Significance of Chi square test
The Chi-square test is a statistical method used across various disciplines including Ayurveda, Science, Psychiatry, Health Sciences, and Environmental Sciences. It analyzes categorical data to determine if there is a significant association between variables. It compares observed and expected frequencies to assess relationships, differences between groups, and the significance of study results. This test helps researchers identify meaningful correlations and dependencies within datasets, providing valuable insights across diverse fields of study.
Synonyms: Chi-squared test, Chi-square analysis, Statistical test
The below excerpts are indicatory and do represent direct quotations or translations. It is your responsibility to fact check each reference.
Hindu concept of 'Chi square test'
In Hinduism context, the Chi-square test is an inferential statistical tool used to analyze data, find associations between categorical variables, and assess the significance of research results.
From: Journal of Ayurveda and Integrated Medical Sciences
(1) The Chi square test was one of the statistical tools employed to compare the values obtained before and after treatment in order to ascertain the significance and effectiveness of the applied therapies.[1] (2) It is a statistical method used to examine the relationship between categorical variables, determining if there is a significant association between them.[2] (3) It is a type of inferential testing.[3] (4) A statistical method used to analyze the association between central obesity and night duty workers, and the tests provide values that indicate the significance of the association between variables.[4] (5) This is one of the inferential statistical tests used to analyze the results of the study, which helps to determine the significance of differences observed in the study.[5]
From: Journal of Ayurvedic and Herbal Medicine
(1) The Chi-square test is a statistical test used for intergroup comparison of Plaque Index, Gingival Index and Sulcus Bleeding Index.[6] (2) This test was used for Gingival bleeding index (GBI), as it was measured in percentage, as indicated in the text about the study.[7] (3) This is a statistical test used to compare categorical variables, such as symptoms, to assess the association between different groups and outcomes in the study.[8] (4) This is a statistical test used to analyze the overall effect of therapy, comparing the outcomes between the two groups and determining the significance of the results.[9]
The concept of Chi square test in scientific sources
The Chi-square test, according to the text, is a statistical method used to analyze relationships and differences between categorical variables. It determines if associations are statistically significant.
From: International Journal of Environmental Research and Public Health (MDPI)
(1) A statistical procedure employed to determine if there were significant relationships or associations between demographic variables, specifically age and sex, and the occurrence rates of the most frequently identified injuries.[10] (2) Chi-square tests were performed alongside the t-tests to examine the relationship between the derived cluster groupings and other relevant classification data collected during the comprehensive study.[11] (3) The Chi-square test was one of the statistical tools used to analyze the collected data, specifically employed to identify significant categorical differences between various variables related to self-medication.[12] (4) A statistical procedure employed before hypothesis testing in order to effectively control for any distribution differences that might exist among the variables within each distinct group being examined in the research.[13] (5) A statistical method used to compare the observed ratios of individuals categorized as either displeased or highly displeased across different groupings based on sound exposure and personal characteristics.[14]
From: Sustainability Journal (MDPI)
(1) A statistical procedure applied to cross-tabulation results to determine whether a significant association exists between categorical variables, such as age bracket and agreement with sending evaluations.[15] (2) A Chi-square test was utilized to determine if the observed difference in the number of respondents from the private versus the public sector could statistically affect the overall results of the investigation.[16] (3) The chi-square test was utilized to analyze the influence of organization size on Green Human Resource Management practices adopted by the organization, examining differences among various groups.[17] (4) Chi-Square Tests, specifically those involving only one degree of freedom, were the subject of extensions to the Mantel-Haenszel Procedure detailed in a statistical paper from 1963.[18] (5) This statistical measure is employed to confirm the significance of the groupings by assessing whether the observed co-occurrence patterns of words within the text segments are unlikely to have occurred by chance.[19]
From: The Malaysian Journal of Medical Sciences
(1) A statistical method used specifically for the purpose of analyzing categorical variables within a dataset to determine independence or association between them.[20] (2) This is a statistical test used to compare categorical variables, and it was used to analyze the data.[21] (3) This is the statistical method used to test the differences between groups, helping to identify significant variations in the study's findings.[22] (4) Chi-square test is a statistical method used to analyze the differences in proportions, and it was used to analyze the data in the study.[23] (5) This test was used to assess the associations between the subjects' age, workstation and work experience and their hearing loss, with the results deemed significant if the P-values were less than 0.05.[24]
From: International Journal of Pharmacology
(1) This test was used to analyze differences of the occurrence of bloody diarrhea.[25] (2) This was utilized in the study for correlation analysis, and was recorded in the sample population following various antiviral therapies.[26] (3) A statistical test used for inter-group comparison of counting data. Enumeration data were presented in the form of cases (percentage) and the chi-square test was used.[27] (4) Statistical methods employed to scrutinize the factors influencing the occurrence of the disease, helping to identify potential causes.[28] (5) This is a statistical test adopted to assess the association of various analyzed factors with the mother's experience of early childhood mortality.[29]
From: Journal of Public Health in Africa
(1) Comparisons between categorical variables, such as sex and age groups, were performed using the Chi-square test to determine associations with different characteristics within the sample.[30] (2) A statistical test employed to analyze the relationships between categorical variables, determining if there is a significant association between them.[31] (3) is a statistical method used to determine the association between the number or proportion of HIV positive individuals on SDI for ART and the facility, as well as the characteristics of the facilities.[32] (4) The Chi-Square test was used to analyze the relationship between various factors and rat eradication behavior, revealing significant associations in leptospirosis endemic areas.[33] (5) Statistical method used to analyze the risk factors of latent TB infection in the study.[34]
From: Asian Journal of Pharmaceutics
(1) Statistical tests used to compare categorical variables.[35] (2) A statistical method used to find a significant association between perceptions, barriers, attitude, and participant characteristics.[36] (3) It is a statistical test used to examine the association between categorical variables.[37] (4) A test used to examine the relationship between qualitative variables and OSA disease.[38] (5) A statistical test that was used to compare categorical variables in the study.[39]
From: African Journal of Primary Health Care and Family Medicine
(1) A statistical procedure employed to determine if there is a significant association or relationship between categorical variables, such as the method of delivery and the satisfaction level reported concerning pain management during labor.[40] (2) A statistical method used to determine if there is a significant association between two categorical variables, such as age and the proportion of underweight children.[41] (3) This refers to the statistical method used to compare differences between groups. It was used to determine p-values.[42] (4) A statistical test used to determine the association between variables, with a significance level.[43] (5) Percentages were compared using this during the analysis of the collected data.[44]
From: South African Family Practice
(1) A chi-square test was used to determine the statistical significance of associations between variables related to blood and body fluid exposures.[45] (2) It is a statistical method used in the analysis of data to assess associations between categorical variables, with a p-value less than 0.05 being deemed statistically significant.[46] (3) This statistical test was used to determine the association between blood pressure control and the various independent variables, assessing the significance of the relationships.[47] (4) This is a statistical test used to determine if there is a significant association between two categorical variables.[48] (5) This is a statistical test used to determine whether a significant relationship exists between burnout and the participants' demographics.[49]
From: Onderstepoort Journal of Veterinary Research
(1) This test was used to determine the association between the infection and the risk factors such as age, body condition score, and sex.[50] (2) The Chi-square test was used to ascertain associations between positive cases and sex and species of the animals, providing statistical analysis.[51] (3) A statistical method used to analyze the data, which revealed significant differences between districts in the number of positive samples, related to heartwater infection.[52] (4) This statistical test was used to determine if there was a significant difference in the prevalence of infection between the three areas of Tshwane (Pretoria) Metropole.[53] (5) A statistical test used to compare the proportion of dip-tanks or animals that were positive for each of the four tick species on goats and cattle.[54]
From: South African Journal of Physiotherapy
(1) It was used to explore the association between the National Benchmark Test proficiency bands and the first-year Grade Point Average, categorised into bands.[55] (2) It was used to test differences in fibre distribution contingency tables.[56] (3) Chi square tests were used within the inferential statistics to determine associations between categorical variables, such as race and success, in the study's analysis of predictors.[57] (4) These were employed to analyze the relationships between categories, helping to understand the associations within the data collected during the study.[58] (5) This is a statistical test used to compare the experimental and control groups, with the aim of determining the effectiveness of a home treatment program by examining readmission rates.[59]
From: South African Journal of HIV Medicine
(1) The Chi-square test was one of the statistical methods used to summarise categorical data, specifically to determine if genotyped SNPs were in Hardy-Weinberg equilibrium across the study cohort.[60] (2) Chi-square tests were used in the study to analyze the categorical data, to assess the relationship between two or more categorical variables.[61] (3) This is a statistical test used to compare categorical variables, used in the study to compare women with and without detectable cervical HIV, alongside Fisher’s exact test.[62] (4) The Chi-square test is a statistical method used to assess the significance of associations between variables, like retention in care and other factors, to analyze data.[63] (5) Statistical tests used to analyze categorical variables, which were employed to compare the differences between individuals who use drugs and those who do not.[64]
From: International Journal of Pharmacology
(1) Statistical tests used to assess heterogeneity among studies in a meta-analysis.[65] (2) The Chi-square test is a statistical method used to determine if observed allele distributions deviate from Hardy Weinberg equilibrium.[66] (3) A statistical test used to analyze categorical data, applied here to the antidiarrheal assay.[67] (4) A statistical test used to analyze categorical data, such as count data and percentages, to determine if there is a significant association between variables.[68] (5) The Chi-square test is a statistical tool employed to analyze categorical data and determine significant associations between variables.[69]
From: South African Journal of Psychiatry
(1) The chi-square test was used for associations during the statistical analysis, helping to determine the significance of relationships between variables.[70] (2) This is a statistical test used to analyze categorical data, and it was used to compare variables within gender categories.[71] (3) Pearson’s chi-square test was used to compare the difference of depressive features between the elderly with different characteristics, with significant variables assessed by this test.[72] (4) These were statistical tests used to determine the significant differences between various variables and correlates within the study's data analysis.[73] (5) This is a statistical test used to determine if there is a significant difference between the observed and expected values, and it was used to compare the prevalence of isolated sleep paralysis among different groups in a study.[74]
From: Religions Journal (MDPI)
(1) The Chi-square (χ²) test was the statistical tool used to estimate significant departures from expected distributions when analyzing categorical data, such as comparing religious affiliation frequencies between the survey sample and the general Spanish society.[75] (2) Chi-square test is a statistical test used to determine if there is a significant association between categorical variables, such as comparing norm values between different regions.[76] (3) This test determines if there is a significant difference between observed and expected frequencies in one or more categories. Commonly used for categorical variables, it is suitable for research involving opinion polls or market studies.[77]