Statistics I (PHARM 3040)

Part one of two. Course is designed to teach graduate students standard and advanced statistical methods of data analysis. Major topics covered will be descriptive statistical methods, probability, the most widely used discrete and continuous distributions, parameter estimation techniques, hypothesis testing, contingency tables, regression methods, multi-sample inference, design and analysis techniques for epidemiological data including power calculations, nonparametric techniques, and survival analysis. Introcution to multivariate statistical analysis will include applications of latent vaiable modeling. Students will be taught to apply statistical software packages, such as JMP, SPSS, SAS, or other appropriate programs to real data.

Competencies

* Asterisk denotes properties specific to the Clinical Pharmaceutical Sciences track

  • Critique clinical and scientific evidence derived from literature.
  • Interpret primary research literature within the pharmaceutical sciences.

  • Generate a relevant biomedical, clinical, public health, or translational research hypothesis.
  • *Defend the clinical and public health implications of a given research hypothesis.

  • Design appropriate experiments to address generated research questions in the pharmaceutical sciences.
  • Conduct appropriate experiments to address generated research questions.
  • Evaluate possible problems in the design and execution of a study in the pharmaceutical sciences.
  • *Develop appropriate methods to recruit and retain study participants for a selected research design.
  • *Identify important outcome measures for incorporation into patient oriented clinical trial design.
  • *Design appropriate, ethically sound, and hypothesis-driven clinical studies.

  • *Define bias in clinical and translational research.
  • Develop appropriate conclusions based on results from research data.
  • Apply fundamental principles of statistical analysis, such as power analysis, correlation, causation, regression, and summary statistics.
  • Select the appropriate statistical approach for the interpretation of preclinical and clinical datasets.

  • Defend a written research proposal describing specific research aims, significance, innovation, and approach.
  • *Defend a written research proposal that describes specific research aims, significance, innovation, and approach for a human clinical trial.

Develop presentations describing proposed research, research in progress, or research findings.