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Sampling for Beginners

via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

5 weeks, 1 hour a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

Found in

Sampling Courses

Overview

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This course introduces the fundamentals of selecting a sample for research involving human participants. It takes a practical approach to sampling and will provide you with a clear understanding of why samples are needed, an overview of common sampling techniques, and information around ethical research and minimizing bias.

Syllabus

What Is Sampling?
- This module introduces the foundations of sampling in research and explores how researchers define and select populations for study. You will learn the key distinctions between populations, samples, and elements, examine the relationship between samples and the broader populations they represent, and evaluate whether existing datasets provide suitable samples for addressing your research questions.
What Are Common Sampling Methods?
- This module explores the two main approaches to sampling in research: probability and non-probability sampling. You will learn how different sampling methods are used to select participants or cases, examine the role of sampling frames in probability sampling, and evaluate the strengths, limitations, and practical applications of common non-probability sampling approaches, including convenience sampling.
What Are the Practical and Ethical Challenges of Sampling?
- This module examines the ethical and practical challenges involved in recruiting research participants, particularly from populations that may be difficult to define, access, or engage. You will explore key considerations when identifying and contacting potential participants, learn strategies for working with hard-to-reach groups, and evaluate the strengths and limitations of recruitment approaches such as snowball sampling.
How Can I Reduce Error and Bias in Sampling?
- This module explores sampling error and the factors that can affect how well a sample represents a wider population. You will examine the key sources of sampling error, including sampling variance and sampling bias, learn how issues such as non-response and incomplete sampling frames can influence research findings, and develop strategies for reducing error while balancing sample size with practical, ethical, and research considerations.
Sampling for Beginners Glossary
- In addition to the glossary you’ll find woven throughout the course, you can find the full glossary collated in one place here.