Learn how representative samples and random samples differ and why combining them minimizes sampling bias for accurate data.

Discover how to determine the ideal percentage of a population for a representative sample to ensure accurate data analysis with minimal sampling error.

XRF sample preparation is a precise method of preparing analytes for elemental analysis. For example, organic samples being analyzed by XRF must be uniformly homogenized through the use of hydraulic ...

Single-cell proteomics provides information about a cell at its protein level, which can prove useful for anticancer drug resistance and cell differentiation research. However, current proteomics ...

Precise protein quantification is a crucial step in workflows involving protein extraction, isolation, and analysis. Accurate knowledge of the concentration of your protein sample is essential for ...

Sampling is a technique in which samples are drawn at random (without any favor or bias). For this, suitable measures or procedures may be laid down and adopted according to the nature and ...

Heat treatment originated in the Bronze Age and was developed further for processing iron (blacksmithing) around 800 BC, reaching a first peak with the production of Damascus steel at the start of the ...

By Courtney Kennedy, Andrew Mercer, Scott Keeter, Nick Hatley, Kyley McGeeney and Alejandra Gimenez As the costs and nonresponse rates of traditional, probability-based surveys seem to grow each year, ...

This study looks at how national public opinion polling in the United States changed from 2000 to 2022. It focuses on two aspects: the sample source(s) – that is, where the survey takers came from – ...

I sent my forage sample to two different laboratories and received different results. How can I know which one is right?” ...