Definition of Statistics in Economics
Statistics, in itself, is the collation and analysis of numerical data to arrive at specific inference. This academic discipline finds application in various other branches of studies, such as Economics. Any study about Economics and Statistics involves the validation of theories with quantified data sets. For instance, the Theory of Demand must be eventually supported by the examination of data on incomes, quantities and prices.
Definition of Statistics
Originally the term ‘statistics’ was used to collect data relating to historical and descriptive regions. It has now acquired a very broad definition and is used for all types of data and methods for data analysis. So in recent times, it has been used in two ways, namely, singular and plural.
Features of Statistics in its Plural Sense
Expressed numerically: Economic statistics are numerical and quantitative. Symbolic adjectives such as rich, poor, tall etc. have no value attached to the universal mathematical value.
Reasonable accuracy: The mathematical conclusion must be accurate based on the purpose of the investigation, its nature, size and available resources.
Can involve estimation: If the field of study is large, for example, the number of people attending the rally, a small estimate can be tricky. However, for small learning areas, take, for example, the number of students in each college learning area, counting numbers directly is easy and important.
Systematic collection of data: Data collection should be done in an orderly manner, that is, raw data collection without any information about its origin, purpose etc. is not allowed in the mathematical universe.
Relative: Economic statistics in their sense of quantity have a comparative aspect. This means that the same type of data from different sources can be compared.
Multiple items: Statistics are affected by a large number of features and not just one item. For example, an increase in the price of an asset is not the result of a change in one area but a result of a large number of factors.
Addition: Mathematics is a middle or integration game. The number represented by one business is not related to statistics. For example, the height of one student is not mathematical data but the average length of students in a class is the same.
Statistics in its Singular Sense
Whenever we use mathematical methods for collecting, dividing, presenting, analyzing, and interpreting quantitative data, we call mathematics a singular noun. In addition, this involves holding various stages of mathematical research. Each section has its own set of tools to do a specific task. These are:
Stage 1- Data Collection: First we need to collect statistical data to begin the statistical research journey. Census techniques and samples are commonly used in this category.
Phase 2- Data editing: Yes data in raw or chaotic format is difficult to translate. This is the reason why the second phase deals with the classification of collected data. Data editing is done with the help of data collection and statistics bars.
Step 3- Data Presentation: After editing, this data needs to be properly presented. Data presentation is widely achieved with the help of tables, graphs, and diagrams.
Phase 4- Data analysis: Before moving on to the final stage, we first need to find out the percentages, averages and so on to draw conclusions about the data. Percentages, estimates, correlations and regression coefficients form the data analysis toolbox.
Stage5- Data Translation: Finally, we need to translate data and conclude or build ideas about data. This is done with the help of percentage size, average, and level of relationship between different economic variables.
Benefits of Statistics in Economics
There are many economic benefits to economics. We cannot imagine economics without statistics. Statistics have put the economy on another level. Here are a few economic benefits: -
Quantitative expression:
Statistics give extra weight to quantity data. It also enhances economic credibility and financial integrity by releasing data in bulk. If you understand the size of the mathematical data, it would be easier for us to solve the economic crisis.
Economics Theories Deduction:
Economic statistics are also useful in attracting economic ideas. It helps to establish theories of economic theatre and models by providing evidence.
Identifying patterns and predicting economic events. It is also helpful to identify patterns in the data. There are many economic math tools that help you do this job successfully. So it helps to predict future trends.
Policy formulation:
Policy formulation is used to formulate national policies. Statistics are very helpful in creating an effective policy. There are many economic statistics that help you create better policies. Many economists use mathematical tools in this field.
Economic equality:
It is a workplace used between manufacturers and consumers. In this case, both sides are satisfied with the market. It is very easy to do economic equality and economic statistics.
If you are asked to write three sentences highlighting the importance of Statistics in Economics, the following points would be the relevant aspects-
The explanation of different parameters in Economics may require quantification for further study. Based on such quantitative data, comparison can be made across various sectors within the economy as well as across different plan periods.
Data sets are required to present causal relationships between different phenomena, which become particularly important for policy formulation.
For the development of Economic theories such as variation of price concerning product demand, concrete data sets are required.
Statistical data becomes essential in terms of forecasting for alterations in economic influence factors.
Characteristics of Statistics
Any discussion in the concept of Economics and significance of Statistics in Economics notes would necessarily focus on different features of Statistics as well. Some of those features are:
Aggregation of Facts
Numerical data is essentially an aggregation of facts, which means, there will be multiple facts or information clubbed together. Influence on data – There are multiple causes which influence data to a certain extent. For example, any data on malnutrition will not only include poverty as one of its underlying causes but also other aspects such as hygiene, practices of a marginalised community etc.
Data Presentation
There are specific stipulations in terms of data presentation. It has to be numerically expressed accurately and also placed in the common context of each other.
Collection
The collection of data should necessarily be for a predetermined purpose, and the collection technique has to adhere to any given systematic procedure.
Various Stages of Statistical Method
When you are asked a question such as “Briefly explain how Statistics helps to study Economics”, be sure to also include the different stages in the Statistical method. There are five main stages:
Stage I:
The initial step is to have clear ideation with regards to the problem that has to be worked on. Based on such a clear definition can the identification and collection of data be undertaken.
Stage II:
Before starting data collection, there is a range of steps that have to be observed. The steps are (a) determination of the source of data, (b) type of enquiry, (c) defining the statistical unit and (d) establishing a degree of accuracy.
Stage III:
A proper method of data collection has to be decided regarding the nature of study, scope and objective of the research, grants provided etc. The most common techniques adopted for data collection are sampling techniques or census techniques.
Furthermore, the raw data has to be organised and edited for interpretation purposes. Data organisation can be done by way of tally bars, among others.
Stage IV:
Data analysis is done through Statistical measures such as coefficients, percentages, averages etc.
Stage V:
The final stage is the interpretation of data to arrive at a conclusion based on the data sets. The patterns or relations in interpretation lend a broader meaning to the findings of the survey.
Benefits of Statistical Study in Economics
In the concept of Economics and significance of Statistics in Economics, the advantages inherent to Statistical Study indicates the latter’s importance –
The quantitative expression extends higher accuracy and credibility to result.
The development of Economic theories requires grounding on Statistics for the creation of viable models.
Forecasting of Economic events needs identification of specific patterns seen in raw data.
Inter-temporal and Inter-sectoral comparisons can be made for better policy formulation.
Disadvantages of Statistical Study in Economics
The main limitations of Economics and Statistics include:
Statistical inference holds only on average computation.
It can only deal in aggregates, and a single observation will have no bearing.
Heterogeneous data will not be applicable.
Errors can creep in collection, analysis and interpretation of data if not handled with expert knowledge.
FAQs on Statistics in Economics: Uses and Importance
1. What is the meaning of statistics in the context of economics?
In economics, 'statistics' is understood in two ways. As a plural noun, it refers to numerical data or facts, such as data on population, unemployment, or inflation. As a singular noun, statistics is the science of collecting, organising, presenting, analysing, and interpreting this numerical data to understand economic problems and validate economic theories.
2. What is the importance of statistics for studying economics?
Statistics is crucial for studying economics as it helps to:
- Quantify Economic Problems: It allows economists to express problems like poverty or unemployment in precise numerical terms.
- Validate Economic Theories: Theories like the law of demand are tested and proven using statistical data.
- Facilitate Economic Forecasting: By analysing past data, statistical tools help in predicting future trends, such as inflation rates or GDP growth.
- Aid in Policy Formulation: Governments use statistical data on factors like income and prices to formulate effective economic policies.
- Enable Inter-sectoral and Inter-temporal Comparisons: It allows for the comparison of economic growth between different sectors of the economy or over different time periods.
3. What are the five main stages involved in a statistical study?
A statistical study systematically progresses through five distinct stages:
- Collection of Data: The first step is gathering data relevant to a pre-defined problem, using methods like surveys or experiments.
- Organisation of Data: Raw data is organised and structured into a more understandable format using tools like tally bars and arrays.
- Presentation of Data: The organised data is presented clearly using tables, graphs, and diagrams to make it easy to comprehend.
- Analysis of Data: The presented data is analysed using statistical measures like averages, percentages, and correlation to find patterns.
- Interpretation of Data: The final stage involves drawing meaningful conclusions from the analysed data to understand the economic phenomenon being studied.
4. How exactly does statistics help in formulating economic policies for a country?
Statistics forms the backbone of effective economic policy-making. For example, to create a policy to control inflation, the government first needs statistical data on price levels over time. By analysing this data, policymakers can understand the magnitude of the problem, identify its causes (e.g., rising fuel costs or supply chain issues), and then formulate targeted policies like adjusting interest rates. Later, they use new statistical data to evaluate the effectiveness of these policies.
5. Why is it often said that the field of economics is unimaginable without statistics?
Economics would be purely theoretical and abstract without statistics. Economic concepts like National Income, poverty, and demand elasticity would just be ideas. Statistics provides the tools to measure these concepts, giving them concrete, real-world meaning. It allows economists to move from qualitative statements (e.g., "prices are rising") to precise, quantitative analysis (e.g., "the inflation rate was 5.8% last quarter"), which is essential for verification, comparison, and policy-making.
6. How is the concept of 'demand' in economics explained with the help of statistics?
The economic theory of demand states that, all else being equal, as the price of a good falls, its quantity demanded increases. While this is a qualitative statement, statistics makes it verifiable. Economists can collect data on the price of a product and the corresponding quantities sold over a period. By analysing this data, they can establish a numerical relationship, create a demand schedule or curve, and thus provide empirical evidence to support the theory.
7. What are the major limitations of using statistics in economic analysis?
While statistics is powerful, it has several limitations in economics:
- Ignores Qualitative Aspects: Statistics deals with numerical data and cannot directly study qualitative phenomena like honesty, welfare, or culture.
- Focuses on Aggregates: Statistical conclusions are based on the average or aggregate behaviour and may not be true for an individual case.
- Requires Uniformity: Statistical methods are not applicable to heterogeneous or dissimilar data.
- Potential for Misuse: Without context, statistical results can be manipulated to support a pre-drawn conclusion.
- Results are True Only on Average: Statistical laws are not as exact as laws of natural sciences; they are tendencies based on probability.
8. If statistics only deals with numbers, how can it study a qualitative problem like poverty?
This is a common misconception. While statistics cannot directly measure the feeling of poverty, it can analyse it by converting the problem into quantitative terms. For instance, poverty can be defined and measured using numerical indicators such as:
- The number of people below a certain income level (the poverty line).
- Average daily calorie intake.
- Consumption expenditure on essential goods.
By collecting and analysing data on these indicators, economists can statistically assess the extent and severity of poverty in a region.
