Course: Introduction to Biostatistics

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Course Description

Introduction to Biostatistics provides an introduction to selected important topics in biostatistical concepts and reasoning. This course represents an introduction to the field and provides a survey of data and data types. Specific topics include tools for describing central tendency and variability in data; methods for performing inference on population means and proportions via sample data; statistical hypothesis testing and its application to group comparisons; issues of power and sample size in study designs; and random sample and other study types. While there are some formulae and computational elements to the course, the emphasis is on interpretation and concepts.

Course Objectives

Upon completion of the course, students are able to:

  • Recognize and give examples of different types of data arising in public health and clinical 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% confidence interval for the difference in population means
  • 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
  • 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
  • Describe different kinds of studies
  • Understand confounding and interaction in studies
  • Use SPSS/STATA package to
    • Perform two sample comparisons of means and create confidence intervals for the population mean differences
    • Compare proportions amongst two independent populations
    • Interpret output from the statistical software package STATA related to the various estimation and hypothesis testing procedures covered in the course

Course Requirements

Students complete pre-course, post-course, and three month post-course assessments to assess student understanding of course material and to measure changes in understanding.