Statistical Science and Data Analytics
Learn more about the Bachelor of Science in Statistical Science and Data Analytics.
Edoardo M. Airoldi, Chair and Millard E. Gladfelter Professor of Statistics and Data Science
airoldi@temple.edu
Lauren Burns, Deputy Chair and Academic Director
lburns@temple.edu
https://www.fox.temple.edu/faculty-research/academic-areas/statistics-operations-and-data-science/
The Statistics, Operations, and Data Science Department offers the Bachelor of Science (B.S.) in Statistical Science and Data Analytics. The recent Best Jobs list compiled by CareerCast (a Local and National Job search company) ranks Data Scientist as No. 1 in their list of the best jobs with high demand. As we survey representatives from different companies, the consistent message we receive is that the cost of hiring and the demand for talent are skyrocketing. The demand is driven by the proliferation of computing technology, software and statistical tools for capturing and interpreting the substantial volume of data now available at the enterprise, government and personal levels.
The educational objective of the program is to provide graduates with a rigorous and broad-based curriculum providing:
- Rigorous quantitative foundation;
- Alignment and coordination with the established quantitative disciplines at Fox and at Temple University;
- Exposure to programming and modern languages such as Python, R, and SAS, including preparation for future SAS certification exams, after obtaining the Basics SAS certificate during the program; and
- Effective communication skills.
The major areas of employment mentioned in the report are: decision-making in business, healthcare, policy, as well as in social media, and commercial areas. In these areas, there are large bodies of data accumulated over the internet in need of being explored, understood, and analyzed. Statisticians will also be increasingly needed in the pharmaceutical industry. Biostatisticians will be needed to conduct the research and clinical trials necessary for companies to obtain approval for their products from the Food and Drug Administration. Another area of employment for statisticians is the government, where policy analysis is needed more and more. There is also growth projected for future graduates in statistics in research and development in the physical, engineering, and life sciences, where statisticians' skills in designing tests and assessing results are highly useful.
Reputable national organizations, like the American Statistical Association (ASA), endorse the value of undergraduate programs in statistics as a reflection of the increasing importance of the discipline. Statistics programs should be flexible enough to prepare bachelor's graduates to either be functioning statisticians in a service-oriented economy or go on to graduate school. The ASA guidelines for curriculum development address required changes in curriculum and suggest pedagogy in response to the strong upward demand for statisticians. Institutions need to ensure students entering the work force or heading to graduate school have the appropriate capacity to "think with data" and to pose and answer statistical questions.
Minor
Skilled users of data enhance their career opportunities. Students in any major who wish to become proficient in the ability to select, utilize, and apply quantitative and data analysis skills can pursue a minor in Statistics & Data Science. Courses cannot be used to meet minor requirements if already used to meet the requirements for a major or a different minor. Requirements for the minor must be completed prior to graduation.
Summary of Requirements
University Requirements
All new students are required to complete the university's General Education (GenEd) curriculum.
Note that students not continuously enrolled who have not been approved for a Leave of Absence or study elsewhere must follow University requirements current at the time of re-enrollment.
College Requirements
Students must meet College Graduation Requirements for the Bachelor of Science, including the requirements of the major listed below. Students must attain an overall GPA of 2.0 and a 2.0 GPA in the major to graduate as a Statistical Science and Data Analytics major.
Core Requirements
| Code | Title | Credit Hours |
|---|---|---|
| BA 2104 | Excel for Business Applications | 1 |
| ECON 1101 | Macroeconomic Principles | 3 |
| or ECON 1901 | Honors Macroeconomic Principles | |
| ECON 1102 | Microeconomic Principles | 3 |
| or ECON 1902 | Honors Microeconomic Principles | |
| HRM 1101 | Leadership and Organizational Management | 3 |
| or HRM 1901 | Honors Leadership and Organizational Management | |
| MATH 1041 | Calculus I | 4 |
| or MATH 1941 | Honors Calculus I | |
| MATH 1042 | Calculus II | 4 |
| or MATH 1942 | Honors Calculus II | |
| STAT 2103 | Statistical Business Analytics | 4 |
| or STAT 2903 | Honors Statistical Business Analytics | |
| ACCT 2101 | Financial Accounting | 3 |
| or ACCT 2901 | Honors Financial Accounting | |
| BA 2196 | Business Communications | 3 |
| or BA 2996 | Honors Business Communications | |
| CIS 1051 | Introduction to Problem Solving and Programming in Python | 4 |
| CIS 1068 | Program Design and Abstraction | 4 |
| MKTG 2101 | Marketing Management | 3 |
| or MKTG 2901 | Honors Marketing Management | |
| RMI 2101 | Introduction to Risk Management | 3 |
| or RMI 2901 | Honors Introduction to Risk Management | |
| Total Credit Hours | 42 | |
Major Requirements
Students must follow the Major Requirements and College Requirements current at the time of declaration. Students not continuously enrolled who have not been approved for a Leave of Absence or study elsewhere must follow University, College, and Major requirements current at the time of re-enrollment.
Requirements of Statistical Science and Data Analytics Major
| Code | Title | Credit Hours |
|---|---|---|
| STAT 2501 | Quantitative Foundations for Data Science (spring only) | 3 |
| STAT 2512 | Intermediate Statistics | 3 |
| STAT 2521 | Data Analysis and Statistical Computing | 3 |
| STAT 2522 | Survey Design and Sampling (spring only) | 3 |
| STAT 2523 | Design of Experiments and Quality Control (fall only) | 3 |
| STAT 3502 | Regression and Predictive Analytics (fall only) | 3 |
| STAT 3503 | Applied Statistics and Data Science | 3 |
| STAT 3504 | Time Series and Forecasting Models (fall only) | 3 |
| STAT 3505 | Introduction to SAS for Data Analytics (spring only) | 3 |
| STAT 3506 | Nonparametric and Categorical Data Analysis (fall only) | 3 |
| STAT 4596 | Capstone: Statistical Science and Data Analytics (spring only) | 3 |
| Focus Area | ||
| Select one set from the following: | 6-8 | |
| Managerial Accounting and Financial Management | ||
| Mathematical Concepts in Computing I and Database Management Systems | ||
| Introduction to Health Services Systems and Healthcare Financing and Information Technology | ||
| Digital Marketing and Customer Data Analytics | ||
| Introduction to Media Theory and Introduction to Media Production | ||
or MSP 2141 | Media Research | |
| Operations Management and Principles of Supply Chain Management | ||
or SCM 3516 | Transportation and Logistics Management | |
| Total Credit Hours | 39-41 | |
Suggested Academic Plan
Bachelor of Science in Statistical Science and Data Analytics
Requirements for New Students starting in the 2022-2023 Academic Year
Please note that this plan is suggested only, ensuring prerequisites are met.
| Year 1 | ||
|---|---|---|
| Fall | Credit Hours | |
| MATH 1041 | Calculus I (waives GenEd Quantitative Literacy requirement) | 4 |
| BA 2104 | Excel for Business Applications | 1 |
| ECON 1102 | Microeconomic Principles | 3 |
| HRM 1101 | Leadership and Organizational Management | 3 |
| ENG 0802, 0812, or 0902 | Analytical Reading and Writing [GW] | 4 |
| Term Credit Hours | 15 | |
| Spring | ||
| MATH 1042 | Calculus II | 4 |
| STAT 2103 | Statistical Business Analytics | 4 |
| ECON 1101 | Macroeconomic Principles | 3 |
| IH 0851 or 0951 | Intellectual Heritage I: The Good Life [GY] | 3 |
| GenEd Breadth Course | 3 | |
| Term Credit Hours | 17 | |
| Year 2 | ||
| Fall | ||
| STAT 2521 | Data Analysis and Statistical Computing | 3 |
| ACCT 2101 | Financial Accounting | 3 |
| BA 2196 | Business Communications [WI] | 3 |
| CIS 1051 | Introduction to Problem Solving and Programming in Python | 4 |
| IH 0852 or 0952 | Intellectual Heritage II: The Common Good [GZ] | 3 |
| Term Credit Hours | 16 | |
| Spring | ||
| STAT 2501 | Quantitative Foundations for Data Science | 3 |
| STAT 2522 | Survey Design and Sampling | 3 |
| CIS 1068 | Program Design and Abstraction | 4 |
| MKTG 2101 | Marketing Management | 3 |
| RMI 2101 | Introduction to Risk Management | 3 |
| Term Credit Hours | 16 | |
| Year 3 | ||
| Fall | ||
| STAT 2523 | Design of Experiments and Quality Control | 3 |
| STAT 3502 | Regression and Predictive Analytics | 3 |
| Focus Area Elective1 | 3 | |
| GenEd Breadth Course | 3 | |
| GenEd Breadth Course | 3 | |
| Term Credit Hours | 15 | |
| Spring | ||
| STAT 3503 | Applied Statistics and Data Science | 3 |
| STAT 3505 | Introduction to SAS for Data Analytics | 3 |
| STAT 2512 | Intermediate Statistics | 3 |
| GenEd Breadth Course | 3 | |
| GenEd Breadth Course | 3 | |
| Term Credit Hours | 15 | |
| Year 4 | ||
| Fall | ||
| STAT 3504 | Time Series and Forecasting Models | 3 |
| STAT 3506 | Nonparametric and Categorical Data Analysis | 3 |
| GenEd Breadth Course | 3 | |
| GenEd Breadth Course | 3 | |
| Free Elective | 3 | |
| Term Credit Hours | 15 | |
| Spring | ||
| STAT 4596 | Capstone: Statistical Science and Data Analytics [WI] | 3 |
| Focus Area Elective1 | 3 | |
| Free Elective | 3 | |
| Free Elective | 4 | |
| Term Credit Hours | 13 | |
| Total Credit Hours: | 122 | |
| 1 | See Requirements section for list of Focus Area courses. |