Research Methodologies (Coursera)

Research Methodologies (Coursera)

This course focuses on research methodologies. In this vein, the focus will be placed on qualitative and quantitative research methodologies, sampling approaches, and primary and secondary data collection. The course begins with a discussion on qualitative research approaches, looking at focus groups, personal interviews, ethnography, case studies and action research.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

We will also discuss quantitative research methods with a focus on experimental research design and survey methodology. There will be an exploration of the sampling design process and different sampling approaches, including probability and non-probability sampling as well as sample size and non-response issues. We will look at the nature and scope of primary and secondary data, and the importance of measurement. We will look at the role of the Internet in market research as well as non-comparative scaling techniques. The course ends with a discussion on different data collection approaches, with a focus on observation, content analysis, narrative research, phenomenology, and the collection of data using ethnography.
Course 2 of 4 in the Market Research Specialization.

What You Will Learn

  • Different research methodologies
  • Different sampling approaches
  • Primary and secondary data collection approaches

Syllabus

Week 1
This week begins with a discussion on qualitative research approaches, looking at focus groups, personal interviews, ethnography, case study and action research. The week ends with a discussion of quantitative research methods with a focus on experimental research design and survey methodology.

Week 2
The week begins with a discussion on the sampling design process and continues with different sampling approaches, including probability and non-probability sampling. The week ends with a discussion on sample size and non-response issues.

Week 3
The week begins with a discussion of the nature and scope of secondary data and continues with a discussion of primary data and the importance of measurement. The week ends with the role of the Internet in market research and a discussion about non-comparative scaling techniques.

Week 4
The week starts a discussion on different data collection approaches with a focus on observation, case study and content analysis. The week continues with a focus on narrative research, phenomenology and the action research project. The week ends with a discussion of collecting data using ethnography.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Collection and Processing with Python (Coursera) Coursera
University of Michigan

Data Collection and Processing with Python (Coursera)

This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a “tag recommender” for the flickr photo sharing site.

Nov 2nd 2026
3 Weeks
Community Engagement in Research and Population Health (Coursera) Coursera
University of Rochester

Community Engagement in Research and Population Health (Coursera)

Welcome to the Community Engagement in Population Health course! As you will learn, the health system is in the midst of a critical transition. The current system is not sustainable with escalating costs, mediocre health outcomes, and unacceptable disparities. This course will first discuss the current system, including definitions of population health and social determinants of health, and how the US compares to other countries on the triple aim –lower cost, better care, and a healthier population.

Nov 16th 2026
4 Weeks
Prepare Data for Exploration (Coursera) Coursera
Google

Prepare Data for Exploration (Coursera)

This is the third course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. As you continue to build on your understanding of the topics from the first two courses, you’ll also be introduced to new topics that will help you gain practical data analytics skills. You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives and how to organize and protect your data. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Nov 2nd 2026
5-12 Weeks
Pre-MBA Statistics (Coursera) Coursera
Indian Institute of Management Ahmedabad (IIMA)

Pre-MBA Statistics (Coursera)

Welcome to the Pre-MBA Statistics course! By the end of this course, you will be able to describe how statistics can be used to summarize, analyze, and interpret data. This course introduces you to some aspects of descriptive and inferential statistics. You will learn to distinguish between various data types and describe the operations that you can execute with each type of data and the right tools to use.

Nov 9th 2026
5-12 Weeks
Data Management for Clinical Research (Coursera) Coursera
Vanderbilt University

Data Management for Clinical Research (Coursera)

This course presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research. Understanding and implementing solid data management principles is critical for any scientific domain. Regardless of your current (or anticipated) role in the research enterprise, a strong working knowledge and skill set in data management principles and practice will increase your productivity and improve your science. Our goal is to use these modules to help you learn and practice this skill set.

Nov 9th 2026
5-12 Weeks
Sampling People, Networks and Records (Coursera) Coursera
University of Michigan

Sampling People, Networks and Records (Coursera)

Good data collection is built on good samples. But the samples can be chosen in many ways. Samples can be haphazard or convenient selections of persons, or records, or networks, or other units, but one questions the quality of such samples, especially what these selection methods mean for drawing good conclusions about a population after data collection and analysis is done. Samples can be more carefully selected based on a researcher’s judgment, but one then questions whether that judgment can be biased by personal factors.

Nov 2nd 2026
5-12 Weeks
Probabilistic Graphical Models 2: Inference (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 2: Inference (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more.

Nov 9th 2026
5-12 Weeks
Framework for Data Collection and Analysis (Coursera) Coursera
University of Maryland, College Park

Framework for Data Collection and Analysis (Coursera)

This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan.

Oct 26th 2026
4 Weeks
Python and Statistics for Financial Analysis (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Python and Statistics for Financial Analysis (Coursera)

Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry. The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data.

Nov 2nd 2026
4 Weeks
Introduction to Probability and Data with R (Coursera) Coursera
Duke University

Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Oct 26th 2026
5-12 Weeks
Advanced Manufacturing Process Analysis (Coursera) Coursera
University at Buffalo,The State University of New York

Advanced Manufacturing Process Analysis (Coursera)

Extreme variability is a fact of life in manufacturing environments, impacting product quality and yield. Through this course, students will learn why performing advanced analysis of manufacturing processes is integral for diagnosing and correcting operational flaws in order to improve yields and reduce costs. Gain insights into the best ways to collect, prepare and analyze data, as well as computational platforms that can be leveraged to collect and process data over sustained periods of time. Become better prepared to participate as a member of an advanced analysis team and share valuable inputs on effective implementation.

Nov 2nd 2026
3 Weeks
Exploration et production de données pour les entreprises (Coursera) Coursera
University of Illinois at Urbana-Champaign

Exploration et production de données pour les entreprises (Coursera)

Ce cours fournit un cadre analytique afin de vous aider à évaluer les problèmes clés de manière structurée. Il vous procurera également des outils afin de mieux gérer les incertitudes qui envahissent et compliquent les processus des entreprises. Plus précisément, vous serez initié(e) aux statistiques et à la manière de résumer les données. Vous découvrirez les concepts de fréquence, de loi normale, d’études statistiques, de l’échantillonnage et des intervalles de confiance.

Nov 9th 2026
4 Weeks