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.
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.
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:
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.
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.
The collection of data should necessarily be for a predetermined purpose, and the collection technique has to adhere to any given systematic procedure.
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:
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.
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.
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.
Data analysis is done through Statistical measures such as coefficients, percentages, averages etc.
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.
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.
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Q1. What is the Role of Statistics in Economics?
Ans. In the context of a discussion about Economics and Statistics, the study of various Economy theories or its application needs to be necessarily analysed by way of numbers. There exists a whole host of variables within economic and social phenomena. Such variables are better presented by Statistics, laying out the facts based on figures. It enables a comparison between facts.
For example, the establishment of a relationship between demand and supply and that of price or price level and money supply requires the application of Statistics. Modern econometric methods are dependent on Statistics.
Q2. What are the Limitations of Statistical Application in Economics?
Ans. The shortcoming about Economics and Statistics relates to the latter’s inadequacy in certain specific parameters. Few of the vital limitation include (1) Qualitative aspects such as health not taken into consideration (2) No focus on individual items as only aggregate is indicated (3) Discrepancy in data collection may alter the result or lead to misinterpretation (4) Result accuracy can be best found in average etc.
Q3. What are the Different Stages of Statistical Method?
Ans. There are five main stages of Statistical method. Those are – (1) Data collection, (2) Data organisation, (3) Data presentation, (4) Analysis (5) Interpretation.
The collection of data can be done through sample techniques or by taking a census. The next stage is an organisation which is most likely to be done through tally bars or any other systematic procedure, as the case may be. Subsequently, data may be presented by graphs, diagrams or tables etc. Data analysis is done in terms of percentages or averages. Those are the most commonly used techniques for analysis. For data interpretation, the tools that are used include averages and degree of relationship between various variables, the magnitude of percentages etc.