The authors of the educative academic article considered the binary logistic regression to establish the relationships between the dependent and independent variables for a better understanding of the complex nature of Hepatitis disease. Regression analysis, like all reversion analyses, is a binary classification. Logistic regression is often used for describing and explaining the correlation between each binary variable reliant and one or more individual variables named ordinary, interval, or ratio-level. For instance, the enlightened stakeholders took advantage of the program to assess the association between several variables to give a detailed understanding of the topic. Specifically, the objective of the study was to increase the predictive ability and to decrease the incidence of covariates (Abdulqader, 2017). The method depended on the step-by-step manner and the greatest regression by implementing data from health surveys.
The test was the most appropriate choice with the argument that the findings of the study are not only reliable but also valid. According to business specialists, the test needed to measure what it was intended to do. Validity is often assessed by examining how the measurements match certain criteria. To evaluate the validity of every test, the acceptable criterion measures must be carefully chosen, and sensible people may argue about the most appropriate criteria measure. Furthermore, only valid tests can provide useful information on individuals, but authenticity adjustment correlations have never been so high as reliability. On the other hand, reliability tests should produce the same results even if separate testers manage them, different test scores are given in different ways, and the same individual takes the test on two or more different occasions. Confidence is usually verified by comparing various sets of scores (Abdulqader, 2017). Specifically, for the classification of people into two categories, infected and not infected by hepatitis virus, this technique was used.
The authors used both tables and figures to present their data. Both figures and tables have been used to elucidate findings or notions, but they are intended to show significant differences. Tables present statistics or sum up or define ideas, definitions, or other descriptions on an assessment for comparative analysis with other stats (Abdulqader, 2017). The results of their studies are often reported through tables and figures by scientists and researchers. The tables must not duplicate the data presented in the figure. Apart from the independence of the visual presentations, the information presented will aid in the understanding of the concepts associated with Hepatitis, including the other related health conditions. Thus, it is evident that the enlightened researchers considered multiple presentation techniques to make it easier for the readers to comprehend the information effectively.
The ability of the readers to interpret the study by assessing the results tables makes them independent. Before they navigate through the text, readers often look at tables and figures. Each figure and table should therefore be independent, comprehensive, and informative. These findings add to the existing numerical insights into multiple regression that resulted in this argument. The article presents techniques that can appropriately be included in the regression analysis throughout the calculation of effect sizes. The results also show how the structure of exchangeability between the predictor variables can be achieved (Abdulqader, 2017). This article will therefore be very resourceful for interested experts in the fields of statistics. Thus, although each table gives unique information about the comprehensive idea, the presentation model used by the authors makes it stand alone and significant for the target audiences and the scholars.
Reference
Abdulqader, Q. M. (2017). Applying the binary logistic regression analysis on the medical data. Science Journal of University of Zakho, 5(4), 330-334.