Descriptive statistics and normality tests for statistical data

Abstract

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.

The effects of “Fangcang, Huoshenshan, and Leishenshan” hospitals and environmental factors on the mortality of COVID-19

“…where µ T and σ T were the arithmetic mean value and standard variance of sequence T. The data of each region was then divided into group A (from January 21 to February 5, before the use of MSHs) and group B (from February 6 to February 21, after the use of MSHs). Since the sample size was small (less than 50), the normality of the data was determined using Shapiro-Wilk test, and P value > 0.05 was considered as normally distributed (Mishra et al, 2019). If the data of the two groups were both normally distributed, Student's t -test would be performed to compare their difference, and if the data of at least one group had a skewed distribution, Mann-Whitney U test would be performed instead (Parab & Bhalerao, 2010).…”

The impact of social distancing policy on small and medium-sized enterprises (SMEs) in Indonesia

“…The data were analyzed using descriptive statistics with SPSS software. Descriptive statistics data describe the research sample summarized in numbers in a valid and meaningful way (Mishra et al, 2019;Thompson, 2009), and the information is presented in the simplest possible way (Mishra et al, 2019). This study focused on measures of central tendency using mean values.…”

Maternal and perinatal outcomes in pregnant women infected by SARS-CoV-2: A meta-analysis

“…Subsequently, 4 studies [21][22][23][24] were excluded, as 2 studies examined infants and children but not neonates [23,24], while another 2 did not report any perinatal outcomes of pregnancies infected by SARS-CoV-2 [21,22]. As a result, the present meta-analysis was based on 16 observational studies [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] and 44 case reports/series , including a total of 920 neonates born to women with SARS-CoV-2 infection.…”