2017
DOI: 10.1080/00949655.2017.1319948
|View full text |Cite
|
Sign up to set email alerts
|

Power comparison of the Kolmogorov–Smirnov test under ranked set sampling and simple random sampling

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2018
2018
2024
2024

Publication Types

Select...
5
2

Relationship

1
6

Authors

Journals

citations
Cited by 9 publications
(3 citation statements)
references
References 16 publications
0
3
0
Order By: Relevance
“…Slovin's Equation was used in determining the random of population and selection of the respondents via simple random sampling. Simple random sampling is described by Sevil and Yildiz (2017) as a situation when a researcher chooses a set of samples from a large population. Specifically grade 12 students were the chosen study participants coming from different academic strands namely; ABM (Accountancy Business and Management), HUMSS (Humanities and Social Sciences), IA (Industrial Arts), STEM (Science and Technology, Engineering and Mathematics) and HE (Home Economics).…”
Section: Method:-mentioning
confidence: 99%
“…Slovin's Equation was used in determining the random of population and selection of the respondents via simple random sampling. Simple random sampling is described by Sevil and Yildiz (2017) as a situation when a researcher chooses a set of samples from a large population. Specifically grade 12 students were the chosen study participants coming from different academic strands namely; ABM (Accountancy Business and Management), HUMSS (Humanities and Social Sciences), IA (Industrial Arts), STEM (Science and Technology, Engineering and Mathematics) and HE (Home Economics).…”
Section: Method:-mentioning
confidence: 99%
“…Recently, statistical inference for mean, total, variance and quantiles have been discussed by Ozturk [25,26,27], Ozturk and Bayramoglu Kavlak [28,29] in finite population setting. Also, Sevil and Yildiz [30,31] and Yildiz and Sevil [32,33] proposed the following empirical distribution function (EDF) in finite population setting.…”
Section: Introductionmentioning
confidence: 99%
“…If the distribution function of the sheep weights is estimated, both the quantiles and the probabilities corresponding to the specific quantiles can be obtained. Unlike the studies Sevil and Yildiz [30,31] and Yildiz and Sevil [32,33], we provide design-based estimators for distribution function. These estimators use the information of inclusion probabilities as well.…”
Section: Introductionmentioning
confidence: 99%