Advanced Analysis of Public Opinion and Consultancy Research


Course description:


This course introduces you to the basic principles of doing research and conducting consultancy work. Quantitative data analysis is an important part of business reports, marketing analyses, and consultancy projects, while surveys of public opinion are one of the major sources of quantitative data. The course will, therefore, teach you how to use data from public opinion polls in producing analytical reports. However, the work of a consultant also presupposes knowledge of methods of data collection, both quantitative and qualitative, and being able to design a research project aimed to provide answers for a particular question. Hence the course will not only teach you how to conduct applied data analysis using surveys and large datasets, but it also prepares you to implement stand-alone quantitative research projects independently on your own. On the one hand, we will consider all the stages of conducting an individual-led quantitative project, from the initial conception and research questions to data analysis and presentation. On the other, you will be trained in the main techniques of quantitative data analysis using the SPSS statistical package.


Course requirements:

  • Basic statistics (descriptive stats, basics of estimation, regression, chi-square, and comparisons of means).
  • Able to get and interpret descriptive stats and regression in any software eg excel, Stata, R.
  • Basics of data management in any software is an asset (understanding the structure of the data file, data manipulation, data cleaning, and recoding).


Another requirement is to have a project or a topic in hand on which they want to do an applied analysis and report writing.  The students should also already have a datafile on which they can conduct analysis, or be willing to find a suitable dataset on the issue they want to study from publicly available sources.


Learning Objectives:

By the end of the course, students should be able to:

  • Design and conduct a quantitative research project;
  • Understand the difference between analytics for academic and applied projects;
  • Differentiate and apply appropriate quantitative methods in social and economic research, depending on research goals;
  • Understand the advantages and limitations of quantitative methods in conducting social, economic or developmental research


Skills-based objectives

By the end of the course, students should acquire the following skills:

  • Basic analytical skills to conduct an applied research project;
  • Use a variety of quantitative methods in an analytical report;
  • Use statistical data analysis software (e.g., SPSS) to manipulate the data and answer practical research questions in a project;
  • Learn how to write and present a research report to different stakeholders;
  • Learn how to become a consultant


Learning outcomes:

At the end of this course, the student should be able to:

  • Understand the goals, uses, advantages, and disadvantages of surveys and other quantitative methods of data collection;
  • Design research or an evaluation project using surveys or other quantitative data as evidence, formulate the research questions, and answer them with available data;
  • Understand the connection between the study design, research questions, methods to be used in social and evaluation research, and types of data analysis that can be produced;
  • Understand the difference between social science projects and evaluation or consultancy reports written for large international organizations;
  • Conduct a study answering specific research questions and applying the most common quantitative analysis techniques.


Language: English


Price: UAH 24 000


Date: May 24-31



Course outline:


Module 1

Lesson 1

Why quantitative research?

  • The importance of a sociological approach
  • Qualitative vs Quantitative research
  • The role of statistics in social research-Goals and uses
  • The process of research, formulating the research questions.

Teamwork: formulating research questions


Lesson 2

Research designs. Advantages and limitations of research designs.

Teamwork: practicing research designs


Lesson 3

Conceptualization vs measurement in a research process.

Teamwork: defining concepts, variables, and measurement in research


Lesson 4

Advantages of qualitative vs quantitative research.

Types of quantitative data analysis: explaining factors or searching for factors.

  • Data modeling techniques: Factor analysis, Cluster Analysis, Regression, and Multilevel Modelling


Lesson 5

Quantitative vs qualitative data sources. Review of available quantitative data sources.

Teamwork: a review of available quantitative sources.

Lab: Introduction to SPSS



Module 2

Lesson 1

Introduction to Survey Research

  • Common Uses of Surveys
  • Survey Collection methods
  • Merits and Demerits of Surveys


Lesson 2

Quantitative Data Analysis 1:

  • Making inferences in Chi-Square procedure
  • Bivariate tables-Level of Measurement and Statistical Analysis
  • Chi-squared Test of Independence for Nominal Variables
  • Recoding and Transformation of Variables

Lab: applying chi-square based techniques on your data. Recording of variables. Team assignments


Lesson 3

Quantitative Data Analysis 2:

  • Inferential Statistics in comparative Design
  • T-test for Independent and Dependent Means

Lab: running a comparative analysis of your Data. Team assignments.


Lesson 4

Organization of Surveys and Survey Sampling:

  • Survey as interview
  • Main principles of questionnaire construction; survey structure
  • Writing Survey Questions: Dos and Don’ts
  • Survey sampling
  • Using technology and supplementary materials in the survey interview


Lesson 5

Presenting Multivariate Analysis in a Report

  • Strategies of Presentation
  • Research questions and Levels of the Report
  • Writing sectional conclusions and Implications
    Discussion – Advantages and Disadvantages of Survey Research: Representativeness, ability to discover patterns and make inferences? Covering topics on meaning and process?



Module 3

Lesson 1

Understanding Regression

  • Correlation and Simple Regression
  • Regression model
  • Independent Variables in Regression
  • Regression Interpretations and writing about regression in a report.

Lab: practicing Regression


Lesson 2

Using Multiple Regression

  • Why multiple Regression
  • Standardised Coefficient
  • Regression diagnostics

Lab: practicing Multiple Regression. Teamwork


Lesson 3

Building Regression Models

  • SelectingVariables
  • Using Dummy Variables
  • Limitations of Regression and Comparison to other techniques

Lab: practicing Regression Models. Teamwork.


Lesson 4

Logistic Regression(if time permits)

  • Logistic Regression Model
  • Interpreting Logistic regression

Lab: practicing Logistic Regression


Lesson 5

Advantages and disadvantages of Quantitative Model-Building and Implications for Analysis
  • Advantages and disadvantages of modeling
  • Presenting your results and report writing. Why is storytelling important?

Consultation on your course projects.

Contact us to get more details:

Viber, WhatsApp +380 67 441 01 11

[email protected]