MSC 516
Graduate Research Methods and Statistics
Spring 2008
Distance Offering
Gregory D. Madson, Ph.D.
Associate Professor
University of Great Falls
Library #113
791-5359 or gmadson01@ugf.edu
Office Hours: 2:15 – 4:00 p.m. Tuesdays and Thursdays,
or by appointment
Course Objective:
Students will learn to conduct social science research at the graduate-level. Students will advance through: (1) framing the research question; (2) conducting a relevant literature review; (3) formulating hypotheses; (4) examining various modes of data collection; (5) specifying a methodology; and (6) detailing various data analysis techniques.
Different types of research designs and methodologies will be presented. There will be emphasis on writing a research proposal and on selecting the appropriate design and methods for a given research problem. By the end of the course, students will have developed a research proposal in their field of study.
In addition, the course will provide a thorough grounding in statistical applications and practices. Concepts, principles, and methods of statistics from two perspectives, descriptive and inferential, will be presented. Statistical topics include describing and displaying data, measures of central tendency, correlation, regression, sampling, probability, mean comparisons, analysis of variance, and non-parametric tests.
Given the need to understand and apply basic research methods and statistical tools in graduate studies and beyond; by the end of this course the student will be able to: (1) understand the terminology and concepts used in reference to research methods and statistics; (2) interpret statistical results in the literature; (3) utilize and apply basic statistical formulas and graphically display statistical results; and (4) design a viable research proposal.
Required Text:
Salkind, Neil J. 2006. Exploring Research. Sixth edition. Upper Saddle River, NJ: Prentice Hall, Inc.
Recommended Text:
Converse, Jean M. and Stanley Presser. 1986. Survey Questions:
Handcrafting the Standardized Questionnaire. Newbury Park, CA:
Sage Publications, Inc.
Locke, Lawrence F., Waneen Wyrick Spirduso, and Stephan J.
Silverman. 1993. Proposals that Work. Newbury Park, CA:
Sage Publications, Inc.
Minium, Edward W., Robert C. Clarke, and Theodore Coladarci. 1999. Elements of Statistical Reasoning. Second edition. New York, NY: John Wiley and Sons, Inc.
Turabian, Kate. 2007. A Manual for Writers of Term Papers, Theses, and
Dissertations. Seventh edition. Chicago, IL: The University of
Chicago Press.
Assignments and Exams:
Students will be expected to develop a research proposal advancing through the research design and methods process (i.e., approximately 8 - 10 pages[see proposal outline document]). In addition, six research article reviews will be completed (i.e., 2 - 3 pages [see sample article review document]). These reviews should be relevant to the student's research proposal and should facilitate the literature review within the proposal. At least two of the reviews should be quantitative articles.
In addition, a midterm exam will be given covering research design and data collection. Finally, a statistics assignment will be completed, which will be primarily computational.
Grading will be based on the following:
Six Research Article Reviews: 200 (20%)
Midterm Exam: 100 (10%)
Research Proposal: 500 (50%)
Total: 1000 (100%)
Due Dates:
Three Research Article Reviews: February 8th by 5:00pm
Three Research Article Reviews: February 29th by 5:00pm
Midterm Exam: Administered week of March 10th
Research Proposal: April 30th by 5:00pm
Student Responsibilities:
Students are expected to attend each of the telecom sessions and to be prepared to discuss the subject material and their research proposals. The weekly telecom sessions will not be lectures but will be used to clarify and elaborate on the topics and to have questions answered on the assignments. Students are expected to maintain a self-directed progression through the lectures.
Assignments will be typewritten and double-spaced. The statistics assignment will be hand-calculated with the aid of a spreadsheet for column calculations, if desired. Ten points will be deducted per day for late assignments. The mid-term exam will use a multiple-choice answer format.
Video Lectures:
Lecture Topics Applicable Readings
1 Course Overview Salkind,
What is Research? Chapter 1
The Scientific Method
Ideals of Scientific Inquiry
Social Science Paradigms of Inquiry
Quantitative vs. Qualitative Studies
2 Formulation of the Research Problem Salkind,
The Literature Review Chapters 2, 3, and 13
The Structuring of Inquiry
Conceptualization
Operationalization
Measurement
Validity and reliability
Identifying the Unit of Analysis
Identifying Relationships
Independent versus Dependent Variables
Overview of the Research Process
3 Indirect Data Collection Modes Salkind,
Unobtrusive Chapters 6 and 9
Content Analysis
Secondary/Existing Data
Historical/Archival
Direct Data Collection Modes (Non-experimental)
Participant and Non-participant observation
Survey Research [See survey research
Question Protocol document]
Types of Questions
Questionnaire Development and Design
4 The Logic of Sampling Salkind,
Sampling terminology and concepts Chapter 4
Sampling Theory and Distributions
Sample Size
Types of Sampling Designs
Nonprobability and Probability
5 Qualitative Research Salkind,
Case Study Chapter 10
Ethnography
Phenomenology
Grounded Theory
Lecture Topics Applicable Readings
6 Experimental Designs Salkind,
Issues of Validity and Bias in Scientific Inquiry Chapter 5, 11, and 12
Ethical Issues in Research
Data Coding
7 Why Statistics? Salkind,
What is Statistics? Chapter 7
Descriptive Statistics
Frequency Distributions Minium,
Displaying Data Chapters 1-3
8 Central Tendency Minium,
Variability Chapters 4-6
Normal Distributions and Standard Scores
9 Correlation Minium, Chapter 7
10 Regression Minium,
Multivariate Regression Chapter 8
Regression Diagnostics
Factor Analysis
11 Inferential Statistics Salkind,
Hypothesis Testing Chapter 8
Standard deviation known Minium,
Standard deviation not known Chapters 11 and 13
12 Comparing Means Minium,
Independent samples Chapters 14 and 15
Dependent samples
13 Analysis of Variance Minium,
One-way Chapters 18, 19, and 20
Two-way
Non-parametric tests
Chi-square