Research studies often require the collection of data from various segments of a population to draw meaningful conclusions. Allocating sample sizes within research is a critical aspect that significantly impacts the validity and reliability of findings. Several strategies exist to determine how samples are distributed across different segments of a population. This essay explores four key methods utilized in research for allocating sample sizes: Proportional Allocation, Stratified Sampling, Different Sample Sizes for Precision, and Resource Availability.
See Full PDF See Full PDFJournal of Health Specialties
Download Free PDF View PDF
Proceedings on Engineering Sciences
Download Free PDF View PDF
Advances and Applications in Statistics
Download Free PDF View PDF
Communications in Statistics - Simulation and Computation
Download Free PDF View PDF
Download Free PDF View PDF
Download Free PDF View PDF
Computational Statistics & Data Analysis
Download Free PDF View PDF
Journal of clinical epidemiology
Download Free PDF View PDF
This is the second article of a three-part series that continues the discussion on the fundamentals of writing research protocols for quantitative, clinical research studies. In this editorial, the author discusses some considerations for including information in a research protocol on the study design and approach of a research study. This series provides a guide for undergraduate researchers interested in publishing their protocol in the Undergraduate Research in Natural and Clinical Sciences and Technology (URNCST) Journal.
Download Free PDF View PDF
Biometrics & Biostatistics International Journal
The possibility that researchers should be able to obtain data from all cases is questionable. There is a need; therefore, this article provides a probability and non-probability sampling. In this paper we studied the differences and similarities of the two with approach that is more of fritter away time, cost sufficient with energy required throughout the sample observed. The pair shows the differences and similarities between them, different articles were reviewed to compare the two. Quota sampling and Stratified sampling are close to each other. Both require the division into groups of the target population. The main goal of both methods is to select a representative sample and facilitate sub-group research. There are major variations, however. Stratified sampling uses simple random sampling when the categories are generated; sampling of the quota uses sampling of availability. For stratified sampling, a sampling frame is necessary, but not needed for quota sampling. More specifi.
Download Free PDF View PDF
