Topic
Population proportion
About: Population proportion is a research topic. Over the lifetime, 247 publications have been published within this topic receiving 4099 citations.
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TL;DR: The finite population proportion of a sensitive characteristic is estimated indirectly by using Randomized Response (RR) Techniques (RRTs) pioneered by Warner (1965) followed by several other RRT Techniques as mentioned in this paper.
Abstract: The finite population proportion of a sensitive characteristic is estimated indirectly by using Randomized Response (RR) Techniques (RRT’s) pioneered by Warner (1965) followed by several other RRT’...
1 citations
01 Jan 2003
TL;DR: In this paper, a two-stage procedure is proposed to estimate the population proportion of a sensitive group by combining the direct question method and a modified randomized response technique, which is verified that the proposed procedure is more efficient than existing methods under some mild conditions.
Abstract: A two-stage procedure is proposed to estimate the population proportion of a sensitive group. The proposed procedure is obtained by combining the direct question method and a modified randomized response technique. It is verified that the proposed procedure is more efficient than existing methods under some mild conditions.
1 citations
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TL;DR: The prediction approach is used to define a new estimator that presents desirable efficiency properties that can be used to estimate a finite population proportion when there are missing values.
1 citations
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TL;DR: The research indicates that the population proportion of successful students in a course of Business Statistics does not depend on their gender; likewise, the proportion of success is not affected nor depends on the manner on how these students decided to take their course instruction, whether online or in a classroom.
Abstract: This article describes the students' academic progress in an online course of business statistics through interactive software assignments and diverse educational homework, which helps these students to build their own e-learning through basic competences; i.e. interpreting results and solving problems. Cross-tables were built for the categorical variables: course-type (at 2 levels of classification: “online” and “classroom”) and the 2 levels of gender, where the dependent variable was the proportion of successful and unsuccessful students. The statistical analysis was performed via the Chi-square test for which we found that the variable “course-type” was not significant (p-value=0.512). Similarly, the variable “gender” was not significant (pvalue=0.652). Both conclusions were also confirmed via the Normal distribution z-test with similar p-values: 0.516 for course-type and 0.556 for gender. Thus, our research indicates that the population proportion of successful students in a course of Business Statistics does not depend on their gender; likewise, the proportion of success is not affected nor depends on the manner on how these students decided to take their course instruction, whether online or in a classroom.
1 citations
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01 Jan 2010TL;DR: In this article, the authors learn how to use sample data to estimate a population mean, a population variance, and a population proportion, and the standard error of these estimates is considered.
Abstract: We learn how to use sample data to estimate a population mean, a population variance, and a population proportion. We discuss point estimates, which are single-value estimates of the parameter. The standard error of these estimates is considered. We also consider interval estimates that contain the parameter with specified degrees of confidence.
1 citations