Big picture
People have unlimited wants but limited resources (money, time, land). This scarcity forces everyone (individuals, firms and governments) to make choices. Economics studies how these choices are made.
To understand economic problems such as poverty, inflation or unemployment, we need facts in numbers, and methods to collect and analyse them. That is the role of statistics. This chapter introduces both ideas and the basic vocabulary used in the rest of the statistics unit.
Learning goals
Explain scarcity, choice and the basic economic activities.
Define statistics in the singular and plural senses.
Explain the characteristics of statistics as data.
Explain the importance of statistics in economics.
Explain the limitations of statistics and why people sometimes distrust it.
Distinguish discrete and continuous variables, and quantitative and qualitative data.
Core ideas
1. Economics: scarcity and choice
Scarcity: resources are limited in relation to wants. Every student wants more time to study, play and sleep, but has only 24 hours.
Choice: because of scarcity, we must choose how to use resources. Choosing one option means giving up another; the value of the next best alternative given up is the opportunity cost.
Basic economic activities
Activity | Meaning | Person involved |
|---|---|---|
Consumption | Using goods and services to satisfy wants | Consumer |
Production | Making goods and services to earn income | Producer |
Distribution | Dividing national income among factors of production as wages, rent, interest and profit | Factor owners |
Economics can be divided into consumption, production and distribution studies. In each, we need data, such as how much households spend, how much firms produce, and how income is shared.
2. Meaning of statistics
In the plural sense, statistics means numerical facts or data collected for a purpose, such as the population of India, marks of students in a class, or prices of rice over ten years.
In the singular sense, statistics means the science (or methods) of collecting, organising, presenting, analysing and interpreting numerical data.
Stage | What is done |
|---|---|
Collection | Gathering data through surveys or published sources |
Organisation | Classifying and arranging data |
Presentation | Showing data in tables, diagrams and graphs |
Analysis | Applying methods such as averages and correlation |
Interpretation | Drawing conclusions from the analysis |
3. Characteristics of statistics (as data)
Characteristic | Explanation | Example |
|---|---|---|
Aggregate of facts | A single figure is not statistics; a group of related figures is | "Ravi is 160 cm tall" is not statistics; the heights of all students in a class are |
Numerically expressed | Facts must be in numbers; "very good" or "rich" is not statistics unless measured | Marks out of 100 |
Affected by multiple causes | Data reflect many factors | Crop output depends on rainfall, seeds, fertilisers and irrigation |
Reasonable standard of accuracy | Absolute accuracy isn't possible, but data must be reasonably accurate for the purpose | Population figures rounded to the nearest thousand |
Collected in a systematic manner | Data must be collected carefully, using a proper method | A planned census |
Collected for a predetermined purpose | The purpose must be clear before collecting | Data on family income for studying poverty |
Placed in relation to each other | Data should be comparable (same units, same basis) | Comparing the price of wheat in two years in ₹ per quintal |
4. Importance of statistics in economics
Quantitative expression of economic problems: it states economic facts precisely in numbers, such as "inflation is 5%".
Inter-relations between economic facts: it helps find relationships, such as between price and demand, or income and consumption.
Formulating economic policies: the government uses data on unemployment, prices and production to plan policies.
Forecasting: data from the past help predict future trends, such as demand for electricity next year.
Testing economic theories: economic laws (for example, the law of demand) can be tested with real data.
Comparison: data help compare economic progress across years and countries.
5. Limitations of statistics
It does not study individuals: it deals with aggregates. The income of one family isn't statistics; the average income of families is.
It ignores qualitative aspects: honesty, intelligence and beauty can't be studied directly unless converted into numbers.
Results are true only on average: a statement such as "the average Indian family has four members" may not be true of a particular family.
It can be misused: figures can be selected or presented in a misleading way.
Data must be homogeneous: you can't meaningfully compare the height of trees with the weight of people.
6. Distrust of statistics
People sometimes say "statistics can prove anything". This distrust arises when data are collected carelessly, presented with bias, or interpreted wrongly. The fault lies not in statistics as a science, but in its misuse. Careful collection and honest interpretation remove these problems.
7. Basic terms
Variable: a characteristic that changes from one item to another and can be measured, such as height, income or marks.
Type | Meaning | Example |
|---|---|---|
Discrete variable | Takes only certain values (usually whole numbers), with gaps between them | Number of children in a family (1, 2, 3), number of cars |
Continuous variable | Can take any value within a range, including fractions | Height (152.4 cm), weight, temperature, time |
Types of data
Basis | Types |
|---|---|
Nature | Quantitative (measurable in numbers: income, marks) and qualitative (attributes that can't be measured directly: gender, literacy, colour) |
Source | Primary data (collected first-hand by the investigator for the purpose) and secondary data (already collected by someone else and used again) |
A reliable approach to questions
To decide if something is statistics (data), check: is it an aggregate, numerical, comparable and collected for a purpose?
To classify a variable, ask whether it can take fractional values (continuous) or only separate values (discrete).
For importance or limitations, give an economic example for each point.
Connections that matter
Collection of data explains how primary and secondary data are gathered.
Organisation and presentation of data shows how data are classified, tabulated and graphed.
Measures of central tendency and correlation are the analysis methods.
Common mistakes
Calling a single figure statistics. Statistics needs an aggregate of related facts.
Saying statistics studies individuals. It studies groups.
Classifying height as discrete. Height is continuous.
Blaming statistics for misuse. Distrust arises from misuse, not from the science itself.
Revision checklist
I can explain scarcity, choice and the basic economic activities.
I can define statistics in both senses and list the stages of a statistical study.
I can explain the characteristics of statistics with examples.
I can explain the importance and limitations of statistics in economics.
I can classify variables and data.