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Sampling Methods: Overview01:06

Sampling Methods: Overview

2.0K
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
2.0K
Random Sampling Method01:09

Random Sampling Method

14.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
14.0K
Randomized Experiments01:13

Randomized Experiments

8.8K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
8.8K
Cluster Sampling Method01:20

Cluster Sampling Method

13.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.9K
Data Collection by Experiments01:13

Data Collection by Experiments

26.8K
Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
26.8K
Stratified Sampling Method01:16

Stratified Sampling Method

14.4K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
14.4K

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Related Experiment Video

Updated: Dec 29, 2025

Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories
04:15

Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories

Published on: February 23, 2024

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Conducting online virtual environment experiments with uncompensated, unsupervised samples.

Bernd Huber1, Krzysztof Z Gajos1

  • 1School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States of America.

Plos One
|January 31, 2020
PubMed
Summary
This summary is machine-generated.

Online virtual environment experiments with unsupervised samples yield high-quality data. This research demonstrates the feasibility of web-based studies, replicating lab findings across diverse devices for robust scientific conclusions.

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Area of Science:

  • Psychology
  • Human-Computer Interaction
  • Virtual Reality

Background:

  • Web-based experimentation offers advantages like larger, diverse samples and faster research cycles.
  • Concerns exist regarding data quality from unsupervised, online participants.
  • Virtual environments present a novel platform for online research.

Purpose of the Study:

  • To investigate the feasibility and data quality of online experiments using virtual environments.
  • To determine if findings from virtual environment studies generalize across various devices.
  • To assess the viability of using uncompensated samples in online virtual reality research.

Main Methods:

  • Conceptual replication of two prior virtual environment experiments.
  • Data collection from participants using diverse devices (desktops, mobiles, VR headsets).
  • Analysis of results to compare with previous laboratory-based findings.

Main Results:

  • Replication of findings from traditional laboratory settings was successful.
  • Results remained consistent across all tested device types.
  • High-quality data was obtained, supporting robust conclusions.

Conclusions:

  • Online experimentation in virtual environments with uncompensated samples is feasible.
  • Virtual environment studies can yield generalizable and high-quality data.
  • This approach accelerates the cycle from theory to empirical evidence.