Data Template 2.6.1: Courses and activities through which competencies are met Biostatistics MS
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1 Data Template 2.6.1: Courses and activities through which competencies are met Biostatistics MS Core Competencies Courses and other learning experiences by which the is met Assessment of the Recent program changes related to this assessment Moved the MS to the end of the 1st year rather than the 2nd year, to allow for ample time to work on the MS thesis. This also allows for students to retake the exam within a few months if they fail and still complete the program in a timely manner. Also modified the MS to remove the multiple choice component and make both parts be short answer with one part theory and one part applied. Address health problems by appropriate problem definition, study design, data collection, data management, statistical analysis, and interpretation of results. Demonstrate mastery of the BIOST 2042 Introduction to Statistical Methods 2 (P) and Applications (R) BIOST 2093 SAS for Data Management and Analysis (P) BIOST 2094 Statistical Computing and Data Analysis Using R (R) BIOST 3023 Geographic Information System and Spatial Data Analysis (R) MS COMP EXAM (P) BIOST 2025 Biostatistics Seminar (R) The thesis will be evaluated to determine whether the student has demonstrated a level of using a score as judged by a committee of three faculty members. Score as follows: Does not meet level of Does meet level of Assessment is done at the time of the thesis defense only. Master s comprehensive exam is designed to test Moved the MS
2 theory underlying statistical methods. Understand and implement innovative statistical approaches. BIOST 2043 Introduction to Statistical Methods 1 (P) BIOST 2044 Introduction to Statistical Theory 2 (P) BIOST 2066 App lied Survival Analysis: Methods and Practice (R) BIOST 2078 Introduction Genomic Analysis 2: Theory and Practice (P) BIOST 2081 Mathematical Methods for Statistics (R) BIOST 2096 Numerical Methods Biostatistics (P) BIOST 3023 Geographic Information System and Spatial Data Analysis (P) MS COMP EXAM (P) INTERNSHIP (R) BIOST 2042 Introduction to Statistical Methods 2 (P) BIOST 2043 Introduction to Statistical Methods 1 (R) BIOST 2044 Introduction to Statistical Theory 2 (R) BIOST 2046 Analysis of Cohort Studies (P) BIOST 2049 Applied Regression Analysis (P) BIOST 2052 Multivariate Analysis (P) mastery of basic statistical theory and applications. thesis preparation and to the end of the 1st year rather than the 2nd year, to allow for ample time to work on the MS thesis. This also allows for students to retake the exam within a few months if they fail and still complete the program in a timely manner. Also modified the MS to remove the multiple choice component and make both parts be short answer with one part theory and one part applied. Modified the course BIOST 2093 to be a SAS programming class. In the past, this course was based on several different programming packages (mainly SPSS, SAS, Minitab). We have restructured this course to reflect the necessary
3 Apply research design principles to problems in public health. BIOST 2078 Introduction Genomic Analysis 2: Theory and Practice (P) BIOST 2081 Mathematical Methods for Statistics (R) BIOST 2093 SAS for Data Management and Analysis (P) BIOST 2094 Statistical Computing and Data Analysis Using R (P) BIOST 2096 Numerical Methods Biostatistics (P) BIOST 2098 Agent Based Modeling (P) BIOST 3023 Geographic Information System and Spatial Data Analysis (P) BIOST 2041 Introduction to Statistical Methods 1 (R) BIOST 2046 Analysis of Cohort Studies (P) and Applications (R) BIOST 2066 App lied Survival Analysis: Methods and Practice (R) Comp Exam, MS thesis preparation and material needed for the 1st SAS certification exam so that our students can hopefully be SAS certified when they graduate. The department will also pay for one attempt of the 1st SAS certification exam. Allowed the use of an internship experience to be the basis of the MS thesis.
4 Recognize strengths and weaknesses of approaches, including alternative designs, data sources, and analytic methods. Communicate biostatistical BIOST 2096 Numerical Methods Biostatistics (R) BIOST 3023 Geographic Information System and Spatial Data Analysis (P) MS THESIS (R) BIOST 2042 Introduction to Statistical Methods 2 (P) BIOST 2046 Analysis of Cohort Studies (P) BIOST 2056 Introduction to Diagnostic Test Evaluation and ROC Analysis (P) BIOST 2081 Mathematical Methods for Statistics (R) BIOST 2093 SAS for Data Management and Analysis (R) BIOST 2094 Statistical Computing and Data Analysis Using R (R) BIOST 2096 Numerical Methods Biostatistics (R) BIOST 3023 Geographic Information System and Spatial Data (R) MS COMP EXAM (P) Comp Exam, MS thesis preparation and Students must take a consulting practicum. As
5 analyses to individuals with varying degrees of statistical knowledge. Determine the data best suited to address public health issues, program planning, and program evaluation. BIOST 2058 Scientific Communication Skills (P) BIOST 2083 Linear Models (R) BIOST 2093 SAS for Data Management and Analysis (R) BIOST 2094 Statistical Computing and Data Analysis Using R (R) BIOST 3023 Geographic Information System and Spatial Data (R) BIOST 2025 Biostatistics Seminar (R) BIOST 2041 Introduction to Statistical Methods 1 (R) and Applications (R) BIOST 2066 App lied Survival Analysis: Methods and Practice (R) part of the course they are required to meet and interact with clients. Communication skills evaluated at et the completion of the course by course coordinator using following scale: 1=Does not meet level of 2=Does meet level of 3=Above level of. thesis preparation and Allowed the use of an internship experience to be the basis of the MS thesis.
6 BIOST 2083 Linear Models (R) BIOST 2096 Numerical Methods Biostatistics (R) BIOST 3023 Geographic Information System and Spatial Data (P) MS THESIS (R) INTERNSHIP (R) P=Primary, R=Reinforcing
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