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Employing Statistical Analysis in Public Relations Researches: (An Analytical Study of the Theses and Dissertations of Public Relations for the Period from 2005 to 2012)
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Public relations are amongst the social sciences that rely on scientific methods in achieving new knowledge or resolving existing problems by means of its scientific researches that are often applied and require a classification in terms of their results’ analysis. It also requires subtle statistical processes whether in constructing their material or in analyzing and interpreting their results.

This research seeks to identify the relation between public relations and statistics, and the significance a researcher or practitioner in the domain of public relations should assign to statistics being one of the important criteria in identifying the accuracy and objectivity of researches;  by answering the main question of this research: “How far has statistical analysis been employed in researches of public relations”; and “Has the implementation of statistical methods been suitable for the requirements of these researches?”.

In order to achieve the objective of this work, the researchers have adopted a descriptive approach by analyzing the content of theses and dissertations of public relations in the College of Mass Communication, Baghdad University, during the period 2005-2012, numbering 82 studies.

The results showed little employment of statistical analysis in researches of public relations, for most researchers have not used it within their researches and limited them to using tabular presentation and frequency distribution. Some statistical methods used in some researches were superfluous which reflected in the increase of statistical tables that have not attained the objective of these researches, in addition to mentioning and explaining some statistical laws and using them incorrectly by most researchers. It appears also that most statistical methods used in public relations researches were the arithmetic mean, standard deviation,

Materiality Concept, Chi square test, the T test, and Pearson correlation coefficient

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Publication Date
Mon Mar 02 2026
Journal Name
International Journal Of Inventions In Engineering & Science Technology
A Review: Campus Violence Detection Using Deep Learning Models
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This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

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