Basic statistical tools in research and data analysis

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data. The results and inferences are precise only if proper statistical tests are used. This article will try to acquaint the reader with the basic research tools that are utilised while conducting various studies. The article covers a brief outline of the variables, an understanding of quantitative and qualitative variables and the measures of central tendency. An idea of the sample size estimation, power analysis and the statistical errors is given. Finally, there is a summary of parametric and non-parametric tests used for data analysis.

Related collections

Most cited references 13

Record: found
Abstract: found
Article: not found

Early exposure to anesthesia and learning disabilities in a population-based birth cohort.

Robert Wilder, Randall P. Flick, Juraj Sprung … (2009)

Anesthetic drugs administered to immature animals may cause neurohistopathologic changes and alterations in behavior. The authors studied association between anesthetic exposure before age 4 yr and the development of reading, written language, and math learning disabilities (LD). This was a population-based, retrospective birth cohort study. The educational and medical records of all children born to mothers residing in five townships of Olmsted County, Minnesota, from 1976 to 1982 and who remained in the community at 5 yr of age were reviewed to identify children with LD. Cox proportional hazards regression was used to calculate hazard ratios for anesthetic exposure as a predictor of LD, adjusting for gestational age at birth, sex, and birth weight. Of the 5,357 children in this cohort, 593 received general anesthesia before age 4 yr. Compared with those not receiving anesthesia (n = 4,764), a single exposure to anesthesia (n = 449) was not associated with an increased risk of LD (hazard ratio = 1.0; 95% confidence interval, 0.79-1.27). However, children receiving two anesthetics (n = 100) or three or more anesthetics (n = 44) were at increased risk for LD (hazard ratio = 1.59; 95% confidence interval, 1.06-2.37, and hazard ratio = 2.60; 95% confidence interval, 1.60-4.24, respectively). The risk for LD increased with longer cumulative duration of anesthesia exposure (expressed as a continuous variable) (P = 0.016). Exposure to anesthesia was a significant risk factor for the later development of LD in children receiving multiple, but not single anesthetics. These data cannot reveal whether anesthesia itself may contribute to LD or whether the need for anesthesia is a marker for other unidentified factors that contribute to LD.

0 comments Cited 292 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Null hypothesis significance testing: a review of an old and continuing controversy.

Raymond Nickerson (2000)

Null hypothesis significance testing (NHST) is arguably the most widely used approach to hypothesis evaluation among behavioral and social scientists. It is also very controversial. A major concern expressed by critics is that such testing is misunderstood by many of those who use it. Several other objections to its use have also been raised. In this article the author reviews and comments on the claimed misunderstandings as well as on other criticisms of the approach, and he notes arguments that have been advanced in support of NHST. Alternatives and supplements to NHST are considered, as are several related recommendations regarding the interpretation of experimental data. The concluding opinion is that NHST is easily misunderstood and misused but that when applied with good judgment it can be an effective aid to the interpretation of experimental data.

0 comments Cited 220 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Nonparametric statistical tests for the continuous data: the basic concept and the practical use

Francis Nahm (2016)

Conventional statistical tests are usually called parametric tests. Parametric tests are used more frequently than nonparametric tests in many medical articles, because most of the medical researchers are familiar with and the statistical software packages strongly support parametric tests. Parametric tests require important assumption; assumption of normality which means that distribution of sample means is normally distributed. However, parametric test can be misleading when this assumption is not satisfied. In this circumstance, nonparametric tests are the alternative methods available, because they do not required the normality assumption. Nonparametric tests are the statistical methods based on signs and ranks. In this article, we will discuss about the basic concepts and practical use of nonparametric tests for the guide to the proper use.

0 comments Cited 75 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): Indian J Anaesth

Journal ID (iso-abbrev): Indian J Anaesth

Journal ID (publisher-id): IJA

Title: Indian Journal of Anaesthesia

Publisher: Medknow Publications & Media Pvt Ltd (India )

ISSN (Print): 0019-5049

ISSN (Electronic): 0976-2817

Publication date (Print): September 2016

Volume: 60

Issue: 9

Pages: 662-669

Affiliations

[1]Department of Anaesthesiology, Division of Neuroanaesthesiology, Sheri Kashmir Institute of Medical Sciences, Soura, Srinagar, Jammu and Kashmir, India

[1 ]Department of Anaesthesiology and Critical Care, Vijayanagar Institute of Medical Sciences, Bellary, Karnataka, India

Author notes

Address for correspondence: Dr. Zulfiqar Ali, Department of Anaesthesiology and Critical Care, Sheri Kashmir Institute of Medical Sciences, Soura, Jammu and Kashmir, Srinagar, India. E-mail: zulfiqaraliiii@ 123456yahoo.com

Article

Publisher ID: IJA-60-662

DOI: 10.4103/0019-5049.190623

PMC ID: 5037948

PubMed ID: 27729694

SO-VID: 3667ae14-d33d-44ac-9a40-18c2bc86719e

License:

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

Basic statistical tools in research and data analysis

Read this article at

Abstract

Related collections

Core Readings in Statistical Mediation Analysis

Most cited references 13

Early exposure to anesthesia and learning disabilities in a population-based birth cohort.

Null hypothesis significance testing: a review of an old and continuing controversy.

Nonparametric statistical tests for the continuous data: the basic concept and the practical use

Author and article information

Journal

Affiliations

Author notes

Article

History

Categories

Comments

Comment on this article

Similar content 313

Cited by 44

Most referenced authors 71