Simple Random Sampling without Replacement

1986 ◽  
pp. 1-30 ◽  
Author(s):  
Pieter G. de Vries
Keyword(s):  
Random Sampling ◽  
Simple Random Sampling ◽  
Sampling Without Replacement

scholarly journals Estimation of general parameters using ancillary information in simple random sampling without replacement

2021 ◽  
pp. 101754
Author(s):  
Nitesh Kumar Adichwal ◽  
Abdullah Ali H. Ahmadini ◽  
Yashpal Singh Raghav ◽  
Rajesh Singh ◽  
Irfan Ali
Keyword(s):  
Random Sampling ◽  
Simple Random Sampling ◽  
Sampling Without Replacement ◽  
Ancillary Information

scholarly journals Coalescence in Critical and Subcritical Galton-Watson Branching Processes

2012 ◽  
Vol 49 (03) ◽  
pp. 627-638 ◽  
Author(s):  
K. B. Athreya
Keyword(s):  
Random Sampling ◽  
Branching Process ◽  
Branching Processes ◽  
Simple Random Sampling ◽  
Sampling Without Replacement ◽  
Coalescence Time ◽  
Lines Of Descent

In a Galton-Watson branching process that is not extinct by the nth generation and has at least two individuals, pick two individuals at random by simple random sampling without replacement. Trace their lines of descent back in time till they meet. Call that generation X n a pairwise coalescence time. Similarly, let Y n denote the coalescence time for the whole population of the nth generation conditioned on the event that it is not extinct. In this paper the distributions of X n and Y n , and their limit behaviors as n → ∞ are discussed for both the critical and subcritical cases.

Simultaneous Estimation of Proportions in a Finite Population

1993 ◽  
Vol 43 (1-2) ◽  
pp. 65-74
Author(s):  
N. Mukhopadhyay ◽  
S. Chattopadhyay
Keyword(s):  
Random Sampling ◽  
Finite Population ◽  
Simple Random Sampling ◽  
Subject Classification ◽  
Simultaneous Estimation ◽  
Sampling Strategies ◽  
Sampling Without Replacement ◽  
First Order ◽  
Multistage Sampling

Sequential and multistage sampling strategies via simple random sampling without replacement, are proposed for simultaneously estimating several proportions in a finite population. Various asymptotic first-order properties are addressed, while some limited moderate sample performance have also been included. AMS (1980) Subject Classification: Primary 62L99; Secondary 62L12

scholarly journals Coalescence in Critical and Subcritical Galton-Watson Branching Processes

2012 ◽  
Vol 49 (3) ◽  
pp. 627-638 ◽  
Author(s):  
K. B. Athreya
Keyword(s):  
Random Sampling ◽  
Branching Process ◽  
Branching Processes ◽  
Simple Random Sampling ◽  
Sampling Without Replacement ◽  
Coalescence Time ◽  
Lines Of Descent

In a Galton-Watson branching process that is not extinct by the nth generation and has at least two individuals, pick two individuals at random by simple random sampling without replacement. Trace their lines of descent back in time till they meet. Call that generation Xn a pairwise coalescence time. Similarly, let Yn denote the coalescence time for the whole population of the nth generation conditioned on the event that it is not extinct. In this paper the distributions of Xn and Yn, and their limit behaviors as n → ∞ are discussed for both the critical and subcritical cases.

Item Count Technique in Ranked Set Sampling

2022 ◽  
pp. 26-41
Author(s):  
Beatriz Cobo ◽  
Elvira Pelle
Keyword(s):  
Simulation Study ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
Ranked Set Sampling ◽  
Alternative Methods ◽  
Randomized Response Technique ◽  
Randomized Response ◽  
Sampling Without Replacement ◽  
Questioning Techniques ◽  
Item Count Technique

In situations where the estimation of the proportion of sensitive variables relies on the observations of real measurements that are difficult to obtain, there is a need to combine indirect questioning techniques. In the present work, the authors will focus on the item count technique, with alternative methods of sampling, such as the ranked set sampling. They are based on the idea proposed by Santiago et al., which combines the randomized response technique proposed by Warner together with ranked set sampling. The authors will carry out a simulation study to compare the item count technique under ranked set sampling and under simple random sampling without replacement.

scholarly journals Bias Correction Technique for Estimating Quantiles of Finite Populations under Simple Random Sampling without Replacement

2021 ◽  
Vol 11 (05) ◽  
pp. 854-869
Author(s):  
Nicholas Makumi ◽  
Romanus Odhiambo Otieno ◽  
George Otieno Orwa ◽  
Festus Were ◽  
Habineza Alexis
Keyword(s):  
Bias Correction ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
Finite Populations ◽  
Sampling Without Replacement ◽  
Correction Technique

scholarly journals Modified Ratio-Cum-Product Estimators of Population Mean Using Two Auxiliary Variables

2020 ◽  
pp. 55-65
Author(s):  
J. O. Muili ◽  
E. N. Agwamba ◽  
Y. A. Erinola ◽  
M. A. Yunusa ◽  
A. Audu ◽  
...  
Keyword(s):  
Random Sampling ◽  
Finite Population ◽  
Simple Random Sampling ◽  
Degree Of Approximation ◽  
Ratio Estimator ◽  
Auxiliary Variables ◽  
Sampling Without Replacement ◽  
Sample Mean ◽  
Population Mean ◽  
Product Estimator

A percentile is one of the measures of location used by statisticians showing the value below which a given percentage of observations in a group of observations fall. A family of ratio-cum-product estimators for estimating the finite population mean of the study variable when the finite population mean of two auxiliary variables are known in simple random sampling without replacement (SRSWOR) have been proposed. The main purpose of this study is to develop new ratio-cum-product estimators in order to improve the precision of estimation of population mean in sample random sampling without replacement using information of percentiles with two auxiliary variables. The expressions of the bias and mean square error (MSE) of the proposed estimators were derived by Taylor series method up to first degree of approximation. The efficiency conditions under which the proposed ratio-cum-product estimators are better than sample man, ratio estimator, product estimator and other estimators considered in this study have been established. The numerical and empirical results show that the proposed estimators are more efficient than the sample mean, ratio estimator, product estimator and other existing estimators.

AN EFFICIENT CLASS OF PRODUCT ESTIMATORS USING MEASURES OF DISPERSIONS

2021 ◽  
Vol 21 (2) ◽  
pp. 347-354
Author(s):  
MUHAMMAD IJAZ ◽  
TOLGA ZAMAN ◽  
BUSHRA HAIDER ◽  
SYED MUHAMMAD ASIM
Keyword(s):  
Standard Deviation ◽  
Mean Square Error ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
Mean Deviation ◽  
Mean Square ◽  
Sampling Without Replacement ◽  
Population Mean ◽  
Class Of Estimators ◽  
Secondary Information

The study suggests a class of product estimators for estimating the population mean of variable under investigation in simple random sampling without replacement (SRSWOR) scheme when secondary information on standard deviation, mean deviation, and quartile deviation is available. The expression for Bias and Mean Square Error (MSE) has been derived. A comparison is made both theoretically and numerically with other existing product estimators. It is concluded that compared to other product type estimators, suggested class of estimators estimate the population mean more efficiently.

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