Social Science Research Methods

Description

Are you interested in analyzing human behavior through data? Learn data theories, examine theoretical research and develop your critical analysis skills. You'll leverage qualitative evidence in the world around you and gain the quantitative skills that create and confirm theories.

The concentration in social science research methods prepares students to acquire, manage and analyze a broad range of human thought and behavior data. Data can be qualitative (e.g., text, images, sound) or quantitative (e.g., direct observation, surveys, geographic information systems).

Data acquisition skills may include downloading and managing information from online sources, collecting data in surveys or making direct observations. A key feature of this concentration is a focus on data analysis, so students can analyze any data they collect.

All students in this concentration demonstrate skills in statistical analysis and selecting methods related to their interests.

Requirements

• Students must complete a minimum of 18 credit hours including 12 of upper division hours for this concentration.
• All courses must be completed with a grade of “C” (2.00) or higher.
• A minimum 12 hours must be taken in courses offered at ASU.

Required Course -- 3 credit hours
GIS 469 / SOC 469: Multivariate Statistics for Social Sciences or STP 452: Multivariate Statistics (3)

Electives (choose at least four) -- 12 credit hours
Choose at least four courses for a minimum of 12 credit hours. At least six credit hours must be
upper division.
ACO 100: All About Data: Design, Query, and Visualization (CS) (3)
ACT 435: Statistics for Risk Modeling (3)
ACT 450: Actuarial Models (3)
ALA 235: Introduction to Computer Modeling (CS) (3)
AML 253: Introduction to Mathematical Tools and Modeling for the Life and Social Sciences (3)
AML 441: Mathematical Concepts and Tools in Sustainability (3)
ASM 494: Models in Social Evolution (3)
BME 301: Numerical Methods in Biomedical Engineering (2)
BMI 211: Modeling Biomedical Decisions (3)
BMI 311: Modeling Biomedical Knowledge (3)
BMI 312: Modeling Biomedical Data (3)
BMI 461: Advanced Topics in Biomedical Informatics I (3)
BMI 462: Advanced Topics In Biomedical Informatics II (3)
COM 308: Advanced Research Methods in Communication (L) (3)
COM 407: Advanced Critical Methods in Communication (3)
CRJ 303: Statistical Analysis (CS) (3)
ECN 310: Applied Regression and Data Analytics (3)
ECN 416: Game Theory and Economic Behavior (3)
EDP 454: Statistical Data Analysis in Education (3)
FAS 361 / SOC 391: Applied Research Methods (L or SB) (3)
FAS 498: Advanced Statistics for Social Sciences (3)
GCU 351: Population Geography (SB & G) (3)
GCU 373: Introduction to Geographic Information Science (SG) (4)
GCU 442: Geographical Analysis of Transportation (SB) (3)
GCU 496: Geographic Research Methods (L) (3)
GIS 311: Geographic Information Science III (CS) (4)
GIS 322: Programming Principles in GIS II (3)
GIS 341: Cartography and Georepresentation (CS) (3)
GIS 431: Spatial Databases (3)
GIS 441: Geographics: Interactive and Animated Cartography and Geovisualization (CS) (3)
GIS 461 / PUP 481: Fundamentals of Spatial Optimization (3)
GIS 462: Location Analysis and Modeling (3)
GIS 470: Advanced Statistics for Geography and Planning (CS) (3)
GIS 471: Spatial Statistics for Geography and Planning (3)
GIS 472: Spatial Regression Analysis (3)
GPH 494: Advanced Digital Analysis (3)
HSE 290: Experimental Methods for Human Systems Research (L) (3)
HSE 390: Qualitative Research Methods (L) (3)
IFT 200: Information Modeling, Storage and Retrieval (3)
IFT 410: Big Data Tools and Practices (3)
MKT 352: Marketing Research (L) (3)
POS 301 / SGS 305: Empirical Political Inquiry (SB) (3)
POS 401 / SGS 401: Political Statistics (CS) (3)
PSY 330: Statistical Methods (CS) (3)
PUP 424: Planning Methods (4)
SBS 302: Qualitative Methods (3)
SBS 404: Social Statistics II: Multivariate Analysis (CS) (3)
SOC 389 / SBS 389 / ASB 389: Ethnographic Field Lab (1-6)
SOS 211: Calculus and Probability for the Life and Social Sciences (3)
STP 280: Probability and Statistics for Researchers (CS) (3)
STP 310: Design and Analysis of Experiments (3)
STP 311: Regression and Time Series Analyses (3)
STP 315: Statistical Computing (3)
STP 420: Introductory Applied Statistics (CS) (3)
STP 421: Probability (3)
STP 425: Stochastic Processes (3)
STP 429: Applied Regression (CS) (3)
STP 450: Nonparametric Statistics (3)
STP 460: Categorical Data Analysis (3)
TWC 301: Fundamentals of Writing for Digital Media (L) (3)
TWC 411: Principles of Visual Communication (L) (3)

Required Capstone Course -- 3 credit hours
ASB 499: Individualized Instruction or an equivalent capstone course approved by academic advisor (3)

Prerequisite courses may be needed in order to complete the requirements of this certificate.