140.653.01 | AY 2013-2014 - 3rd Term | 4 Credit(s)
TTh 10:30:00 AM
  • Contact Information
    Hongkai Ji
  • Course Learning Objectives

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

    • Formulate a scientific question about the relationship of a continuous response variable Y and predictor variables X in terms of the appropriate linear regression model
    • Interpret the meaning of regression coefficients in scientific terms as if for a substantive journal
    • Develop graphical and/or tabular displays of the data to display the evidence relevant to describing the relationship of Y with one X controlling for others
    • Estimate the model using a modern statistical package such as R and interpret the results for substantive colleagues
    • Check the major assumptions of the model including independence and model form (mean, variance and distribution of residuals) and make changes to the model or method of estimation and inference to appropriately handle violations of standard assumptions
    • Write a methods and results section for a substantive journal, correctly describing the regression model in scientific terms and the method used to specify and estimate the model. Correctly interpret the regression results to answer the specific substantive questions posed in scientific terms that can be understood by substantive experts
    • Critique the methods and results from the perspective of the statistical methods chosen and alternative approaches that might have been
  • Course Description
    Biostatistics 140.653 introduces linear regression analysis for public health science. Foundational topics include: correlation, analysis of variance (ANOVA), and regression models and their uses; least squares estimation and inference for parameters; model formulation, checking for adequacy, and interpretation; and making predictions. Topics are introduced using simple linear regression equations, then amplified in the context of multiple linear regression and matrices. Techniques are introduced for: identifying influential points; modeling variable adjustments, effect modification, and nonlinear relationships; and identifying and handling departures from basic model assumptions.
  • Intended Audience
    Biostatistics master's students and quantitatively-oriented students from other depts
  • Methods of Assessment
    Student evaluation based on problem sets, a midterm exam, and a final exam
  • Prerequisites


  • Required Textbook

    Ramsey & Schafer. The Statistical Sleuth: A Course in Methods of Data Analysis (3rd edition).

  • Course Schedule

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

  • 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.

  • Welcome Message

    Hello All

    Welcome to Biostat 653!

    Lab TA Hours TBA


  • 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