Statistical Reasoning I 



 
 November 7, 2009

 
Course Syllabus


 

Course Description

Provides a broad overview of biostatistical methods and concepts used in the public health sciences, emphasizing interpretation and concepts rather than calculations or mathematical details. Develops ability to read the scientific literature to critically evaluate study designs and methods of data analysis. Introduces basic concepts of statistical inference, including hypothesis testing, p-values, and confidence intervals. Topics include comparisons of means and proportions; the normal distribution; regression and correlation; confounding; concepts of study design, including randomization, sample size, and power considerations; logistic regression; and an overview of some methods in survival analysis. Draws examples of the use and abuse of statistical methods from the current biomedical literature.


Course Objectives

Upon completion of this course, you will be able to:

  • Understand and give examples of different types of data arising in public health studies
  • Interpret differences in data distributions via visual displays
  • Calculate standard normal scores and resulting probabilities
  • Calculate and interpret confidence intervals for population means and proportions
  • Interpret and explain a p-value
  • Perform a two-sample t-test and interpret the results; calculate a 95%Êconfidence interval for the difference in population means
  • Use Stata to perform two sample comparisons of means and create confidence intervals for the population mean differences
  • Select an appropriate test for comparing two populations on a continuous measure, when the two sample t-test is not appropriate
  • Understand and interpret results from Analysis of Variance (ANOVA), a technique used to compare means amongst more than two independent populations
  • Choose an appropriate method for comparing proportions between two groups; construct a 95% confidence interval for the difference in population proportions
  • Use Stata to compare proportions amongst two independent populations
  • Understand and interpret relative risks and odds ratios when comparing two populations
  • Understand why survival (timed to event) data requires its own type of analysis techniques
  • Construct a Kaplan-Meier estimate of the survival function that describes the "survival experience" of a cohort of subjects
  • Interpret the result of a log-rank test in the context of comparing the "survival experience" of multiple cohorts
  • Interpret output from the statistical software package Stata related to the various estimation and hypothesis testing procedures covered in the course

Course Topics

  • Lecture 1: Describing Data, Part 1
  • Lecture 2: Describing Data, Part 2
  • Lecture 3: Sampling Variability and Confidence Intervals
  • Special Lecture: Some Useful Stata Information
  • Lecture 4: The Paired t-test and Hypothesis Testing
  • Lecture 5: Comparing Means Among Two (or More) Independent Populations
  • Lecture 6: Comparing Proportions Between Two Independent Populations
  • Lecture 7: When Time Is of Interest: The Case for Survival Analysis

Course Format

The content of this course is divided into four separate modules. All the required course work can be accessed from the Course Modules page. The lecture sections are presented sequentially and should be completed in that order. Each of these sections combines audio presentation and slides—just like attending lectures in class. You may return to any previous section at any point and review its contents at your convenience. In each lecture section, you will find a listing of the section objectives, links to the lecture materials, a listing of reading assignments, and links to Web resources.


Grading Policy

50% of grade: Your four homework assignments. These exercises will encompass the interpretation of concepts covered in class and give some practice with using Stata for very common computations. This homework portion of your final course grade will be based on the three highest scoring assignments of the four (each will contribute 16.6% to the final course grade).  

Homework solutions will be accessible on the day after the assignment is due.

25% of grade: Two quizzes. Each quiz will constitute 12.5% of your final grade. These will be multiple-choice quizzes with a time limitation. They will be administered online and each will be available for a limited time period.

25% of grade: Final exam. This is a closed-book, proctored exam. You'll receive further information and details about the final exam and identifying a proctor from your professor.


Evaluation

Lecture and Instructor Evaluation
Feedback from students each year has greatly enhanced the course. An online evaluation form is available during the last week of the course. In addition, during the LiveTalk session of the last week, we will discuss what was helpful or not helpful and how the course could be improved. By having a discussion, suggestions can be clarified and enhanced. These discussions have proved much more helpful than written evaluations.

 

Course Materials

There is no textbook for this course.

Reading Material

The recommended reading material for the course will be in the eReserves system. If you are prompted for a password please enter 140611sph.

Students are also encouraged to have access to "Small Stata," a version of Stata that is less powerful (in terms of the amount of data it can store and process, not in terms of functionality) than regular "Intercooled Stata," and costs significantly less ($48 for a one year license). Small Stata carries a one-year users license. However, if you intend to further your study of statistics beyond this course, you may wish to purchase a copy of Intercooled Stata 11. With the discount for graduate students, this costs $98 for a one year license, or $179 for a perpetual license. These can be ordered directly via Stata (http://www.stata.com/order/new/edu/gradplans/gp-direct.html). In order to get the academic discount, you will need to indicate that you are a student at Hopkins and you will need to provide your student ID number.

Other useful, but optional, references include the following:

  • Freedman, D., Pisani, R., Purves, R. Statistics
  • Moore, D., McCabe, G. Introduction to the Practice of Statistics
  • Altman, D.G. (1991). Practical Statictics for Medical Research. London: Chapman and Hall

You may purchase any of these materials (except Stata) from Matthews Medical Book Center or Amazon.com. Stata may be purchased directly from Stata Corporation.


Contact Information

Faculty Contact:
John McGready
Johns Hopkins Bloomberg School of Public Health
Department of Biostatistics
615 North Wolfe Street, Room E3527
Baltimore, MD 21205
(410) 614-9405
(410) 955-0958 (Fax)

Teaching Assistants:
Yaping Wang
Shanshan Li
George Wu
Andrew Mirelman

Homework Assignments:
Please submit to the dropbox.

 


Help

Concerns
Contact
Concerns about course topics and assignments
Technical concerns about the functionality and operation of course Web pages (before emailing, please make sure that you can replicate the problem)
  • DEHelp, the central help system for all tech support inquiries related to DED courses

Technical help on weekends
  • JHSPH User Support: 410-955-3781
Concerns about your Internet connection
  • Your Internet service provider (e.g., AT&T, Erols, etc.)
Concerns about your personal software
  • Your software vendor


Schedule

The Course Schedule outlines all the important course dates and deadlines but does not contain links to access course material. The Course Modules page (password-protected) is set up like the Schedule page but provides access to course materials.


Ethical Conduct

The academic ethics code, as discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class.


Disability Support Services

If you are a student with a documented disability who requires an academic accommodation, please contact Betty H. Addison in the Office of Career Services and Disability Support: dss@jhsph.edu, 410-955-3034, or Room E-1140.


 

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Copyright to this collective work of materials is owned by The Johns Hopkins University.
Copyright to individual contributions may be retained by contributing authors.