Cochran's Rule for Simple Random Sampling

Sugden, R. A.; Smith, T. M. F.; Rh, Jones

doi:10.1111/1467-9868.00264

Cited by 29 publications

(13 citation statements)

References 12 publications

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“…In research studies, a sample has to be obtained if it is not possible to include all the subjects in the study population [32]. The sample size for this study was computed using Cochran's [35] method through which the minimum sample size of 385 was obtained [35,36].…”

Section: Methodsmentioning

confidence: 99%

An Investigation of the Effects of Customer's Educational Attainment on their Adoption of E-banking in Nigeria

Oyeleye¹,

Sanni²,

Shittu³

2015

J Internet Bank Commer

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The study aimed at investigating the effects of customers' educational attainment on their adoption of e-banking in Nigeria and adopted the extension of technology adoption model (TAM) by adding customers' educational attainment to it. The researcher used primary data collected through administered structured questionnaire. The researcher employed the SPSS (16.0) for descriptive statistical analysis and the Structural Equation Model (SEM) as statistical test

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Section: Methodsmentioning

confidence: 99%

An Investigation of the Effects of Customer's Educational Attainment on their Adoption of E-banking in Nigeria

Oyeleye¹,

Sanni²,

Shittu³

2015

J Internet Bank Commer

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“…The minimum sample size (n) estimation for the survey was 400 individuals based on Cochran’s theorem [13]. Survey participants were male and female heads of household both members and non members of the CHF.…”

Section: Methodsmentioning

confidence: 99%

Feasibility of introducing compulsory community health fund in low resource countries: views from the communities in Liwale district of Tanzania

Marwa

Njau

Kessy

et al. 2013

BMC Health Serv Res

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BackgroundIn 1995, Tanzania introduced the voluntary Community Health Fund (CHF) with the aim of ensuring universal health coverage by increasing financial investment in the health sector. The uptake of the CHF is low, with an enrolment of only 6% compared to the national target of 75%. Mandatory models of community health financing have been suggested to increase enrolment and financial capacity. This study explores communities’ views on the introduction of a mandatory model, the Compulsory Community Health Fund (CCHF) in the Liwale district of Tanzania.MethodsA cross-sectional study which involved 387 participants in a structured face to face survey and 33 in qualitative interviews (26 in focus group discussions (FGD) and 7 in in-depth interviews (IDI). Structured survey data were analyzed using SPSS version 16 to produce descriptive statistics. Qualitative data were analyzed using content analysis.Results387 people completed a survey (58% males), mean age 38 years. Most participants (347, 89.7%) were poor subsistence farmers and 229 (59.2%) had never subscribed to any form of health insurance scheme. The idea of a CCHF was accepted by 221 (57%) survey participants. Reasons for accepting the CCHF included: reduced out of pocket expenditure, improved quality of health care and the removal of stigma for those who receive waivers at health care delivery points. The major reason for not accepting the CCHF was the poor quality of health care services currently offered. Participants suggested that enrolment to the CCHF be done after harvesting when the population were more likely to have disposable income, and that the quality care of care and benefits package be improved.ConclusionsThe CHF is acceptable to the most of study participants and feasible in rural Tanzania as an alternative mechanism to finance health care for the rural poor. Community members are willing to join the scheme provided they are well informed, involved in the design and implementation, and assured quality health care. Strong political will and a supportive environment are key ingredients for the success of the CCHF.

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“…23 enables to split sets into 5 classes while respecting the Cochran rule, i.e. 80% of the classes having at least 5 elements [21]. 45 enables to split sets into 9 classes of 5 elements, knowing that 46 is the maximal value that do not discard the GREYC W2 dataset.…”

Section: Datasetsmentioning

confidence: 99%

Statistical modeling of keystroke dynamics samples for the generation of synthetic datasets

Migdal

Rosenberger

2019

Future Generation Computer Systems

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Biometrics is an emerging technology more and more present in our daily life. However, building biometric systems requires a large amount of data that may be difficult to collect. Collecting such sensitive data is also very time consuming and constrained, s.a. GDPR legislation in Europe. In the case of keystroke dynamics, most existing databases have less than 200 users. For these reasons, it is crucial for this biometric modality to be able to generate a significant and realistic synthetic dataset of keystroke dynamics samples. We propose in this paper an original approach for the generation of synthetic keystroke data given samples from known users as a first step towards the generation of synthetic datasets. Experimental results show the capability of the proposed statistical model to generate realistic samples from existing datasets in the literature.

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Cochran's Rule for Simple Random Sampling

Cited by 29 publications

References 12 publications

An Investigation of the Effects of Customer's Educational Attainment on their Adoption of E-banking in Nigeria

An Investigation of the Effects of Customer's Educational Attainment on their Adoption of E-banking in Nigeria

Feasibility of introducing compulsory community health fund in low resource countries: views from the communities in Liwale district of Tanzania

Statistical modeling of keystroke dynamics samples for the generation of synthetic datasets

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