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Year : 2005  |  Volume : 8  |  Issue : 2  |  Page : 12-14
Vital Statistics


Meenakshi Ammal Dental College and Hospital, Chennai, India

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   Abstract 

The term "statistics" has always been associated with studies relating to facts and figures and has been defined as a discipline concerned with the treatment of numerical data. The purpose of this article is to emphasize the importance of statistics in collection, presentation, analysis and interpretation of comparative data, as any research outcome depends to a large extent on the analysis of the comparative values obtained. This paper outlines the steps involved in a statistical study, namely­ selection of sample size, selection of type of test to be employed and analysis of results in a simplified manner

How to cite this article:
Gupta T, Ballal S, Bharaadwaj N, Kandaswamy. Vital Statistics. J Conserv Dent 2005;8:12-4

How to cite this URL:
Gupta T, Ballal S, Bharaadwaj N, Kandaswamy. Vital Statistics. J Conserv Dent [serial online] 2005 [cited 2020 Nov 1];8:12-4. Available from: https://www.jcd.org.in/text.asp?2005/8/2/12/42599

   Introduction Top


The final outcome of an experiment or research depends to a large extent on the analysis of comparative values obtained. To the dictum of Helmholtz [8] that "All science is measurement", one can also add Sir Henry Dale's clause that, "All true measurement is essentially comparative". Statistics plays an integral role in collection, presentation, analysis and interpretation of comparative data. In a broad sense, the term "statistics" has always been associated with studies related to facts and figures e.g. health statistics, business statistics etc. In the book "Statistical methods in medical research" statistics has been defined as a discipline concerned with the treatment of numerical data derived from groups of individuals or materials [8].

STEPS IN STATISTICAL STUDY

The chronology of steps involved in a statistical study are as follows:

SELECTION OF SAMPLE SIZE

Often, the primary problem encountered by a student of research is the number of samples or sample size to be selected.

Crieteria for selection of sample size are as below:

  • A sample size of 25-30 in each group is adequate if there is one variable or one parameter in the study.


  • In invivo studies where there is less availability of samples, a slight decrease in sample size may be acceptable.


  • LARGER SAMPLE SIZE WILL BE NEEDED IF:

    • Larger variation is expected
    • Rare characteristic is present
    • More variables are present
    • More precision required
    • More reliability required




SELECTION OF TEST

The tests employed to complete a study can be classified as:

A. For comparison of mean (average of observations) of different samples.

B. For comparison of proportion (percentage) of different samples.

C. Correlation tests

D. Regression tests.


A. For comparison of mean (average of observations) of different samples

Two types of tests are available, namely parametric and non-parametric

Parametric tests

  • Employed if the distribution of the population from which the samples are drawn is known'. (i.e. normally distributed with less variation).
  • In the computation of parametric tests the arithmetic processes of addition, division and multiplication are used [6] .
  • Used if adequate sample size is present [6] .


(i) Independent t-test

Employed to compare mean of two groups using one variable [2] . Eg Comparison of bond strength of amalgam and composite.

(ii) Paired t-test

Used for within group comparisons

at different time intervals [1] . Eg. Number of microbes in root canal before and after antibiotic therapy.

(iii) ANOVA (Analysis of variance)

Mean of any number of groups using one variable is determined by this test [5] . Eg. Sealing capacity of different endodontic sealers.

Non parametric tests

Employed if distribution is unknown [6] .(large variation present)

Data are changed from measurements or scores to ranks or even to signs [6] .

Used if adequate sample size is not present [6] .

(i) Mann Whitney U test

It is equivalent to independent t-test [3] .

(ii) Wiloxan sign rank test It is equivalent to paired t-test.

(iii) Kruskal Wallis H-test

It is equivalent to ANOVA.

B. For comparison of proportion (percentage) of different samples

The test employed are as follows:

(i) Chi-square test

It checks the proportion between any number of groups using one variable [7] . It is used if adequate sample size is available.

Eg. The effect of ampicillin, sulphonamides and tetracycline in a certain percentage of people.

(ii) Fisher's test

This test is. similar to Chi-square test if less sample size is available.

(iii) Mc-Nemar test

It compares proportion of one variable within a group at different time intervals.

Eg. Proportion of people having sensitivity before and after using desensitizing paste.

C. Correlation tests

It is used to find if two variables co-vary with each other or are independent.

Eg. The susceptibility rate of organisms in root canal following increase in antibiotic dosage.

D. Regression tests

It describes the dependence of one variable on another independent variable.

E L -. Effect of bonding agent on strength of composite.

ANALYSIS OF RESULT

  • Non-parametric tests like Mann Whitney U­ test, Wiloxan sign rank test, Kruskal Wallis H­ test are less sensitive than parametric tests like Independent t-test, ANOVA as they use random ranking instead of original values.
  • Probability (p) value indicates level of significance (sensitivity) of a test [4] .


p < 0.001-> highly significant

The probability that the difference between two groups occurring by chance is less than I in 1000.

p< 0.01 -> Moderately significant

The probability of the difference occurring by chance is less than 1 in 100.

p < 0.05-> Less significant

The probability of the difference occurring by chance is less than 5 in 100.

p> 0.05-> Not significant

The probability of difference occurring by chance is very high.


   Conclusion Top


This paper attempts at explaining importance of statistics as an essential protocol for any research program. Statistics is the greatest leveler. It covers up for all the variations that can creep into the results thereby providing a foolproof system for proper interpretation of data. Hence it would be appropriate to term it as "The Vital Statistics".

 
   References Top

1.Douglas G. Altman : Practical statistics for medical research, 3 rd Edition, Chapman and Hall, 1991 : 191.  Back to cited text no. 1    
2.Leslie E. Dale, Geoffrey J.Bourke : Interpretation and Uses of Medical Statistics, 5 th Edition, Blackwell Science Limited, 2000:207.  Back to cited text no. 2    
3.Martin Bland : An Introduction to Medical Statistics, 3 rd Edition, Oxford University Press. 2000: 211.  Back to cited text no. 3    
4.Michael J. Campbell, David Machin : Medical Statistics - A Commonsense Approach, 3 rd Edition, John Wiley and Sons Limited, 1999 81-82.  Back to cited text no. 4    
5.P. Armitage, G. Berry : Statistical Methods in Medical Research, 2 nd Edition, Blackwell Scientific Publication, 1987 : 187.  Back to cited text no. 5    
6.P.S.S. Sundar Rao, J.Richard : An introduction to Biostatistics. 3 rd Edition, Prentice Hall of India Private Limited. 2003 : 107-109.  Back to cited text no. 6    
7.RA Brown, J Swanson Beck : Medical Statistics on Personal Computers, 2 nd Edition, BMJ Publishing Group, 1994 : 72-73.  Back to cited text no. 7    
8.Sir Austin Bradford Hill : A Short Textbook of Medical Statistics, 10 th Edition, ELBS and Hodder and Stoughton, 1977 : 2-8.  Back to cited text no. 8    

Top
Correspondence Address:
Tina Gupta
Meenakshi Ammal Dental College and Hospital, Chennai
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0972-0707.42599

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