Descriptive Statistics and Normality Tests for Statistical Data
By Prabhaker Mishra, C. Pandey, Uttam Singh, Anshul Gupta, Chinmoy Sahu, A. Keshri. Annals of Cardiac Anaesthesia, 2019
2,092 citations recorded by the source corpus.
Descriptive statistics are an important part of biomedical research which is used to describe the basic features of the data in the study. They provide simple summaries about the sample and the measures. Measures of the central tendency and dispersion are used to describe the quantitative data. For the continuous data, test of the normality is an important step for deciding the measures of central tendency and statistical methods for data analysis. When our data follow normal distribution, parametric tests otherwise nonparametric methods are used to compare the groups. There are different methods used to test the normality of data, including numerical and visual methods, and each method has its own advantages and disadvantages. In the present study, we have discussed the summary measures and methods used to test the normality of the data.
Subfields: Computational Mechanics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/5938066fbac05a3c5ec25bd0d756797d9a0c742a
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Citations in the corpus
- Application of Student's t-test, Analysis of Variance, and Covariance (2019, methodology): “All above methods are parametric method.[2] When the size of the sample is small, mean is very much affected by the outliers, so it is necessary to keep sufficient sample size while using these methods.”
- Drivers of food waste reduction behaviour in the household context (2021, background): “Results regarding normality showed that the Skewness and Kurtosis values were within the expected range of ± 3, indicating that there were no normality issues (Mishra et al., 2019).”