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Quantitative Methods of Data Analysis

2019/2020
Учебный год
ENG
Обучение ведется на английском языке
5
Кредиты
Статус:
Курс обязательный
Когда читается:
2-й курс, 3, 4 модуль

Преподаватель


Нежина Тамара Генриховна

Course Syllabus

Abstract

This discipline forms a part of the sociological and economic mainstream knowledge and leads students to master theoretical and practical instruments and competences for independent research. At the department of public and municipal administration, this discipline qualifies as the core discipline in the BA curriculum. Main concepts and principles of the discipline are used to plan scientific social research, conduct research activities as planned, and write a qualification diploma using the quantitative data analysis competencies. The discipline "The quantitative methods of data analysis" is closely related to the knowledge obtained in the course "Economic and social statistics" and to the course "Mathematics." To further develop the scientific approaches to management in Russia, this course teaches the methods of econometric scientific research and quantitative data analysis for the evaluation of the work of governmental and nongovernmental agencies. Modern leaders and managers today are required to use a systematic analysis of the empirical data to make rational decisions and manage production effectively. Upon the completion of the discipline "The quantitative methods of data analysis" the bachelor should have a thorough understanding of the elements of research process such as (1) formulate a problem and a research question, (2) create and use the instruments for quantitative data collection, (3) collect the data, (4) build a dataset in SPSS, (5) analyze quantitative data, (6) to interpret empirical results for understanding of social reality. Students will be able to use logical and mathematical reasoning to find explanations for successful and unsuccessful policies, and to predict the level of effectiveness based on available quantitative information.
Learning Objectives

Learning Objectives

  • The goals of the discipline "The quantitative methods of data analysis" are designed to form knowledge and skills for empirical quantitative research, to develop analytical and research competences to inform managerial decision-making process. These competences enable students to incorporate the results of their research into practical government and business programs, make decisions on whether to continue or terminate government programs
  • In the course of this discipline, the students will receive the following practical knowledge and skills: formulate proper research questions, organize research work, prepare research plan, apply quantitative reasoning, use quantitative methods for data collection, classify and categorize the data for further analysis and synthesis, and organize results for evidence-based recommendations. To successfully complete this course, students will write a research plan, develop instruments for quantitative data collection, make and interpret quantitative data analysis and write analytical reports
Expected Learning Outcomes

Expected Learning Outcomes

  • Class assignment 1 - each student will discuss research topic within a small group. Class assignment 2 - groups select research topics, write down their names and the selected research topic, submit the assignment to the teacher.
  • Class assignment 1: students identify four goals of literature review. In a provided research text, students identify the theory, the hypothesis(es), the methods, and the instruments for data collection used by the authors of an article. Class assignment 2: students perform class exercise by comparing two articles with the help of Webb- diagram.
  • Class activities 1: define the purpose of your research. Think over and write down the stages of your own research plan. Class activities 2: describe your research problem and the exploratory or explanatory model for this problem. Define social or economic theory to explain the problem. Discuss how the concepts in the problem relate to each other.
  • Activity 1: Discuss the ethical violations in the Stanford Prison Experiment. Suggest possible violations of ethics in your own research Activity 2: The introduction to the SPSS program. Survey data entry in the SPSS. Rules of coding. Coding book.
  • Class assignment 1: define the concepts and quantitative measurements in given examples. Class assignment 2: define dependent and independent variables in a given research, identify potential relationship between the variables.
  • Class activity 1: Work in groups to fine-tune the questionnaires. Class activity 2: Translate the concepts into variables and hypothesize the relationships between the variables
  • Class activity 1 - for a given research question, students design a survey of university students, develop and test a short questionnaire. Class activity 2: Read and discuss the results of "Death penalty law evaluation" in the USA (Babbie, pp. 361-362).
  • Class activity - practical work with the SPSS program in a computer class. Data entry into the SPSS program. Descriptive analysis
  • Class activity 1: students present a causal model graphically and provide theoretical support for the relevant hypotheses. Class activity 2: Discuss in groups how the effectiveness of Russian juvenile justice law can be evaluated.
  • Class activity: discussion of the structure and content of the final group research reports.
Course Contents

Course Contents

  • Theme 1. The introduction to the discipline "The quantitative methods of data analysis."
    Human inquiry and science: review of the discipline. In the first place, we will discuss the need to perform the quantitative research for public administrators. Further, the students learn the goals and practical application of quantitative data analysis for government functions. The methodology of social research includes finding and explaining a social research problem, defining the research question and the goal of research, identifying research subjects and the unit of analysis, and formulating the study objectives. Refresh the use of probability theory. Discuss statistical philosophy. The discussion of the purpose of literature review. The characteristics of a quality research question. The necessity to develop scientific approaches to finding a solution to social problems. The importance of explanation and the prognosis of social phenomena and the population behavior. Example: All students take the in class survey. Explanation of research question, theory, hypotheses, and questions.
  • Theme 2. Literature review. HSE database of scientific publications.
    Performing a literature review. The goals of a literature review. How to do the literature review. Analysis and synthesis of ideas, approaches, findings, and challenges. The use of empirical research of others to help your own research. Methods of comparing the literature: comparing and contrasting, the use of Webb diagram. Class goals: students learn and practice the review of scientific articles for their own research. Literature review is done early in this class in order to help students devise, revise, and formulate focused research questions. Seminars: Class assignment 1: students identify four goals of literature review. In a provided research text, students identify the theory, the hypothesis(es), the methods, and the instruments for data collection used by the authors of an article. Class assignment 2: students perform class exercise by comparing two articles with the help of Webb- diagram. Home assignment 1: Students formulate the topic of their proposed research, describe the significance of the study, write research question(s) in line with the guidelines. Find at least three or more articles on the selected topic, include an annotation of each article in the first assignment (2-3 pages).
  • Theme 3. Paradigms, theories, and models
    The definition of the conceptual model for empirical research. The relationship between a theory and hypotheses in building research strategy. Macrotheory and microtheory. Heuristics and practical wisdom. Deductive theory construction and inductive theory construction: building explanatory models. Three types of research: exploration, description, explanation. The stages of empirical research. Developing research plan. The structure of research plan: introduction, literature review, theory and hypotheses, methodology, and methods of research. Describe the relationships between the stages of research. Research design as a logical model of research hypothesis. Visual image of research design: the use of diagrams. The time dimension in research design: cross-sectional, panel, and longitudinal research design. Class goals: students appreciate the role of theory in the selection of the type of research. Students learn the meaning of each part of research plan and the connections between the parts; develop a visual image of research design - a diagram.
  • Theme 4: The role of ethics in sociological research. The notion of human subjects
    Ethical issues in social research. Professional code of ethics for the social researchers in Russia: major ethical requirements. Class goals: Students discuss the ethical issues in social research and define the vulnerable human subjects. Seminar Activity 1: Discuss the ethical violations in the Stanford Prison Experiment. Suggest possible violations of ethics in your own research Activity 2: The introduction to the SPSS program. Survey data entry in the SPSS. Rules of coding. Coding book. After class home assignment - take an on-line study of ethical issues and human subject protection in social research, complete the test, and bring the certificate of completion to class. The study and the test takes 3-4 hours. You will find it here: http://phrp.nihtraining.com/users/login.php Students must bring the results of the test to the instructor during the next seminar.
  • Theme 5. Conceptualization, operationalization, and measurement of research concepts.
    Conceptions as social constructs: indicators and dimensions; real, nominal and operational definitions. Criteria of measurement quality: methods to improve precision and accuracy, reliability, and validity. The definition of major concepts within a research problem; the development of a hypotheses. Class goals: Students identify main concepts for their group research, give operational definitions of the concepts, and develop ideas about the quantitative measurements.
  • Theme 6. Population and samples
    Research population and samples. Characteristics of quantitative data - nominal, ordinal and interval data types. Planning and implementing the data collection. Construction of an instrument for data collection - the survey. Requirements for voluntary and anonymous participation. Types of questions. Ethical considerations. Class goals: Learn rules for survey building. Learn to operationalize the concepts and quantify the answers. Discuss research population.
  • Theme 7. Quantitative field research
    Sample survey - the main instrument for data collection in sociological and social research. Planning and organizing a survey. Principles for writing questions: simplicity, clarity, relevancy, acceptability, the sequence and form. Guidelines for writing a questionnaire: format, order, contingency questions, and matrix questions. The role on an interviewer. The logic of sampling: probability and non-probability sampling. Populations and sampling frames. Methods of random selection. Pretest of a questionnaire. Class goals: Students learn the basics of survey questionnaire construction, the role of an interviewer, and the sampling strategies.
  • Theme 8. Quantitative research: data processing and analysis.
    Methods of data processing and analysis. Analyzing empirical data with the help of SPSS statistical software. Data presentation with tables and graphs. Class goal: students perform practical data analysis: data coding, create the SPSS data sets for the data collected. Seminar Class activity - practical work with the SPSS program in a computer class. Data entry into the SPSS program. Descriptive analysis.
  • Theme 9. The use of the SPSS statistical package for data analysis.
    The analytical potential of the SPSS, Stata, R etc. The explanatory models and analytical techniques. The level of dependent variables defines the choice of the analytical technique. Main characteristics of causal and predictive analyses. Class goals: students explore the causal analytic techniques on the SPSS. Students develop causal or predictive hypotheses for their research. Students choose and defend the type of data collection methods for their research projects.
  • Theme 10. Doing and presenting data analysis and research results in research reports.
    Interpretation of data analysis. Writing research reports. Class goals: students explain how different goals of research may induce a variety of approaches to conducting data collection. Class activity: discussion of the structure and content of the final group research reports.
  • The purpose of scientific research
    Introduction. Theory-based theoretical and practical research. The goals and purposes of applied scientific research in public management. The role of probability theory and statistical philosophy. Importance of Big Theory testing. The discussion of Big Theories will serve to elaborate smaller applied theories to develop relevant hypotheses for the studies. Students present research plans approved by dissertation supervisors
Assessment Elements

Assessment Elements

  • non-blocking Research plan
  • non-blocking Ethics quiz
  • non-blocking quiz
  • non-blocking report
Interim Assessment

Interim Assessment

  • Interim assessment (4 module)
    0.1 * Ethics quiz + 0.1 * quiz + 0.5 * report + 0.3 * Research plan
Bibliography

Bibliography

Recommended Core Bibliography

  • Bynner, J. M., & Stribley, K. M. (2017). Research Design : The Logic of Social Inquiry. London: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1608766

Recommended Additional Bibliography

  • Jorrín Abellán, I. M. (2019). Hopscotch 2.0: An Enhanced Version of the Model for the Generation of Research Designs in Social Sciences and Education. Georgia Educational Researcher, 16(1), 5–22. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1206222