The World of Statistics:
Fri, 20 Jan 2017 12:47:12 +0000
The importance of statistical literacy
By Eustarckio Kazonga
Introduction
Readers, welcome to The World of Statistics, in which everybody has an entry visa. As I open the door for you, I wish to introduce to you this special world of statistics. |
In this article I focus on the usage of statistics and statistical literacy. Some of you might have heard about statistics and others might have actually done a course or courses in statistics. Your background does not matter as you will not be subjected to any serious number crunching, or complicated and threatening formulae involving long calculations. The main objectives of this column are to: (a) demonstrate utilitilisation of statistics in our day-to-day lives (b) demystify statistics (c) to contribute to the improvement in reading, and interpretation of statistics. In this regard, the media is envisaged to play a very important role in meeting these objectives.
Statistics is a science that deals with collection, analysis and interpretation of data. Statistics is almost always used, in one way or another, in our day-to-day activities knowingly or unknowingly. This usage is even by those that have never had an opportunity to formally learn statistics or those who hated the subject when they were students. Statistics are used in different fields such as health, agriculture, politics, business, media, religion, tourism, education etc. For example, statistics that are used in media stories, debates, news releases, research, reports, and books need to be correctly read and understood.
In order to do this, statistical literacy is a fundamental requirement. When one refers to “50% Plus 1 Vote” concept, what does it mean? The meaning is in statistical literacy and thinking. It is therefore important that we should all be statistically literate. Statistical literacy basically refers to an individual’s ability to understand statistics. It is necessary for citizens to read and understand statistical materials in publications such as print and electronic media. Statistical literacy represents an aspect of media literacy, especially due to a growing share of the statistical information in media reporting. Wallman (1993) suggests that this ability is particularly needed to respond to the information that permeates everyday life and believes that it involves an appreciation of “the contributions that statistical thinking can make in public and private, professional and personal decisions.” It is strongly believed that a citizen’s right to understand and use the information produced by society is the basis of a democratic society. Wells (1903), imagines that statistical thinking [literacy] will one day be as necessary for efficient citizenship as the ability to read and write. Anyhow, in today’s knowledge-economy and information-driven societies, we undoubtedly all need to be good “statistical citizens”. Statistical literacy is one of the aspects of media literacy as confirmed from the media coverage. Statistics impacts greatly on the formation of attitudes and opinions in our society. For an average citizen today it is important to be informed about the issues related to public life, which is a personal culture of every man. The development of society and thus the lives of ordinary people are strongly affected by statistical literacy.
Uses of statistics
Having defined the concepts of statistics and statistical literacy, I now move to how statistics are used in a number of situations, by various users. There are many uses of statistics but among them are: monitoring and evaluation, planning, comparison, forecasting etc. in order to promote statistical literacy. With these uses in mind, I now illustrate the variety of users of statistics and how they use these statistics.
Churches
Churches generate and use statistics such as financial contributions/offerings made during church services. The records can be weekly, monthly or yearly. The general behaviour of these collections is studied in order to determine if it is constant, increasing or decreasing over a period of time. The churches are able to indicate weeks or months of low or high collections/contributions. In statistics, this is formally done as time series analysis to determine trend, seasonal and cyclical variations. Another aspect is growth of the church, which partially measured by the number of followers. Churches would need to pay attention to the age group statistics. Questions can be asked such as are the majority of followers old people? If so why and what does it mean to the church? Furthermore, another question can be asked how many people attend Small Christian Community meetings and what is the gender distribution of those who attend? If very few men attend, there is need to find out why this is so. There a lot of church statistics, which for this purpose I have coined chu-statistics, that are collected and interpreted from the operations of the church. For example, in a month the church may receive following offerings followers: K2900, K1800, K1500 and K900. This will be interpreted as a downward trend and further analysis will be done as to why this is the case. In answering a number of these questions data is collected, analysed and interpreted. The ability to do this is found in statistical literacy.
Public service vehicle drivers and conductors
Daily or weekly or monthly cash-in targets are given and recorded. Drivers, Conductors and vehicle owners will be able to determine if these targets were met. If not met they will find out why since this is a recording of numbers at a regular interval of a period of time, which is referred to as time-series in statistics. They will be able to judge their performance as they can determine the general behaviour of their cash-ins, which is referred to as trend in statistics.
Villages
Each Village Headman is expected to have a village register, to contain number of households and names of all people in his village. This is a village census of population. Farmers always keep count of their animals [goats, sheep, cattle]. They further record in their heads or on paper how much seed they have planted, amount of fertiliser used, cost of inputs, area planted/cultivated, production levels and number of bags of maize or soyabeans sold and the selling prices in a particular agricultural season. Through these recordings, a comparison can then be made to the previous season(s).
In our traditional set-up, it is said that when you see a lot of masuku fruits around August September, it means that there will be high amounts of rainfall in that season. It is clear that these people did not just come up with this prediction in just a day or month but over a period of time [years]. In this situation, a concept of trend analysis was applied and now they just pass it on from one generation to another as their own traditional way of forecasting amount of rainfall. This is technically forecasting. This was discovered after a long time and it is now being passed on from one generation to the other. Off course these forecasts are not perfect just like the formal forecasting models.
Politics
Politicians usually refer to a campaign strategy known as “door-to-door”. They target direct personalised contact with each and every voter in a particular area but very few think of it being a statistical concept. Almost every politician believes that he or she is the most popular among all the other candidates but it is only confirmed by the number of votes received. Surprisingly, little do they know that they are using a descriptive statistic known as mode. Politicians sometimes use number of people attending their political rallies to assess their popularity but this should be carefully interpreted as it can be misleading in some cases. Statistical literacy is a core skill required for politicians as it will enable them to appropriately interpret political statistics.
Opinion polls are usually conducted to predict [forecast] the election results. It is a fact that some of these opinion polls totally miss the actual results while others make very good predictions. Some of the fundamentals that require to be systematically interrogated as a user or reader of such statistics are: how the data was collected and analysed, number of people interviewed (sample size). When the opinion poll process strictly follows the statistical principles usually a good or reasonable estimate is made close to the actual results.
Political parties need to know how many members, Members of Parliament, Councillors, and Council Chairpersons/Mayors that they have. This is a statistical concept. It is important for political parties to know the number of votes their candidates in elections get as these can be informative when correctly used or interpreted. For example, a constituency has 25,000 total numbers of registered voters, 5,000 votes are cast giving a 20% voter turn-out. In interpreting the results, political parties need to bear in mind that the statistic – voter turn-out of 20% can be informative. It is therefore important to investigate why such a low figure was recorded in the constituency. Voters’ registers are sold by the Electoral Commission of Zambia (ECZ) to politicians or any member of the public who need them. The Central Statistical Office (CSO) conducts Census of Population and Housing, which contain important official statistics for use by various categories of people including politicians. These are necessary statistical tools for efficient governance. Members Parliament, Mayors, Council Chairpersons and Councillors need to enhance their statistical literacy skills, which can help them be better statistical consumers. It is claimed that those who understand basic statistical literacy concepts and are more engaged in debates which use statistical evidence, are less passive and accepting arguments that use statistics, better at spotting and avoiding common statistical pitfalls, able to make quick calculations of their own and have an idea where to look for data.
Education
Schools keep a record of pupils [numbers, gender distribution, national examination pass rates] over a period of time. In addition, teachers in these schools collect and use a lot statistics in their classes. For example, number of pupils in each of their classes, attendance registers, test results, ranking of pupils in terms of their performance, average class marks, progression of pupils from one level to the other, and comparisons of performance of pupils within the school and other schools. By ranking the pupils in terms of performance, they use an aspect of non-parametric statistics and by calculating an average, they are dealing with one of data descriptive.
Health
Statistics plays a very important role in monitoring and evaluation of health-related programmes. They measure a variety of health indicators. For example, the Growth Monitoring Programme for children, demands mothers and caregivers having basic statistical literacy skills for correct interpretation of the results of the programme on a child. Statistics are also obtained on the overall health sector performance, Zambia Demographic and Health Surveys, disease burden and trends, health facilities statistics in Zambia, by level and type of ownership, access to health care services, health workforce, and health sector financing. All these require statistical literacy.
Media
Statistics in both print and electronic media are often included in the media to support facts. Very often averages, percentages, tables, charts and diagrams are used. Goldian (2008), states that news depends on a careful dissection of numbers. Statistics are everywhere, from how many farmers are on the E-voucher pilot scheme under the Farmer Input support Programme (FSP), what percentage of people has access to clean drinking water etc. This is further strengthened by Ayayi (2001) who argues that everybody should be involved in the statistical development of a country including the suppliers of statistical data (the respondents), the users of statistical products, the producers (statistical workers) and, a special group, the media which is always referred out as the fourth estate.
Agriculture
A lot of statistics are used in agriculture in order to ascertain crop production and productivity. Statistics are also collected on rainfall statistics, area planted, use of agricultural inputs, livestock census, and animal and crop diseases. For example one may say that army worms are most likely going to be eradicated within the next two weeks. This is a statement that is giving likelihood of this event to happen. Technically this is referred to as probability. A statement on crop diseases such as: About 63,975 farmers in various parts of the country have been affected by arm worms and over 89,000 hectares of maize fields have been affected with Central Province being the most hit by the crisis followed by Copperbelt and Lusaka Provinces. On the basis of this statement, the use of the word about implies that the figure is not exact. It is an approximation. Equally, the word over implies that the exact figure is not known but it is certainly more than 89,000 hectares. Given the statement and one has a farm in Central Province, it will be interpreted that the likelihood of the farm being affected by army ways is very high. This is a typical element of conditional probability. Such statistical reasoning and thinking is derived from statistical literacy.
Conclusion
In conclusion, these demonstrate just a sample of areas in which statistics is used in order to highlight why statistics and statistical literacy are import in our everyday lives. I wish to emphasise that we all use statistics in one form or another but statistical literacy is necessary as it provides the foundation for reasoning and thinking.
It is every citizen’s right to understand and use statistical information produced by society as it is the basis of a democratic society. Anybody can be a user of statistics – from accidental users to major users. This is a world in which everybody consumes statistics, regardless of age, colour, gender, academic qualifications etc. Welcome, once more, to The World of Statistics! My next article will focus on one specific field of application of statistics in details.