Role of statistical skills in communication

M S Sridhar Page 1

Role of Statistical Skills in Communication@

M S Sridhar*

However great may be one’s work, it does not matter to others until it is communicated. In other

words it is not just sufficient to do a great job; one has to ‘sell’ it to others. As everyone is busy

with his/ her own work, only well presented works attract others and make them to keep aside

their own work and give attention to others works. Most people as a routine browse enormous

quantity of written communications, but have time and interest to read only a limited number of

them. For a potential reader to be attracted and retained it is not enough to be simple, clear,

unambiguous in the language used, it must also have suitable, attractive and catchy punch

statements. Successful writers and speakers use catchy and power-packed statistical statements

embedded in their talks and writings. Such punch with suitable articulation is even more required

in oral presentations. The following extracts from live examples illustrate the point more vividly.

America employs 70% of the world’s Nobel prize winners

In 1900, 80% of the world’s Christians lived in Europe and the United States; today 60% live

in developed world

One billion people in the developed countries contribute over half of carbon dioxide emission

where as the other half is by five billion people in the rest of the world

In 1970, America granted over half of the worlds Ph Ds in science and engineering, but by

2010, the share will be just 15%

Nokia 6680 mobile require 13 clicks to change ring tone

Average owner of mobile hand set spends 471 minutes per month and sends 39 text messages

per month

By the time a child becomes 18 years , it would have heard ‘NO’ about 1.5 lakh times (85 -

95%) and most of the rest are ‘neutral’ with a few hundred times ‘YES’

Interestingly, all the above quotes provide statistical information in brief and in textual form (not

in the form of a table or chart). Yet they are not too simple statistics, but a set of carefully

thought out articulation through statistical summaries. Taken in their context, they have highly

impressive, persuasive and dramatizing effect on readers and listeners. They have rich statistics

without jargons or complex formula and hence appeal easily to non-specialists and laymen. We

may recall Einstein’s statement that if a new theory was not based on a physical image simple

enough for a child to understand, it was probably worthless.

Among the 3Rs (Reading, wRiting and aRithmetic), it is the third R that is most feared and least

emphasized in literacy programmes and formal education. By and large, the need for knowledge

Role of statistical skills in communication

M S Sridhar Page 2

of basic statistics assumed much less importance than desired in our educational programmes.

Even in higher education and on the job trainings, the communication skills imparted concentrate

on reading, notes taking, writing, speaking, and listening skills, but not on statistical skills.

Examining six top ranked presentations on ‘communication skills’ and on ‘technical writing’

revealed that only passing mention like ‘check numerical figures’, ‘cite sources of statistical

data’ and ‘ no sentence should begin with numerals’ are made in these presentations.

The knowledge of basic statistics is required not only to communicate effectively, but even to

understand others communication. When a result of research is communicated to common man,

despite avoiding jargons, some elementary ones have to be retained. During school days, many

develop aversion to arithmetic and related subjects like mathematics and statistics. Some

consider them as tough subjects and avoid them and choose social, behavioral and humanities

subjects for further studies, if options are available at later stage. We might wrongly think that

the scope for this third R ends by the time we reach higher learning. On the contrary, the need for

mathematical and statistical skills become critical in the higher learning of even medical,

agricultural, social and behavioural sciences once they start working on practical projects and

research. Researcher cannot ignore science of statistics. It is an essential tool for designing

research, processing & analysing data and drawing inferences. Statistics is an all-pervasive tool-

subject and it is hardly possible to escape from knowing basic statistics in any career. For that

matter it is required in our day-to-day life.

It is necessary to know what statistics can and cannot do to appreciate more fully the role of

statistics as a tool. It offers a logical and systematic procedure for processing data expressed in

numerical values. Goal of statistical analysis is to draw conclusions and understand more about

sources of data. Three major roles of statistics are data reduction, drawing inference and

identification of relationships. Some ways statistics can help includes finding central point

around which the data revolves, how broadly the data is spread, showing relationship between

variables and provide certain techniques to test the degree to which the data conform or depart

from chance or anticipated standard.

In nutshell, what statistics does are as follows.

1. It enables presenting facts in a precise definite form that helps proper comprehension of what

is stated. Exact facts are more convincing than vague statements.

2. It helps condensing the mass of data into a few numerical measures, i.e., summarises data

and presents meaningful overall information about a mass of data.

3. It helps in finding relationship between different factors in testing the validity of assumed

relationship.

4. It helps in predicting the changes in one factor due to the changes in another factor.

5. It helps in formulation of plans and policies which require the knowledge of further trends;

Statistics plays vital role in decision making

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An understanding of basic statistical skills including types of statistical data, variables, different

types of presentation of data, probability distributions including normal distribution, types of

errors and calculation of possible error, precision and reliability of predictions, finding

correlation and its direction and magnitude, measures of central tendency, measures of dispersal

or variation, differences between populations' samples, parameters, and statistics are necessary.

Statistics is also called a double-edged tool, as it can be abused and misused. It can be abused

with poor data coupled with sophisticated statistical techniques to obtain unreliable results and it

can be misused when honest, hard facts are combined with poor/ inappropriate statistical

techniques to create false impressions and conclusions. It is often said that any data coerced with

statistical techniques will surrender.

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SRELS Journal of Information Management, April 2011, v. 48 (2)

* Former Head, Library and Documentation, ISRO Satellite Centre, Bangalore 560017.