- Data are numerical facts or measurements collected from the real world. A single measurement is called a datum.
- Raw data alone may not give clear meaning; it must be analysed and organised to derive useful information.
- Data is important in geography to study patterns like population, rainfall, crop production, migration and city growth.
- Proper statistical analysis and presentation of data is necessary to avoid wrong conclusions (statistical fallacy).
- Modern geographical studies focus more on quantitative analysis using data to explain relationships between different variables clearly and logically.
Key Points
Key Points: Secondary Sources of Data
- Secondary data is data already collected by others and available in published or unpublished records.
- Government publications are the main sources, e.g. Census of India, NSS reports, IMD weather reports, statistical abstracts, commission reports.
- Semi-government and international sources include reports from Municipal Corporations, Urban Development Authorities, and UN agencies like UNESCO, UNDP, WHO, FAO (e.g. Human Development Report).
- Private sources include yearbooks, surveys, research reports published by private organisations, along with newspapers and magazines.
- Unpublished sources include village revenue records (patwari), municipal plans, government documents, and records of companies, trade unions, political organisations, and welfare associations.
Key Points: Data and Its Importance in Geography
Key Points: Sources of Primary Data
- Data is collected from two sources: Primary sources and Secondary sources.
- Primary data is collected first-hand by a person or organisation for the first time, while secondary data is taken from already published or unpublished records.
- One important source of primary data is personal observation, where information is collected directly through field surveys.
- Interviews are used to collect direct information through conversation, and questions should be simple, polite and unbiased.
- Questionnaires and schedules help collect data from large areas; in questionnaires respondents fill answers themselves, while in schedules an enumerator fills it, making it useful even for illiterate people.
Key Points: Tabulation and Classification of Data
- Raw data is unorganised information. To make it meaningful, it must be classified and tabulated.
- A statistical table arranges data in rows and columns, making it easy to understand, compare and save space.
- Data can be presented in three forms:
Absolute values (original numbers), Percentages/Ratios, and Index numbers. - Index number shows change over time or place.
Base year is usually taken as 100 and other years are compared with it. - Grouping of data means dividing raw data into classes (like 0–10, 10–20, etc.) to reduce volume and simplify study.
- Classification is done using tally marks (Four and Cross method), and the final result is shown as a frequency distribution table.
- Frequencies are of two types:
Simple frequency (f) = number of observations in a class,
Cumulative frequency (Cf) = total frequency up to that class (helps in “less than” or “more than” comparisons).
