Here is a term paper on ‘Statistics’ for class 9, 10, 11 and 12. Find paragraphs, long and short term papers on ‘Statistics’ especially written for school and college students.
Term Paper # 1. Meaning of Statistics:
Statistics, a branch of applied Mathematics, is regarded as mathematics applied to observational data. Conceivably everything dealing with the collection, processing, analysis and interpretation of numerical data belongs to the domain of statistics.
However, the term ‘statistics’ is used in several ways. It denotes a compilation of data such as those found in the labour Gazzette or say, Labour Statistics of the Labour Bureau published annually by the Government of India.
The second meaning of the term statistics refers to the statistical principles and methods employed in the collection, processing, analysis and interpretation of any kind of data. In this sense, it is a branch of applied mathematics and helps us to know the complex social phenomena in a better way and lends precision to our ideas.
Term Paper # 2. Functions of Statistics:
Statistics has patently two broad functions. The first of these functions is description and the summarizing of information in a manner so as to make it more usable. The second function of statistics is induction, which involves either making generalizations about some ‘population’ on the basis of a sample drawn from this population or formulating general laws on the basis of repeated observations.
The two functions of statistical methods can be easily understood by the following example. Suppose it is desired to study the problem of labour unrest in a particular area.
The first thing to be done here will be to analyse the various causes of labour unrest and to study the impact of each one of these on the various categories of labour, viz., male workers and female workers or skilled labour and unskilled labour.
This kind of analysis will give us an insight into the problem and we may be able to know from such an analysis many important things, e.g., that the involvement of male workers in strikes is much higher than that of the female workers or that the labour unrest in big industries is much higher than in small industries.
Such an analysis may lead us to the conclusion regarding the incidence of labour unrest in the country and factors responsible for it. The former example illustrates the process of descriptive statistics whereas the latter, that of inductive statistics.
Term Paper # 3. The Place of Statistics in Social Research:
It is evident that knowledge of basic statistical concepts and techniques is necessary for an intelligent understanding of the generality of life. Out of the welter of single events, social researchers seek general trends; out of the vast and confusing variety of individual’ characters; they continually search for the underlying group characteristics.
There are essentially two reasons why the expertise in statistics and the need to study statistics have grown enormously in the field of social sciences. One reason is that the huge amount of data collected by researchers needs simplification so as to render them capable of being commonly understood without much difficulty.
The second and even more important reason is the increasing quantitative approach being currently employed in social science research.
Seemingly statistical considerations enter only at the analysis stage of the research process after the data have been collected, and near to the point in time when the initial plans for analysis are formulated and a sample is to be drawn.
But this does not imply that a social researcher can plan and carry out his entire research without any knowledge of statistics and then hand over the data to the statistician for analysis. If a researcher lacked conversance in statistics the results of a costly research project would probably be disappointing if not useless.
Indeed, the problems that will be encountered in analysis and interpretation have to be anticipated at every stage in the research process and in this sense, statistical methods are involved throughout. This implies that statistics is a very useful tool for the social scientist.
It is a much more useful tool for exploratory analyses than might possibly be imagined. Most social researches are based on highly tentative theoretical ideas.
The variables that need to be controlled in the analysis or even the priorities and sequence of analysis-steps that should be followed are neither precise nor predetermined, researchers are generally awed by the complexity of data analysis no sooner a set of variables is introduced.
In these circumstances especially, knowledge of the statistical methods becomes an invaluable tool for the social researcher in disentangling highly complex interrelationships.
Term Paper # 4. Limitations of Statistics:
Some of the major limitations of the statistical science and hence the attendant cautions that we need to be alerted about while using statistical techniques in the course of a research exercise are well worth noting.
One of the obvious limitations of statistics is that it is more specifically applicable to problems that are amenable to quantitative expression and treatment. Although qualitative attributes may sometimes be subjected to statistical analysis, these of necessity, have to be translated into quantitative indices by recourse to operational definitions.
But then, much would depend on the validity of the operational assumptions. Unfortunately, this is a pit many a researcher falls into, i.e., qualitative data are often operationalized as numerical values without a deeper concern for their validity, in which case, it is rather the poor data that stand to blame and not the statistical science.
In as much as many a problem of concern to social scientists is influenced greatly by subjective factors outside the ambit of mathematical treatment, the statistical approach hardly helps in affording us a rounded understanding of the problems.
It is understandable that the statistical laws are applicable to averages of aggregates. These pathetically ignore the individual intricacies of solitary units. Such a neglect may, in certain investigations, lead to merely superficial findings. The social-human sciences typically requisition a keen concern for the unique and the idiosyncratic aspects in society.
Additionally, there is a likelihood that statistics may be misused, so much so that the researcher may be tempted to twist them to suit his fond conclusions or hypotheses. This also applies equally to the very sensitive tools that the statistical methods afford. They are prone to be misused easily. Thus, great caution needs to be exercised while using them.
The validity of certain statistical methods depends on the nature of data, the levels of measurement, the knowledge of the pertinent aspects of the situations and lastly, the assumptions made vis-a-vis the sample from which the data are secured.
What is most important for us as potential users of statistical methods, therefore, is to bear well in mind that statistics has powerful muscles that can only serve but not direct. Much would depend on the use we want to put it to and whether the situation justifies it.
What is given out by statistical computations may not be the final ‘truth’ since it is basically an approximation of typicality and by nature probabilistic. It is left largely to our interpretative skills to bring out the real message underlying the statistical inferences and propositions.