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Convenience Sampling Method

Convenience Sampling Method

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.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...

Crossover Experiments

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.

Experimental Designs

Experimental Designs

An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...

Randomized Experiments

Randomized Experiments

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...

Factorial Design

Factorial Design

Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...

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Related Experiment Video

Updated: May 25, 2026

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Published on: September 16, 2015

Convenience experimentation.

¹Department of Philosophy, University of Bielefeld, Universitätsstr. 25, 33615 Bielefeld, Germany. ulrich.krohs@uni-bielefeld.de

Studies in History and Philosophy of Biological and Biomedical Sciences

|February 14, 2012

Summary

This summary is machine-generated.

Systems biology

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Last Updated: May 25, 2026

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Area of Science:

Systems biology
Molecular cell biology
Network modeling

Background:

The whole-cell perspective distinguishes systems biology from prior molecular cell biology approaches.
High-throughput 'omic' data generation, enabled by commercial analytic equipment, underpins systems biology.
Convenience experimentation, driven by readily available supplies, characterizes modern systems biology.

Purpose of the Study:

To investigate the epistemic consequences of convenience experimentation in systems biology.
To analyze the shift in scientific methodology driven by data abundance.
To examine the evolving modes of scientific evaluation in systems biology.

Main Methods:

Analysis of the epistemic shifts in scientific practice.
Conceptual examination of hypothesis-driven vs. data-driven research.
Evaluation of the impact of 'convenience experimentation' on scientific inquiry.

Main Results:

Systems biology, driven by convenience experimentation, shifts from hypothesis-testing or exploratory modes to a 'gathering' mode.
Model building is increasingly driven by vast datasets from convenience experimentation.
The abundance of data necessitates a shift in evaluation towards an exploratory endeavor.

Conclusions:

Reliance on convenience experimentation fundamentally alters the scientific method in systems biology.
The 'gathering mode' of science requires new evaluation strategies.
Systems biology's epistemic landscape is reshaped by data-driven, convenience-focused research.