculum"
    },
    "description": "<h1>Track Prerequisites</h1><p>Students must have the following background and courses completed before applying to the Statistics &amp; Data Science, Data Science track MS program. These courses are: <a href=\"https://sciences.ucf.edu/math/course/mac-2311c-calculus-with-analytic-geometry-i/\">MAC 2311C: Calculus with Analytic Geometry I</a>, <a href=\"https://sciences.ucf.edu/math/course/mac-2312-calculus-with-analytic-geometry-ii/\">MAC 2312: Calculus with Analytic Geometry II</a>, <a href=\"https://sciences.ucf.edu/math/course/mac-2313-calculus-with-analytic-geometry-iii/\">MAC 2313: Calculus with Analytic Geometry III</a>, <a href=\"https://sciences.ucf.edu/math/course/mas-3105-matrix-and-linear-algebra/\">MAS 3105: Matrix and Linear Algebra</a> or <a href=\"https://sciences.ucf.edu/math/course/mas-3106-linear-algebra/\">MAS 3106: Linear Algebra</a>. These pre-required courses are basic undergraduate courses from the Math department.</p><h1>Degree Requirements</h1><div><section><header data-test=\"grouping-0-header\"><div><h2 data-testid=\"grouping-label\"><span>Required Courses</span></h2></div><div><span>24</span><span>Total Credits</span></div><div><div><button aria-label=\"Collapse\"><i></i></button></div></div></header><div><div><ul><li><span>Complete <!-- -->all<!-- --> of the following</span><ul><div><span></span><li><span>Complete <!-- -->all<!-- --> of the following</span><ul><li data-test=\"ruleView-A.1\"><div data-test=\"ruleView-A.1-result\">Complete the following: <div><ul style=\"margin-top:5px;margin-bottom:5px\"><li><span><a href=\"#/courses/view/60ca8154a38edffc2a3ecb25\" target=\"_blank\">STA5104</a> <!-- -->-<!-- --> <!-- -->Advanced Computer Processing of Statistical Data<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8158a8d2fb2f1e2d858a\" target=\"_blank\">STA6714</a> <!-- -->-<!-- --> <!-- -->Data Preparation<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8154a8d2fb8bba2d8588\" target=\"_blank\">STA6238</a> <!-- -->-<!-- --> <!-- -->Logistic Regression<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815802fd3ad7f86d8991\" target=\"_blank\">STA6326</a> <!-- -->-<!-- --> <!-- -->Theoretical Statistics I<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815ba38edf3fb73ecb2e\" target=\"_blank\">STA6327</a> <!-- -->-<!-- --> <!-- -->Theoretical Statistics II<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815402fd3a04716d898d\" target=\"_blank\">STA6236</a> <!-- -->-<!-- --> <!-- -->Regression Analysis<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li></ul></div></div></li><li data-test=\"ruleView-A.2\"><div data-test=\"ruleView-A.2-result\">Complete at least <span>1</span> of the following: <div><ul style=\"margin-top:5px;margin-bottom:5px\"><li><span><a href=\"#/courses/view/60ca8154a8d2fb7d132d8586\" target=\"_blank\">STA5703</a> <!-- -->-<!-- --> <!-- -->Data Mining Methodology I<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/631f42a13e0e0c8bb7e9a19e\" target=\"_blank\">STA6366</a> <!-- -->-<!-- --> <!-- -->Statistical Methodology for Data Science I<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li></ul></div></div></li><li data-test=\"ruleView-A.3\"><div data-test=\"ruleView-A.3-result\">Complete at least <span>1</span> of the following: <div><ul style=\"margin-top:5px;margin-bottom:5px\"><li><span><a href=\"#/courses/view/60ca8158a38edf5c413ecb2a\" target=\"_blank\">STA6704</a> <!-- -->-<!-- --> <!-- -->Data Mining Methodology II<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/633f1f7b1ca9b32accfc56e9\" target=\"_blank\">STA6367</a> <!-- -->-<!-- --> <!-- -->Statistical Methodology for Data Science II<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li></ul></div></div></li></ul></li></div><li data-test=\"ruleView-B\"><div data-test=\"ruleView-B-result\"><div>\nNote: STA 5703/STA 6366 and STA 6704/STA 6367 both require research projects that fulfill the independent learning requirement for the program.\n</div></div></li></ul></li></ul></div></div></section><section><header data-test=\"grouping-1-header\"><div><h2 data-testid=\"grouping-label\"><span>Elective Courses</span></h2></div><div><span>6</span><span>Total Credits</span></div><div><div><button aria-label=\"Collapse\"><i></i></button></div></div></header><div><div><ul><li><span>Complete <!-- -->all<!-- --> of the following</span><ul><li data-test=\"ruleView-A\"><div data-test=\"ruleView-A-result\"><div>\nSelect electives from the following courses. No more than one Computer Science (COP prefix) course can be selected.\n\nOther courses may be included in a Plan of Study with departmental approval. Other electives can be used at the discretion of the student advisor and/or Graduate Coordinator.\n</div></div></li><li data-test=\"ruleView-B\"><div data-test=\"ruleView-B-result\">Complete at least <span>2</span> of the following: <div><ul style=\"margin-top:5px;margin-bottom:5px\"><li><span><a href=\"#/courses/view/60ca6a74e6bc794bfe73e4ab\" target=\"_blank\">COP5711</a> <!-- -->-<!-- --> <!-- -->Parallel and Distributed Database Systems<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca6a7102fd3affb66d8346\" target=\"_blank\">COP6730</a> <!-- -->-<!-- --> <!-- -->Transaction Processing<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca6a71714b5fb749521ffe\" target=\"_blank\">COP6731</a> <!-- -->-<!-- --> <!-- -->Advanced Database Systems<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8154a8d2fb7e6f2d8583\" target=\"_blank\">STA5205</a> <!-- -->-<!-- --> <!-- -->Experimental Design<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8154a8d2fb78992d8587\" target=\"_blank\">STA5505</a> <!-- -->-<!-- --> <!-- -->Categorical Data Methods<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8154a38edf2b133ecb26\" target=\"_blank\">STA5825</a> <!-- -->-<!-- --> <!-- -->Stochastic Processes and Applied Probability Theory<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/64ef74d285f57171e920fdd5\" target=\"_blank\">STA6106</a> <!-- -->-<!-- --> <!-- -->Statistical Computing I<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8154e6bc7991da73ec3d\" target=\"_blank\">STA6226</a> <!-- -->-<!-- --> <!-- -->Sampling Theory and Applications<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8154e6bc794fc973ec43\" target=\"_blank\">STA6237</a> <!-- -->-<!-- --> <!-- -->Nonlinear Regression<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815b5a1583748b9e74fe\" target=\"_blank\">STA6507</a> <!-- -->-<!-- --> <!-- -->Nonparametric Statistics<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815860402bed76ae78d7\" target=\"_blank\">STA6707</a> <!-- -->-<!-- --> <!-- -->Multivariate Statistical Methods<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca81589d7535760587739b\" target=\"_blank\">STA6857</a> <!-- -->-<!-- --> <!-- -->Applied Time Series Analysis<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/6212ec08833bc229d163688c\" target=\"_blank\">STA6705</a> <!-- -->-<!-- --> <!-- -->Data Mining Methodology III<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca6ba76b6b62af714001ed\" target=\"_blank\">FIN6406</a> <!-- -->-<!-- --> <!-- -->Strategic Financial Management<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/64ef83cd0bd2ff5b1be968be\" target=\"_blank\">STA6107</a> <!-- -->-<!-- --> <!-- -->Statistical Computing II<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815b5a15837e129e74fd\" target=\"_blank\">STA6329</a> <!-- -->-<!-- --> <!-- -->Statistical Applications of Matrix Algebra<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/631f432833d7637a3cd3fe59\" target=\"_blank\">STA6246</a> <!-- -->-<!-- --> <!-- -->Linear Models<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8158e6bc794b6c73ec4c\" target=\"_blank\">STA6346</a> <!-- -->-<!-- --> <!-- -->Advanced Statistical Inference I<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca81589d7535045f87739d\" target=\"_blank\">STA6347</a> <!-- -->-<!-- --> <!-- -->Advanced Statistical Inference II<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca81585ada370939eca0cf\" target=\"_blank\">STA6662</a> <!-- -->-<!-- --> <!-- -->Statistical Methods for Industrial Practice<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/6169a86003f6422fdb4a489e\" target=\"_blank\">STA6709</a> <!-- -->-<!-- --> <!-- -->Spatial Statistics<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815ba38edfc77c3ecb2f\" target=\"_blank\">STA7722</a> <!-- -->-<!-- --> <!-- -->Statistical Learning Theory<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815b5a15833cc99e7500\" target=\"_blank\">STA7734</a> <!-- -->-<!-- --> <!-- -->Statistical Asymptotic Theory in Big Data<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/6214218c97a11c6ad29cec33\" target=\"_blank\">STA5738</a> <!-- -->-<!-- --> <!-- -->Data and Analytical Methodology for Metropolitan and Regional Areas<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca81545a158313c29e74f3\" target=\"_blank\">STA6223</a> <!-- -->-<!-- --> <!-- -->Conventional Survey Methods<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8154a38edf32093ecb23\" target=\"_blank\">STA6224</a> <!-- -->-<!-- --> <!-- -->Bayesian Survey Methods<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca8158e6bc79cbb773ec49\" target=\"_blank\">STA7239</a> <!-- -->-<!-- --> <!-- -->Dimension Reduction in Regression<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca81589d7535808687739c\" target=\"_blank\">STA7348</a> <!-- -->-<!-- --> <!-- -->Bayesian Modeling and Computation<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca815ba38edf22893ecb30\" target=\"_blank\">STA7719</a> <!-- -->-<!-- --> <!-- -->Survival Analysis<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca81585ada372407eca0d0\" target=\"_blank\">STA7935</a> <!-- -->-<!-- --> <!-- -->Current Topics in Big Data Analytics<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/60ca6a636b6b62568940006e\" target=\"_blank\">CNT5805</a> <!-- -->-<!-- --> <!-- -->Network Science<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li><li><span><a href=\"#/courses/view/654e612268b04a9ff77bf149\" target=\"_blank\">STA5176</a> <!-- -->-<!-- --> <!-- -->Introduction to Biostatistics<!-- --> <span style=\"margin-left:5px\">(3)</span></span></li></ul></div></div></li></ul></li></ul></div></div></section><section><header data-test=\"grouping-2-header\"><div><h2 data-testid=\"grouping-label\"><span>Thesis/Nonthesis Option</span></h2></div><div><span>6</span><span>Total Credits</span></div><div><div><button aria-label=\"Collapse\"><i></i></button></div></div></header><div><div><ul><li><span>Complete <!-- -->1<!-- --> of the following</span><ul><div><span>Thesis Option</span><li><span>Complete <!-- -->all<!-- --> of the following</span><ul><li data-test=\"ruleView-A.1\"><div data-test=\"ruleView-A.1-result\"><div>For this option, the MS degree requires a total of at least 36 credit hours comprised of at least 30 credit hours of course work and 6 credit hours of thesis. This includes the 24 credit hours of the core courses, 6 credit hours of `Elective’ courses, and 3-6 credit hours of a two-course sequence. No more than 6 credit hours of independent study or directed research may be credited toward the degree. \nIt is strongly recommended that the student select a thesis adviser and establish a program of study by the completion of the core courses. With the help of a thesis adviser, the student will form a thesis committee of three members, of which at least two must be from the Department of Statistics and Data Science. An oral defense of the thesis is required. </div></div></li><li data-test=\"ruleView-A.2\"><div data-test=\"ruleView-A.2-result\">Earn at least <span>6</span> credits from the following: <div><ul style=\"margin-top:5px;margin-bottom:5px\"><li><span><a href=\"#/courses/view/6418564d1c7d19dd18aaa7a2\" target=\"_blank\">STA6971</a> <!-- -->-<!-- --> <!-- -->Thesis<!-- --> <span style=\"margin-left:5px\">(1 - 99)</span></span></li></ul></div></div></li></ul></li></div><div><span>Nonthesis Option</span><li><span>Complete <!-- -->all<!-- --> of the following</span><ul><li data-test=\"ruleView-B.1\"><div data-test=\"ruleView-B.1-result\"><div>Nonthesis students will take an additional 3 credit hours of electives and 3 credit hours of independent study for a research project. The electives should be chosen in consultation with the graduate program director. This will consist of 24 credit hours of the core courses, and 9 credit hours of elective courses, and 3 credit hours of independent study for a research project. \nIt is strongly recommended that the student contacts the academic adviser, Graduate Coordinator, and establish a program of study by the completion of the core courses. In addition, students in the nonthesis option are required to complete the research project based on the core courses. The student will choose a research advisor and write a research project report under that person&#x27;s advice. An oral presentation of their research project is required.\n</div></div></li><li data-test=\"ruleView-B.2\"><div data-test=\"ruleView-B.2-result\">Earn at least <span>3</span> credits from the following types of courses: <div>Courses listed in &quot;Elective courses&quot; above.</div></div></li><li data-test=\"ruleView-B.3\"><div data-test=\"ruleView-B.3-result\">Earn at least <span>3</span> credits from the following: <div><ul style=\"margin-top:5px;margin-bottom:5px\"><li><span><a href=\"#/courses/view/6418678edcd1aa1ffe0829c7\" target=\"_blank\">STA6908</a> <!-- -->-<!-- --> <!-- -->Directed Independent Studies<!-- --> <span style=\"margin-left:5px\">(1 - 99)</span></span></li></ul></div></div></li></ul></li></div></ul></li></ul></div></div></section><h3>Grand Total Credits:<!-- --> <strong>36</strong></h3></div><h1>Application Requirements</h1><h1>Financial Information</h1><p>Graduate students may receive financial assistance through fellowships, assistantships, tuition support, or loans. For more information, see the College of Graduate Studies <a href=\"https://funding.graduate.ucf.edu/\" target=\"_blank\">Funding website</a>, which describes the types of financial assistance available at UCF and provides general guidance in planning your graduate finances. The Financial Information section of the Graduate Catalog is another key resource.</p> <p><strong>UCF Student Financial Assistance</strong><br />Millican Hall 120<br />Telephone: 407-823-2827<br />Appointment Line: 407-823-5285<br />Fax: 407-823-5241<br /><a href=\"mailto:finaid@ucf.edu\">finaid@ucf.edu</a><br /><a href=\"http://finaid.ucf.edu/\" target=\"_blank\">Website</a></p><h1>Fellowship Information</h1><p>Fellowships are awarded based on academic merit to highly qualified students. They are paid to students through the Office of Student Financial Assistance, based on instructions provided by the College of Graduate Studies. Fellowships are given to support a student's graduate study and do not have a work obligation. For more information, see <a href=\"https://graduate.ucf.edu/fellowships/\" target=\"_blank\">UCF Graduate Fellowships</a>, which includes descriptions of university fellowships and what you should do to be considered for a fellowship.</p> <p><strong>Grad Fellowships</strong><br />Telephone: 407-823-0127<br /><a href=\"mailto:gradfellowship@ucf.edu\">gradfellowship@ucf.edu</a><br /><a href=\"https://funding.graduate.ucf.edu/\" target=\"_blank\">Website</a></p><div> <p>All MS students must have an approved <strong>Plan of Study (POS)</strong> developed by the student and advisor that lists the specific courses to be taken as part of the degree. Students must maintain a minimum GPA of 3.0 in their POS, as well as a &quot;B&quot; (3.0) in all courses completed toward the degree and since admission to the program.</p> </div>",
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