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Plan of Study: PB - Survey Statistics, Online


The PB-Survey Statistics, OL is a 12-credit graduate program designed to be completed in twelve months of continuous enrollment. UMD’s online learning environment delivers online content through easy to use web-based technology that enables learning in an engaging, interactive environment. Instruction is provided by university faculty and experts in the field. 

See the sample plan of study, below. Students should use this as a guide to develop a plan with the program director. The program uses the semester academic calendar with classes held in fall and spring semester (16 weeks each) and Summer Session (two 6-week sessions).

Specific class meeting information (days and time) is posted on UMD’s interactive web service services, Testudo. Once on that site, select “Schedule of Classes,” then the term/year. Courses are listed by academic unit. 

Sample Plan of Study

The program uses specific section codes for registration which are listed on the sample plan of study. Actual course offerings are determined by the program and may vary semester to semester. Students should note if a course has a pre-requisite or co-requisite. UMD graduate students in other programs who are interested in registering for courses in this program, see Non-Program Student Registration. For a detailed course description, see Courses

Semester Year Type Course Number Section Code Credits
Fall 1 Core SURV400 PLS* 3
Fall 1 Core SURV626 PLS* 2
Spring 1 Recommended SURV667 PLS* 1
Spring 1 Recommended SURV726 PLS* 1
Spring 1 Recommended SURV735 PLS* 1
Spring 1 Recommended SURV747 PLS* 2
Fall 2 Elective SURV*** PLS* 1 to 2
Fall 2 Elective SURV*** PLS* 1 to 2

Course List

Below is a listing of all program courses with area of focus. Actual course offerings are determined by the program and may vary. For a detailed course description, see Courses.

Focus Area Course Number Title
Core SURV400 Fundamentals of Survey and Data Science
Core SURV626 Sampling I
Core SURV742 Inference from Complex Surveys
Recommended SURV662 An Introduction to Small Area Estimation
Recommended SURV667 Introduction to Record Linkage with Big Data Applications
Recommended SURV726 Multiple Imputation
Recommended SURV730 Measurement Error Models
Recommended SURV735 Data Confidentiality and Statistical Disclosure Control
Recommended SURV747 Practical Tools for Sampling and Weighting
Recommended SURV*** Sampling II
Elective SURV623 Data Collection Methods in Survey Research
Elective SURV624 Privacy Law
Elective SURV625 Applied Sampling
Elective SURV627 Experimental Design For Surveys
Elective SURV630 Questionnaire Design and Evaluation
Elective SURV631 Questionnaire Design
Elective SURV635 Usability Testing for Survey Research
Elective SURV656 Web Survey Methodology
Elective SURV665 Intro to Real World Data Management
Elective SURV673 Introduction to Python and SQL
Elective SURV702 Analysis of Complex Survey Data
Elective SURV703 Computer - Based Content Analysis I
Elective SURV704 Computer-Based Content Analysis II
Elective SURV722 Research Design
Elective SURV725 Item Nonresponse and Imputation
Elective SURV736 Web Scraping and API
Elective SURV745 Practical Tools for Sampling and Weighting
Elective SURV746 Advanced Statistical Modeling
Elective SURV751 Introduction to Big Data and Machine Learning
Elective SURV752 Introduction to Data Visualization
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