| SPECIAL ARTICLE |
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| Year : 2019 | Volume
: 2
| Issue : 3 | Page : 120-125 |
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Descriptive statistics: Measures of central tendency, dispersion, correlation and regression
Zulfiqar Ali1, S Bala Bhaskar2, K Sudheesh3
1 Department of Anaesthesiology, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, Jammu and Kashmir, India
2 Department of Anaesthesiology, Vijayanagar Institute of Medical Sciences, Ballari, Karnataka, India
3 Department of Anaesthesiology, Bangalore Medical College and Research Institute, Bengaluru, Karnataka, India
Correspondence Address:
Prof. S Bala Bhaskar
Vijayanagar Institute of Medical Sciences, Ballari, Karnataka
India
 Source of Support: None, Conflict of Interest: None  | 1 |
DOI: 10.4103/ARWY.ARWY_37_19
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Large data obtained from research are subjected to statistical analysis so that outcomes can be extrapolated to the larger population. Towards this end, such large data have to be consolidated into smaller, simpler expressions of measures, representing the outcomes of the whole sample. These form the descriptive statistics, which will later on help in inferential statistics, involving the different variables within one group and more than one group. Their distribution features are analysed and are described as sums, averages, relationships and differences. These measures are classified as those of central location and those of dispersion. Mean, Median and Mode are the three main measures of central tendency and Range. Percentile, variance, standard deviation, standard error and confidence interval are measures of dispersion. Correlation and regression can be used to describe the relationship between two numerical variables. Correlation is a measure of association and regression is used for prediction. Regression analysis helps to assess 'influential' relationships between the data. Changes among one or more variables might affect other variables.
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