Data Science Requirements

Program Director:Robert H. Carver Office: Stanger Hall 104 Phone: 508-565-1130rcarver@stonehill.edu

The minor in Data Science requires the completion of six courses.

Complete Four Required Courses

Code Course Credits

DSC 201

Introduction to Data Science

Offered: Fall Semesters

Introduction to the theory and practice of data science. This course exposes students to the range of applications across fields and provides rudimentary coverage of data structures, simple data queries, the types and goals of analytic models and modern visualization. Lecture, exercises, projects and guest speakers.

Prerequisite(s): Any of the following Statistical Reasoning courses: BUS 206, CHM 331, CRM 311, ECO 241, EDU 301, MTH 145, MTH 207, MTH 225, MTH 396, POL 210, PSY 261, or SOC 311
Course may be applied to the Data Science and Sports, Science & Society programs.

3

CSC 103

Computer Science I

Offered: Fall Semester

An introduction to programming and problem solving using Java. Topics include: Input and Output; Selection; Repetition; Methods; Recursion; Arrays; Classes and Objects.

Course may be applied to the Data Science program.

4

CSC 104

Computer Science II

Offered: Spring Semester

Inheritance; Polymorphism; Exceptions; Stream IO; Elementary Data Structures; Graphics; Event Driven Programming.

Prerequisite(s): CSC 103.
Course may be applied to the Data Science program.

4

DSC 395

Data Science Integrated Project

Offered: Offered Periodically

This is a project-based interdisciplinary course, required of all minors. Students apply data management and analytical skills to large scale data mining and modeling projects appropriate to their major disciplines. Participating students meet weekly in a seminar format, working with faculty guides, to design and develop their projects, reporting regularly to the seminar about progress and challenges.

Prerequisite(s): DSC 201, CSC 103, CSC 104 and one additional data science minor course. Open to Data Science minors only.
Course may be applied to the Data Science program.

3

Complete One of the Following Courses

Code Course Credits

BUS 309

Database Applications

Offered: Spring Semester

Explores the role of information systems in a small business setting. The theory and design of business systems prepare the students for extensive hands-on labs, developing applications using popular software packages.

Course may be applied to the Data Science and Management of Information Systems programs.

3

CSC 325

Database Management Systems

Offered: Alternate Years: Spring 2017, 2019

Data Modeling using the Entity-Relationship approach. The Relational Model and Relational Algebra. SQL. Functional dependencies and normalization. Database design Process. Record storage and primary file organization. Index structures for files. Concurrency control techniques.

Prerequisite(s): CSC 211 (with a grade of C- or better).
Course may be applied to the Data Science and Management of Information Systems programs.

3

Complete One of the Following Courses

These courses provide a grounding in analytic methods beyond elementary statistics.

Code Course Credits

BUS 207

Intermediate Statistics for Business

Offered: Not Offered 2016-2017

Multivariate statistical techniques appropriate to business problems. Emphasis on study design and effective use of software to incorporate statistical reasoning in common business situations. Topics include design of experiments, Analysis of Variance, simple and multiple regression analysis, residual analysis and time series forecasting.

Prerequisite(s): BUS 206 or MTH 145 or MTH 225 or ECO 241 or PSY 261.
Course may be applied to the Data Science program.

3

BUS 308

Decision Support Systems and Business Intelligence

Offered: Fall and Spring Semesters

This course studies the characteristics and capabilities of current, interactive decision support systems in the business decision making environment as well as the design, implementation, and support of numerous types of business intelligence systems. Topics include foundations for decision making, data warehousing and management, business reporting, visualization, forecasting, social networking analytics, mathematical model-based decision making (linear programming, time-series forecasting, simulation), data mining, knowledge management, and expert systems. Considerable use of Microsoft Excel and JMP may be required.

Prerequisite(s): BUS 206 or MTH 145 or MTH 225 or ECO 241 or PSY 261. (BUS 204 is recommended).
Course may be applied to the Data Science and Management of Information Systems programs.

3

BUS 341

Marketing Research

Offered: Fall Semester

Discusses the tools and techniques available for gathering, analyzing, and using information to aid marketing decision making. Covers topics such as problem definition, research design formulation, measurement, research instrument development, sampling techniques, data collection, data interpretation and analysis, and presentation of research findings. Skills acquired are used in a survey research project.

Prerequisite(s): BUS 206 and BUS 340, and Junior standing.
Course may be applied to the Data Science program.

3

COM 322

Communication Research Methods

Offered: Fall and Spring Semesters

Introduction to basic techniques for investigating common communication problems. Topics include focus group interviews, questionnaire design, critical methodology, content analysis, and other basic data collection methods used in communication organizations. Designed for Communication majors seeking a research course which emphasizes practical applications.

Prerequisite(s): Sophomore standing.
Course may be applied to the Data Science program.

3

CRM 310

Research Methods for Criminology (WID)

Offered: Fall Semester

This course examines research methods for criminology, starting with theoretical concepts, ethics, and the literature review, moving to sampling, measurement, and various quantitative and qualitative research methods.

Prerequisite(s): CRM 120 or CRM 201 and open to junior and senior Criminology or Sociology majors.
Fulfills the Writing-in-the-Disciplines requirement. Course may be applied to the Data Science program.

4

CRM 335

Spatial Crime Analysis

Offered: Not Offered 2016-2017

Introduces a variety of methods and techniques for the visualization, exploration, and modeling of crime data using geographic mapping. Emphasis on mapping real life crime data and exploring mapping technology as a strategic planning tool for law enforcement agencies. The main objectives are to teach students the basic concepts of geographic mapping and its use by a variety of criminal justice agencies using ArcView Mapping software.

Prerequisite(s): CRM 120 or CRM 201.
Course may be applied to the Data Science program.

3

ECO 242

Econometrics (WID)

Offered: Spring Semester

Is secondary smoke harmful? Learn econometrics to appropriately answer questions like this. The theory and application of multivariate regression analysis. We concentrate on problems of estimation and hypothesis testing of the direction and magnitude of possible causal relationships among variables. We use STATA econometrics software.

Prerequisite(s): ECO 176 and ECO 178 (or their corresponding First-Year Seminar equivalents) and completion of any statistical reasoning course.
Fulfills the general education Writing-in-the-Disciplines requirement. Course may be applied to the Data Science program.

4

ENV 325

Introduction to Geographic Information Systems

Offered: Spring Semester

Introduction to geographical information systems technology, focusing on spatial data acquisition, development and analysis in the science and management of natural resources. Topics covered include basic data structures, data sources, data collection, data quality, geodesy and map projections, spatial and tabular data analysis, digital elevation data and terrain analysis, cartographic modeling, and cartographic layout. Laboratory exercises provide practical experiences that complement the theory covered in lecture.

Prerequisite(s): ENV 200.
Course may be applied to the Data Science program.

4

MTH 225

Statistics for Science

Offered: Spring Semester

Probability; descriptive statistics; normal distribution, inference; hypothesis testing; analysis of variance; sampling theory; correlation and regression. Examples from the sciences.

Prerequisite(s): MTH 125.
Fulfills the Statistical Reasoning requirement. Course may be applied to the Data Science program.

3

MTH 396

Probability and Statistics II

Offered: Alternate Years: Spring 2017, 2019

Continuation of MTH 395. Theory and application of statistics; random sampling; organization of data; descriptive statistics; sample mean and additional special distributions, the theory of estimators, applications of estimation, hypothesis testing and Regression. Mathematical software is used in applications of statistics.

Prerequisite(s): MTH 395.
Fulfills the Statistical Reasoning requirement. Course may be applied to the Data Science program.

3

POL 210

Research Methods in Political Science (WID)

Offered: Fall and Spring Semesters

This course provides an introduction to the methods that political scientists use to answer questions. Students will learn analytical tools to critically evaluate and conduct research. The course will cover research design, hypothesis formulation, and various qualitative and quantitative methods for collecting and analyzing data.

Prerequisite(s): POL 123.
Fulfills the Statistical Reasoning and Writing-in-the Disciplines requirements. Course may be applied to the Data Science program.Previously offered as POL 310.

4

PSY 262

Intermediate Statistics

Offered: Spring Semester

Further examination of statistical techniques used in the behavioral sciences. Topics include: Two-way analysis of variance, repeated measures ANOVA, regression analysis, and nonparametric techniques (e.g., Mann-Whitney U, Kruskal-Wallace H test). Statistical analysis software complements use of computational formulae.

Prerequisite(s): PSY 261.
Course may be applied to the Data Science program.

3