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Statistical Methods for Reproducible Data Analysis
Published in Asis Kumar Tripathy, Chiranji Lal Chowdhary, Mahasweta Sarkar, Sanjaya Kumar Panda, Cognitive Computing Using Green Technologies, 2021
Sambit Kumar Mishra, Mehul Pradhan, Rani Aiswarya Pattnaik
For categorical variable:Count – Absolute frequency of each category in a categorical variable.Count % – Proportion of different categories in a categorical variable expressed in %.Bivariate analysis: Analysis of the relationship between two variables. This includes the phenomenon when two variables are studied together for their empirical relationship.
Applied Statistics
Published in Vinayak Bairagi, Mousami V. Munot, Research Methodology, 2019
Varsha K. Harpale, Vinayak K. Bairagi
The method of estimating relation or correlation or measure of association between two variables is a bivariate analysis. Normally this correlation ranges between –1 and 1, this negative or positive relationship between the variables states direction of correlation. If the correlation of variable is more away from 0 or more toward –1 and 1 then it represents more perfect the relationship between the independent and dependent variations is called degree or extent of correlation. Measures of association and statistical significance that are used may vary as per the level of measurement of the variables analyzed [5].
Racial and ethnic differences in patients involved in alcohol-impaired motor vehicle crashes and its related clinical outcomes among various age groups in the U.S.
Published in Traffic Injury Prevention, 2020
Ryan Randle, Shahrzad Bazargan-Hejazi, Deyu Pen, Sara Diab, Magda Shaheen
We used descriptive statistics to describe and test the distribution of the variables. Categorical variables are reported as number and percent. Continuous variables are reported as mean, standard deviation, median, and interquartile range. Bivariate analysis for categorical variables was obtained using the chi-square test. Bivariate analysis for the continuous variables was obtained using non-parametric median test. We used multiple logistic regression analysis to test the independent relationship between alcohol-impaired driving and race/ethnicity for each age group.
Managing the organic municipal waste in Palestine: Linking policy, practice, and stakeholders’ attitude toward composting
Published in Journal of the Air & Waste Management Association, 2023
Majed Ibrahim Al-Sari’, A. K. Haritash
The bivariate analysis is used to assess the relationship between two variables, and examine the effect of each influencing factor independently. The findings of the bivariate analysis are presented in Tables 1–3. The analysis of the results of these factors is described as follows.
Lower back pain and its association with whole-body vibration and manual materials handling among commercial drivers in Sabah
Published in International Journal of Occupational Safety and Ergonomics, 2019
Khamisah Awang Lukman, Mohammad Saffree Jeffree, Krishna Gopal Rampal
Data were analysed using SPSS version 13.0. Both descriptive and inferential statistical methods were used. Univariate analysis, bivariate analysis (χ2) and multivariate analysis (multiple logistic regressions) were carried out. The forward stepwise method was used in the multiple logistic regressions; p < 0.05 is considered significant.