Individuals who have a background in mathematics may be interested in continuing their education by enrolling in a graduate-level program in applied statistics. There are a number of master's and Ph.D. programs in applied statistics available, most of which share several commonalities like required courses and admission requirements, which we will discuss in greater detail below.
General Information About Applied Statistics Master's Programs
Master's degrees in applied statistics can prepare graduates for careers in fields like data analysis, financial planning, market research, and statistical consulting. The courses within applied statistics graduate programs are designed to give students an advanced understanding of statistics and data management. Some common course topics include:
Master's degree programs in statistics typically require students to take a course in regression methods or analysis. In this course, students can learn how to analyze different types of data using various regression methods. Advanced regression courses instruct students in both simpler and multiple linear regression.
Applied Multivariate Analysis
This course can give students an understanding of the theory of multivariate analysis and the application of different multivariate methods, which can be used to analyze data from a variety of science and engineering fields. This course may involve the use of statistical software.
Probability Models and Theory
This course acts as an introduction to using probability models to make inferences about data. Some topics covered in this course could include discrete variables, continuous random variables, central limit theorems, likelihood-based estimation, and hypothesis testing. This course could involve solving programs using programming language.
Design and Analysis of Experiments
In this course, students will learn different methods involved in designing valid statistical experiments. They will begin by focusing on the principles of design, putting the appropriate measures in place, and setting up balanced or partially balanced block design.
Applied Data Mining
In a course focused on applied data mining, students can learn how to use different data mining tools and methods. Some of these could include cluster analysis, classification and regression trees, and discriminate analysis. This course may involve using statistical software.
General Information about Applied Statistics Ph.D. Programs
Students who are interested in continuing their education may want to enroll in a Ph.D. program in applied statistics. Some of these programs accept students who have only completed a bachelor's degree, while others require applicants to already have a master's degree. We will look at a few courses common to most Ph.D. programs in applied statistics below.
Data Analysis and Reporting/Consulting
In this course, students focus on learning advanced research and data analysis methods, as well as methods on how to work with clients and provide statical consulting services. A course like this usually includes learning how to correspond both orally and by writing with clients, as well as how to prepare reports.
In a research ethics course you can further your understanding in how to ethically design experiments and surveys, especially if they involve human trials. Depending on the field you want to work in, you may take a course specifically in medical ethics.
A Ph.D. program in applied statistics typically culminates with students proposing and then writing a dissertation. Students can usually pick a topic of their choice as long as a university faculty member or the department approves it, and they may work on it for a year or more. After completing their dissertation they must defend it before a review board to receive credit.
Applied Statistics Graduate Program Admission Requirements
Master's degree programs in applied statistics generally require students to have at least a bachelor's degree. Programs will typically consider applicants with a bachelor's degree in any field, as long as they have also taken a significant number of courses in mathematics, particularly calculus, statistics, and advanced matrix algebra. Students with a stronger mathematics background may be given preference over students without as much experience in math, especially in more competitive programs.
Students will also need to submit GRE scores, proof of English language proficiency (if they are international students), transcripts, and possibly letters of recommendation. Some programs have a minimum GPA requirement that students may have to meet if they wish to be considered. Because many Ph.D. programs also accept bachelor's degree holders, the admission requirements for these programs are generally the same as at the master's level.
Master's degree and Ph.D. programs in applied statistics are widely available and provide students with advanced quantitative analytics and data science skills. Courses in these programs cover topics that range from regression methods to data mining; Ph.D. programs also require a dissertation.