This webpage provides details on introductory course offerings in the Department of Biostatistics and some advice about course selection. Information about specific instructors, meeting times, etc. can be found at cab.brown.edu.

**PHP 1501 - Essentials of Data Analysis**

Course description: This course covers the basic concepts of statistics and the statistical methods commonly used in the social sciences and public health with an emphasis on applications to real data. The first half of the course introduces descriptive statistics and the inferential statistical methods of confidence intervals and significance tests. The second half introduces bivariate and multivariate methods, emphasizing contingency table analysis, regression, and analysis of variance. This is designed to be a first course in Statistics. The course is intended for Public Health or Statistics concentrators. Others can register with instructor's permission.

Notes: PHP 1501 is a survey course providing introduction to the basics of statistical methods and practice. It is intended for undergraduates who have no prior exposure to college level statistics or that have only been exposed to AP statistics. The examples used in the course are primarily derived from public health and biomedical research. There are no prior requirements, but the course involves using statistical software. It meets the biostatistics requirement for public health concentrators and the introductory statistics course for statistics concentators.

Who should take this course: PHP 1501 is required for statistics concentrators and public health concentrators. The course can also be taken by those looking for a hands-on, introductory-level, one-semester survey course of commonly-used statistical methods.

**PHP 1510 and PHP 2510 - Principles of Biostatistics**

Course description: This course is intended to provide a basic foundation in the methods and applications of biostatistics, and is geared towards the students whose fields of study include a substantial statistical or quantitative component. Ideally, this course is the first in a two-part sequence (the sequel being PHP 1511: Applied Regression), designed to provide students in the public health, biological and life sciences with broad-based exposure to modern methods of biostatistical inference, in addition to an understanding of underlying mathematical principles and motivations.

Notes: Both PHP 1510 and 2510 comprise the first half of a two-semester survey of biostatistical methods and practice, with examples derived primarily from public health and biomedical research. Although there are no formal pre-requisites, the course makes use of computing and some mathematical concepts and tools from calculus, such as derivatives. Students should be comfortable with logarithms and exponents. Most of the data analytic exercises will be conducted using R or Stata. This course does satisfy the prerequisite for some advanced courses in biostatistics.

Who should take this course: Students desiring a more in-depth treatment of statistical methods, their rationale and motivation, and a conceptual description of their mathematical justifications; students who are interested in taking additional methods courses in biostatistics at the 2500 level.

PHP 2510 is intended for graduate students in public health, biological sciences and social sciences – particularly those whose thesis work involves considerable data analysis and/or whose graduate training program requires the course. Hence PHP 2510 will be restricted to graduate students. PHP 1510 is intended for undergraduates who are seeking an intensive introduction to applied statistical methods.

Those taking either course should keep in mind that PHP 1510/2510 is the first half of a one-year sequence. Regression and statistical modeling is covered in the spring semester in PHP 1511/2511.

**PHP 2507 – Biostatistics and Applied Data Analysis I**

Course description: The objective of the year-long, two-course sequence is for students to develop knowledge, skills and perspectives necessary to analyze data to answer public health questions. The year-long sequence focuses on statistical principles as well as the applied skills necessary to answer public health questions using data, including: data acquisition, data analysis, data interpretation and the presentation of results. Using lectures, labs and small group discussions, we focus on evaluating data sources, refining research questions, univariate and bivariate analyses, and presentation of initial results. Prerequisite: understanding of basic math concepts and terms. Enrollment limited to 50 students. Instructor permission required.

Notes: This is the first half of a year-long introductory-level sequence using detailed case studies. The course is intended for MPH students whose program of study requires two semesters of biostatistics.

Who should take this course: MPH students whose program of study requires two semesters of biostatistics. The course is restricted to MPH students.

**PHP 2515 – Fundamentals of Probability and Statistical Inference**

Course description: This course will provide an introduction to probability theory, mathematical statistics and their application to biostatistics. The emphasis of the course will be on basic mathematical and probabilistic concepts that form the basis for statistical inference. The course will cover fundamental ideas of probability, some simple statistical models (normal, binomial, exponential and Poisson), sample and population moments, nite and approximate sampling distributions, point and interval estimation, and hypothesis testing. Examples of their use in modeling will also be discussed.

Who should take this course: PHP 2515 is designed for students in the biostatistics masters program. The course content presumes familiarity with essentials of calculus and linear algebra and assumes that students have some working familiarity with coding in R, Python, or a similar language.

**2520 – Statistical Inference I**

Course description: First of two courses that provide a comprehensive introduction to the theory of modern statistical inference. PHP 2520 presents a survey of fundamental ideas and methods, including sufficiency, likelihood based inference, hypothesis testing, asymptotic theory, and Bayesian inference. Measure theory not required. Open to advanced undergraduates with permission from the instructor.

Who should take this course: PHP 2520 is required for students in the biostatistics Ph.D. program and can be taken by students desiring a rigorous course in mathematical statistics. It can be taken by students in other departments provided that they meet the pre-requisites (generally 3 semesters of calculus, 1 semester of linear algebra, and ideally one semester of advanced probability).