scholarly journals Comparison of Variance Estimators for Systematic Environmental Sample Surveys: Considerations for Post-Stratified Estimation

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 772
Author(s):  
Bryce Frank ◽  
Vicente J. Monleon
Keyword(s):  
Random Sampling ◽  
Simple Random Sampling ◽  
National Forest Inventory ◽  
Point Estimation ◽  
Systematic Sampling ◽  
Sampling Variance ◽  
Variance Estimators ◽  
The Past ◽  
Point Estimators ◽  
Species Specific

The estimation of the sampling variance of point estimators under two-dimensional systematic sampling designs remains a challenge, and several alternative variance estimators have been proposed in the past few decades. In this work, we compared six alternative variance estimators under Horvitz-Thompson (HT) and post-stratification (PS) point estimation regimes. We subsampled a multitude of species-specific forest attributes from a large, spatially balanced national forest inventory to compare the variance estimators. A variance estimator that assumes a simple random sampling design exhibited positive relative bias under both HT and PS point estimation regimes ranging between 1.23 to 1.88 and 1.11 to 1.78 for HT and PS, respectively. Alternative estimators reduced this positive bias with relative biases ranging between 1.01 to 1.66 and 0.90 to 1.64 for HT and PS, respectively. The alternative estimators generally obtained improved efficiencies under both HT and PS, with relative efficiency values ranging between 0.68 to 1.28 and 0.68 to 1.39, respectively. We identified two estimators as promising alternatives that provide clear improvements over the simple random sampling estimator for a wide variety of attributes and under HT and PS estimation regimes.

scholarly journals Customer Perceptions of Skills of Agents in Effectively Managing Their Needs within a Call Center

2017 ◽  
Vol 9 (2) ◽  
pp. 58
Author(s):  
Devina Oodith
Keyword(s):  
Random Sampling ◽  
Call Center ◽  
Interpersonal Skills ◽  
Simple Random Sampling ◽  
Training And Development ◽  
Service Environment ◽  
Customer Perceptions ◽  
The Past ◽  
Public Sector Service ◽  
Sector Service

The world’s dynamics and demands of employment and production have evolved over the past decade. Human resources has today become the single largest unrestrained resource and many firms are striving to enhance competence and interaction between its customers and itself via the customer call center through enhanced skills, knowledge, ability and attitude by fostering better interpersonal skills and through the promotion of training and development of their call center agents. This study was undertaken in EThekwini (Durban), South Africa and was conducted within a Public Sector service environment comprising of four major call centers employing a total of 240 call center agents. Using simple random sampling, 220 customers were drawn from all consumers subscribing to e-billing in EThekwini (Durban). Data for the customer sample was collected using a precoded, self-developed questionnaire whose psychometric properties were statistically determined. Data was analyzed using descriptive and inferential statistics. The results specify that agents were unsuccessful in handling customers’ needs timeously and efficiently and that most customers felt burdened by being transferred to other agents due to the incompetence of original agents in handling their queries/complaints. Furthermore it was found that there was an overall lack of empathy from agents in following-up after a customer communication to ensure that the customer was satisfied with their experience within the call center. Based on the results of the study recommendations have been made to manage the interaction between the customers and call center agents more competently and efficiently.

scholarly journals ln-Type Variance Estimators in Simple Random Sampling

2020 ◽  
pp. 689-696
Author(s):  
Hatice Oncel Cekim ◽  
Cem Kadilar
Keyword(s):  
Exponential Type ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
The Other ◽  
Data Sets ◽  
Population Variance ◽  
Sampling Studies ◽  
Variance Estimators ◽  
Study Support ◽  
First Time

Until now, various types of estimators have been used for estimating the population variance in simple random sampling studies, including ratio, product, regression and exponential-type estimators. In this article, we propose a family of -type estimators for the first time in the simple random sampling and show that they are more efficient than the other types of estimators under certain conditions obtained theoretically. Numerical illustrations and a simulation study support our findings in theory. In addition, it has been shown how to determine the optimal points in order to reach the minimum MSE values with the properties of the ln-type estimators in the different data sets.

Sampling moving strata on two occasions

1993 ◽  
Vol 23 (1) ◽  
pp. 96-100 ◽  
Author(s):  
Paul C. Van Deusen
Keyword(s):  
Random Sampling ◽  
Simple Random Sampling ◽  
Systematic Sampling ◽  
Forest Types ◽  
Time Periods ◽  
Over Time

When forest types define the strata, the boundaries will often move over time. A method is presented for producing estimates of stratum means at two time periods when the stratum boundaries are changing. The method is valid when the samples are taken under either simple random sampling or systematic sampling.

scholarly journals On the Estimation of Population Mean Under Systematic Sampling Using Auxiliary Attributes

2016 ◽  
Vol 1 (1-2) ◽  
pp. 21-25 ◽  
Author(s):  
Usman Shahzad
Keyword(s):  
Mean Square Error ◽  
Random Sampling ◽  
Simple Random Sampling ◽  
Sampling Scheme ◽  
Systematic Sampling ◽  
Mean Square ◽  
Numerical Illustration ◽  
Systematic Random Sampling ◽  
Population Mean ◽  
New Family

Naik and Gupta (1996), Singh et al. (2007) and Abd-Elfattah et al. (2010) introduced some estimators for estimating population mean using available auxiliary attributes under simple random sampling scheme. We adapt these estimators under systematic random sampling scheme using available auxiliary attributes. Further, a new family of estimators is proposed for the estimation of population mean under systematic random sampling scheme. The properties such as bias and mean square error of the proposed estimators are derived. From numerical illustration it is shown that proposed estimators are more efficient than the reviewed ones.

Properties of point estimators

2019 ◽  
pp. 91-110
Author(s):  
M. D. Edge
Keyword(s):  
Mean Squared Error ◽  
Point Estimation ◽  
Statistical Decision Theory ◽  
Robust Estimator ◽  
Statistical Decision ◽  
Variance Estimators ◽  
A Value ◽  
Using Data ◽  
Point Estimators ◽  
The Right

Point estimation is the attempt to identify a value associated with some underlying process or population using data. The unknown number that is the target of estimation is called an estimand. An estimator is a function that takes in data and produces an estimate. In this chapter, estimators are evaluated according to a number of criteria. An unbiased estimator is one whose expected value is equal to the estimand—in lay terms, it is accurate. Low-variance estimators, which are precise, are also evaluated. Consistent estimators converge to the estimand as the number of data collected approaches infinity. Mean squared error is the expected squared difference between the estimator and the estimand. Efficient estimators are those that converge to the estimand relatively quickly—i.e., fewer data are necessary to get close to the right answer. An optional section discusses statistical decision theory, which is a general framework for evaluating estimators. Finally, some ideas of robustness are discussed. A robust estimator is one that can still provide useful information even if the model is not quite right or the data are contaminated.

Extending Takahasi‐Sakasegawa’s Indirect Response Technique to Cover Sensitive Surveys in Unequal Probability Sampling

2007 ◽  
Vol 59 (3-4) ◽  
pp. 265-276 ◽  
Author(s):  
Sanghamitra Pal
Keyword(s):  
Random Sampling ◽  
Simple Random Sampling ◽  
Subject Classification ◽  
Randomized Response ◽  
Probability Sampling ◽  
Indirect Response ◽  
Variance Estimators ◽  
Unequal Probability Sampling ◽  
Unequal Probability ◽  
Sensitive Characteristics

Abstract: Randomized Response (RR) Technique (RRT), introduced by Warner (1965), is a well‐known way to unbiasedly estimate proportions of people bearing sensitive characteristics. Takahasi and Sakasegawa (1977) narrated a novel procedure avoiding any particular RR device unlike most researchers in this field. Most RRT’s in the literature give estimators for population totals and variance estimators thereof, allowing exclusively simple random sampling with replacement (SRSWR) schemes, including as well the above too. We present formulae applicable to general varying probability sampling, even without replacement applying Takahasi‐ Sakasegawa device. AMS (2000) Subject Classification: 62D05.

scholarly journals Customer Perceptions of Skills of Agents in Effectively Managing Their Needs within a Call Center

2017 ◽  
Vol 9 (2(J)) ◽  
pp. 58-75
Author(s):  
Devina Oodith
Keyword(s):  
Random Sampling ◽  
Call Center ◽  
Interpersonal Skills ◽  
Simple Random Sampling ◽  
Training And Development ◽  
Service Environment ◽  
Customer Perceptions ◽  
The Past ◽  
Public Sector Service ◽  
Sector Service

The world’s dynamics and demands of employment and production have evolved over the past decade. Human resources has today become the single largest unrestrained resource and many firms are striving to enhance competence and interaction between its customers and itself via the customer call center through enhanced skills, knowledge, ability and attitude by fostering better interpersonal skills and through the promotion of training and development of their call center agents. This study was undertaken in EThekwini (Durban), South Africa and was conducted within a Public Sector service environment comprising of four major call centers employing a total of 240 call center agents. Using simple random sampling, 220 customers were drawn from all consumers subscribing to e-billing in EThekwini (Durban). Data for the customer sample was collected using a precoded, self-developed questionnaire whose psychometric properties were statistically determined. Data was analyzed using descriptive and inferential statistics. The results specify that agents were unsuccessful in handling customers’ needs timeously and efficiently and that most customers felt burdened by being transferred to other agents due to the incompetence of original agents in handling their queries/complaints. Furthermore it was found that there was an overall lack of empathy from agents in following-up after a customer communication to ensure that the customer was satisfied with their experience within the call center. Based on the results of the study recommendations have been made to manage the interaction between the customers and call center agents more competently and efficiently.

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