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Fundamentals of Biostatistical Reasoning

Analytical Thinking

Course Description

Analysis and interpretation of biological and health-related data using biostatistical concepts and methods. Topics include exploratory data analysis, probability distributions, sampling distributions, estimation, hypothesis testing, regression, and contingency table analysis. Application of statistical software for data visualization, inference, and evaluation of relationships between variables.


Athena Title

Fundamentals Biostat Reasoning


Equivalent Courses

Not open to students with credit in BIOS 7001, BIOS 7010E


Grading System

A - F (Traditional)


Student learning Outcomes

  • Students will be able to interpret and apply fundamental biostatistical concepts and terminology to effectively describe and analyze real-world biological or health-related data.
  • Students will be able to employ appropriate graphical and descriptive statistical methods to explore, summarize, and visualize distributions and relationships within datasets.
  • Students will be able to apply probability principles and the normal distribution to understand sampling distributions and the logic of statistical inference for hypothesis testing and confidence interval construction.
  • Students will be able to use appropriate statistical software to construct and interpret confidence intervals and perform hypothesis tests to draw valid conclusions about population parameters form sample data in the context of one- and two-sample studies.
  • Students will be able to use appropriate statistical software to analyze relationships between variables using correlation, regression, and chi-square tests, and interpret the results in the context of biological or public health research questions.

Topical Outline

  • Data Basics
  • Collection of Health-Related Data
  • Exploratory Data Analysis (EDA) – Univariate
  • Exploratory Data Analysis (EDA) – Bivariate
  • Probability Basics
  • Evaluating Screening and Diagnostic Tests
  • Discrete Probability Distributions – Binomial and Poisson
  • Continuous Probability Distributions – Normal
  • Sampling Distributions
  • Estimation
  • Hypothesis Testing
  • One-sample inference
  • Two-sample inference
  • Nonparametric Methods
  • Contingency Table Analysis

Institutional Competencies Learning Outcomes

Analytical Thinking

The ability to reason, interpret, analyze, and solve problems from a wide array of authentic contexts.