METHODS IN BIOSTATISTICS I Syllabus

140.651.01 | AY 2013-2014 - 1st Term | 4 Credit(s)
TTh 10:30:00 AM
  • Contact Information
    Faculty
    Ciprian Crainiceanu
  • Course Learning Objectives

    Upon successfully completing this course, students will be able to:

    • Discuss core applied statistical concepts and methods
    • Discuss the display and communication of statistical data.
    • List the distinctions between the fundamental paradigms underlying statistical methodology
    • Identify the basics of maximum likelihood
    • Identify the basics of frequentist methods: hypothesis testing, confidence intervals
    • Identify basic Bayesian techniques, interpretation and prior specification
    • Discuss the creation and interpretation of P values
    • Describe estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates
    • Describe estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences
    • Describe the basic concepts of ANOVA
  • Course Description

    Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations.

  • Intended Audience
    Biostatistics master's students, quantitatively-oriented students from other departments
  • Methods of Assessment

    Student evaluation based on several problem sets, one midterm and one final in-class exam each term.

  • Prerequisites
    Working knowledge of calculus and linear algebra
  • Required Text(s)

    There is no required textbook. Here are three recommended textbooks:

    • Introduction to Statistical Thought. M. Lavine

                https://www.math.umass.edu/~lavine/Book/book.html

    • Mathematical Statistics and Data Analysis, 2nd Edition. J. A. Rice. Duxbury Press
    • Fundamentals of Biostatistics, nth edition. B. Rosner. Brooks/Cole
  • Course Schedule

    Please see the course Session for a full list of dates and items for this course.

     

    Lectures: 10:30 – 11:50 Tuesday and Thursday in W2008

    Lab: Tuesday 1:30 – 2:20 and Wednesday 3:00 – 3:50 in W4019 

  • Academic Ethics Code

    Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.

  • Disability Support Services
    If you are a student with a documented disability who requires an academic accommodation, please contact the Office of Student Life Services at 410-955-3034 or via email at dss@jhsph.edu.