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What is Social Statistics?
Social statistics is the use of statistics to study
human behaviour and social environments.
Social statistics data is information or knowledge
on an individual, object or event.
About statistics
Statistics are numbers, summaries of patterns and can also be probabilities. Statistical analysis can include the design and collection of data, its interpretation and presentation. Social statistics and quantitative data analysis are key tools for understanding society and social change. We can try to capture people’s attitudes and map patterns in behaviour and circumstances using numbers and also describe how people and populations change.
What is data?
Data can be numerical values or text, sounds or images, memories or perceptions. Often the concept of data suggests information that has been through some kind of processing and having a structure. However, many examples of new types of data have very different and often unstructured formats; for example, millions of tweets or thousands of PDFs of public documents. Huge quantities of data on people, organisations and social groups are collected each day, across the world. As social statisticians, it is our role to analyse and make sense of the huge volumes and sources of data using hypothesis-driven social research.
Understanding society
Social statistics are a means of investigating and testing research questions and policy impacts across different areas of people’s lives. These observations help our understanding of society, research questions include:
- How are populations growing?
- Are wealthy people happier?
- Is society becoming more tolerant of diversity?
- How do people cope with financial hardship?
- Do people with higher qualifications earn more?
- Does volunteering increase your sense of wellbeing? Social statistics are a means of investigating and testing research questions and policy impacts across different areas of people’s lives. Social statistics in the real world The United Nations Social Statistics Division analyses differences among social groups and countries covering such issues as housing, health, education, conditions of work and employment. It pays special attention to the study of conditions of special population groups, including children, the elderly, the unemployed, and people with disabilities. Compare the facts Social statistics are also used to compare data from before and after a policy intervention. For example, we need statistics to measure poverty in the first place and we then may want to assess the impact and costs of a policy providing financial support to families living in poverty. Patterns and relations Statistical analysis techniques can be used to explore patterns and underlying relationships in data sets, such as:
- in relation to people’s responses to multiple questions in a survey;
- to take account of aspects of people's circumstances such as the unemployment rates of where they live; or
- the educational standards of the class and/or school they are studying in;
- change can also be measured through longitudinal surveys where people are interviewed at different points during their lives. Statistical testing and modelling techniques can be used to generalise from small samples to larger populations, for example:
- predicting the outcome of an election;
- attitudes towards the economy in a country. Probability tests can be used to identify the key factor(s) associated with a particular outcome or behaviour. For example, are older people more likely to be worried about being a victim of crime than
about the prevalence of a very good system of collecting vital statistics and registration of births and deaths even before 300 B.C. are available in Kautilya’s ‘Arthashastra’. The records of land, agriculture and wealth statistics were maintained by Todermal, the land and revenue minister in the reign of Akbar (1556-1605 A.D). A detailed account of the administrative and statistical surveys conducted during Akbar’s reign is available in the book “Ain-e- Akbari” written by Abul Fazl (in 1596-97), one of the nine gems of Akbar. Sixteen century saw the application of Statistics for the collection of the data relating to the movements of heavenly bodies—stars and planets—to know about their position and for the prediction of Eclipses. Seventeenth century witnessed the origin of Vital Statistics. Captain John Graunt of London (1620-1674), known as the Father of Vital Statistics, was the first man to make a systematic study of the birth and death statistics. Modern stalwarts in the development of the subject of Statistics are Englishmen who did pioneering work in the application of Statistics to different disciplines. Francis Galton (1822-1921) pioneered the study of ‘Regression Analysis’ in Biometry; Karl Pearson (1857-
- who founded the greatest statistical laboratory in England pioneered the study of ‘Correlation Analysis’. ADVERTISEMENTS: His Chi-Square test (X^2 - test) of Goodness of Fit is the first and most important of the tests of significance in Statistics; W.S. Gosset with his t-test ushered in an era of exact (small) sample tests. Perhaps
most of the work in the statistical theory during the past few decades can be attributed to a single person Sir Ronald A. Fisher (1890-1962) who applied statistics to a variety of diversified fields such as genetics, biometry, psychology and education, agriculture, etc., and who is rightly termed as the Father of Statistics. In addition to enhancing the existing statistical theory he is the pioneer in Estimation Theory (Point Estimation and Fiducial Inference); Exact (small) Sampling Distributions; Analysis of Variance and Design of Experiments. His contributions to the subject of Statistics are described by one writer in the following words: “R.A. Fisher is the real giant in the development of the theory of Statistics.”
Concepts in Statistics:
1. Data: You might be reading a newspaper regularly. Almost every newspaper gives the minimum and the maximum temperature recorded in the city on the previous day. It also indicates the rainfall recorded, and the time of sunrise and sunset. In the school, attendance of the students are recorded in a register regularly. For a patient, the doctor advises recording of the body temperature at regular intervals. If we record the minimum and maximum temperature, or rainfall, or the time of sunrise and sunset, or attendance of children, or the body temperature of the patient, over a period of time, what we are recording is known as data.
limits. A score of 120 upon an intelligence examination, for example, represents the interval 119.5 up to 120.5. The exact midpoint of this score interval is 120 as shown below: Other scores may be interpreted in the same way. A score, of 15, for, instance, includes all values from 14.5 to 15.5, i.e., any value from a point .5 unit below 15 to a point .5 unit above 15. This means that 14.7, 15.0 and 15.4 would all be scored 15. “The usual mathematical meaning of a score is an interval which extends along some dimension from .5 unit below to. unit above the face value of the score.” (Garrett 1979)
3. Variable: In the field of education and psychology we study differences in respect of the persons’ personality traits, abilities, aptitudes, etc. For example, college students of the same class would differ in their performance on a particular test or on marks obtained in examinations. In all such cases, we are dealing with characteristics that vary or fluctuate in a rather unpredictable way. We find that, shape or quality is a characteristic on which objects vary; speed is a characteristic on which animals vary; height is a characteristic on which trees vary and people vary in respect of various characteristics like age, sex, height, weight and personality traits etc.
The characteristic on which individuals differ among themselves is called a variable. Thus speed, shape, height, weight, age, sex, grades are variables in the above examples. In educational and psychological studies we often deal with variables relating to intellectual abilities. Now, it is the aim of every physical and behavioural science to study the nature of the variation in whatever variable it is dealing with, and therefore, it is necessary to measure the extent and type of variation in a variable. Statistics is a branch of science which is concerned with the study of variables that vary in unpredictable fashion and helps in providing an understanding of the phenomena and objects which show such variations.
4. Measurement Scales: Measurement refers to the assignment of numbers to objects and events according to logical acceptable rules. The numbers have many properties, such as identity, order and additivity. If we can legitimately assign numbers in describing of objects and events, then the properties of numbers should be applicable to the objects and events. It is essential to know about the different kinds of measurement scales, as the number of properties applicable depends upon the measurement scale applied to the objects or events. Let us take four different situations for a class of 30 students: i. Assigning them roll nos. from 1 to 30 on random basis.
In the third situation, the students have been awarded marks from 0 to 50 on the basis of their performance in the test administered on them. Consider the marks obtained by 3 students, which are 30, 20 and 40 respectively. Here it may be interpreted that the difference between the performance of the 1st and 2nd student is the same, as between the performance of the 1st and the 3rd student. However, no one can say that the performance of the 3rd student is just the double of the 2nd student. This is because there is no absolute zero and a student getting 0 marks, cannot be termed as having zero achievement level. This scale refers to interval scale. Here the properties of identity, order and additivity are applicable. In the fourth situation, the exact physical values pertaining to the heights and weights of all students have been obtained. Here the values are comparable in all respects. If two students have heights of 120 cm. and 140 cm, then the difference in their heights is 20 cm and the heights are in the ratio 6:7. This scale refers to ratio scale.
Importance and Scope of Statistics:
The fact that in the modern world statistical methods are universally applicable. It is in itself enough to show how important the science of statistics is. As a matter of fact there are millions of people all over the world who have not heard a word about statistics and yet who make a profuse use of statistical methods in their day- to-day decisions. Statistical methods are common ways of thinking and hence are used by all types of persons. Examples can be multiplied to show that human behaviour and statistical methods have much in common. In fact statistical
methods are so closely connected with human actions and behaviour that practically all human activity can be explained by statistical methods. This shows how important and universal statistics is. Statistics in Social Sciences: Every social phenomenon is affected to a marked extent by a multiplicity of factors which bring out the variation in observations from time to time, place to place and object to object. Statistical tools of Regression and Correlation Analysis can be used to study and isolate the effect of each of these factors on the given observation. Sampling Techniques and Estimation Theory are very powerful and indispensable tools for conducting any social survey, pertaining to any strata of society and then analysing the results and drawing valid inferences. The most important application of statistics in sociology is in the field of Demography for studying mortality (death rates), fertility (birth rates), marriages, population growth and so on. In this context Croxton and Cowden have rightly remarked: “Without an adequate understanding of the statistical methods, the investigators in the social sciences may be like the blind man groping in a dark room for a black cat that is not there. The methods of statistics are useful in an over-widening range of human activities in any field of thought in which numerical data may be had.”
