国际学生入学条件
Applicants must have an undergraduate degree from an accredited institution with at least 12 credits in mathematics, including calculus. Students who do not meet these requirements may be admitted if they satisfy the university's requirements for admission. An undergraduate GPA of at least 3.0 on a 4.0 scale or equivalent is normally required.
IELTS - A minimum score of 6.5 with no sub-score lower than 6.0 is required for the IELTS exam, TOEFL IBT-79, PBT-550 ,TOEFL computer-based -213, Duolingo - 120
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IDP—雅思考试联合主办方

雅思考试总分
6.5
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雅思考试指南
- 雅思总分:6.5
- 托福网考总分:79
- 托福笔试总分:550
- 其他语言考试:Duolingo Test - 120
CRICOS代码:
申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
The Graduate Certificate in Biostatistics Essentials provides the groundworks for developing new statistical methods, as well as applying existing techniques, to interpret data about the medical and life sciences Biostatistics is because it is used widely in the pharmaceutical industry, the health-care industry and in medical schools.<br>The certificate allows the students to focus and dig deep into this specific topic, and start applying your knowledge sooner. Earn this certificate on our NJIT Newark campus. And youll learn from NJIT's distinguished professors and instructors. Statistical techniques with emphasis on applications in health related sciences, summarizing and displaying data, basic probability and inference, Bayes' theorem and its application in diagonostic testing, estimation, confidence intervals, and hypothesis testing for means and proportions, contingency tables, regression and analysis of variance, logistic regression and survival analysis, basic epidemiologic tools, use of statistical software.<br>Different sampling methods, simple random sampling, stratified sampling, ratio and regression estimates, cluster sampling, systematic sampling.<br>Statistical methods and issues in the design of clinical trials and analysis of their data, which include clinical trial designs for phases 1-4, randomization principle and procedures, analysis of pharmacokinetic data for bioequivalence, multi-center trials, categorical data analysis, survival analysis, longitudinal data analysis, interim analysis, estimation of sample size and power, adjustment for multiplicity, evaluation of adverse events, and regulatory overview.<br>Modeling time-to-event data in the presence of censoring and truncation, with emphasis on applications to the health sciences, including survival and hazard functions, censoring and truncation, parametric and nonparametric models for survival data, competing-risks, regression models including Cox proportional hazards model and time-dependent covariates, one and two sample tests, and use of appropriate statistical software for computations.
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