Applied Statistics (100% online)
Offered at IU South Bend by College of Liberal Arts and Sciences.
About
This is an online program.
The IU Bachelor of Science in Applied Statistics is designed to meet the needs of students who want to pursue careers in the fields of statistics, medical research and analysis, industrial data analytics, and marketing. It may also appeal to individuals working in the financial sector.
According to the U.S. Bureau of Labor Statistics, employment demand and job openings remain strong for graduates pursing STEM occupations in computer science, engineering, and mathematics.
The 120-credit hour transfer-friendly curriculum combines the flexibility of 100% online asynchronous delivery with high-quality instruction offered by IU faculty members and is tailored to the particular needs of students who are working and/or have family responsibilities.
Students transferring into the IU Online B.S. in Applied Statistics will be able to transfer up to 60 credit hours earned in accredited associate degree programs, and formal articulation agreements are in place to facilitate transfer into the program from Ivy Tech and Vincennes.
Graduates from the B.S. in Applied Statistics degree program will demonstrate the statistical and computational skills described in the American Statistical Association Curriculum Guidelines for Undergraduate Programs in Statistical Science and possess strong skills in SQL and familiarity with industrial-leading statistical packages, including SAS or R.
Core skill areas include:
- Foundational mathematical knowledge in calculus (differentiation, integration, and infinite series), linear algebra, and calculus-based probability theory (properties of univariate and multivariate random variables, discrete and continuous distributions).
- The application of statistical methods and theory such as distributions of random variables, likelihood theory, point and interval estimation, hypothesis testing, Bayesian methods, and resampling to solve problems.
- Design of studies, proficiency in data collection and analysis with a focus on data-management skills including organization, design, and drawing inferences from data using appropriate statistical methodology.
- Statistical modeling for problem-solving in variety of linear and nonlinear parametric, parametric, and semiparametric regression models, including model building and assessment, as well as skills in applying multivariate methods; and statistical learning and statistical data mining techniques for big data analysis.
- Statistical computation using statistical tools involving computer programming languages, such as R or SQL, for statistical modeling and data analysis.
- Data analytics communication that employs statistical ideas and appropriate technical terms in oral and written presentations to provides critically reasoned analysis for professional as well as non-statistical audiences.
Many online support services are available to assist you as you progress through this 100% online program.