Data Its Source and Compilation Class 12 NCERT Solutions

The chapter defines data as "numbers or characters that represent measurements from the real world". Tally-mark grouping uses four vertical strokes with the fifth drawn diagonally to make blocks of five, the tally-marking method. An ogive is a graph of cumulative frequency (not simple frequency) plotted against the upper class-limit. In frequency grouping, the inclusive method keeps both ends of a class interval (10-19, 20-29) and the exclusive method drops the upper end (10-20 keeps the 10 but excludes the 20).

• (i) A digit is a single character (0-9); a number is one of many forms a measurement can take. The chapter's exact phrase "represents measurement" is the textbook definition of data. Answer: (b) Data.
• (ii) Tables and frequency distributions are ways to organise data; information is the processed output. A single datum is a single observation from the real world. Answer: (c) Real world.
• (iii) The standard tally pattern, four strokes and a diagonal fifth, is called the tally marking method. Answer: (b) Tally Marking Method.
• (iv) An ogive is defined as a graph in which cumulative frequency is plotted against the upper class-limit. It is a graphical method, not a measuring method. Answer: (d) Cumulative frequency is plotted.
• (v) The exclusive method excludes the upper end of the class interval; the inclusive method takes both ends. Answer: (b) Inclusive Method.

(i) (b) Data; (ii) (c) Real world; (iii) (b) Tally Marking Method; (iv) (d) Cumulative frequency is plotted; (v) (b) Inclusive Method.

Data are raw measurements; information is the meaning we get after processing those measurements. Data processing is the act of organising, cleaning, computing and presenting data. Footnotes clarify or qualify a table's entries. Primary sources collect first-hand data; secondary sources publish already-collected data.

• (i) Data vs Information. Data are raw, unprocessed measurements (heights, marks, populations). Information is the meaning we obtain after processing the data (an average, a trend, an interpretation). Data without processing is like an unlit lamp; information is the lit lamp.
• (ii) Data processing. Data processing is the chain of steps that turns raw data into useful information: collection, editing, classification, tabulation, calculation, graphical representation and interpretation. Each step adds a layer of meaning. Today this is largely done with software (Excel, R, Python, SPSS, GIS).
• (iii) Advantage of a footnote in a table. A footnote provides extra information that does not fit in the column headers: source of the data, units, special definitions, exceptions or limitations. It helps the reader interpret the figures correctly and flags any caveats that affect comparability.
• (iv) Primary sources of data. Primary sources provide data that are collected for the first time by the investigator, through direct observation, personal interviews, questionnaires, schedules, telephone or online surveys, focus-group discussions and field measurements (soil kit, water quality kit). Primary data are fresh and customised to the investigator's purpose.
• (v) Five sources of secondary data. Government publications (Census of India, Statistical Abstract, NSSO reports, RBI bulletins), international organisation publications (UN, UNESCO, WHO, FAO, World Bank, IMF), books and journals (research journals, university publications), newspapers and magazines (The Hindu, Down to Earth, EPW), and electronic media and databases (data.gov.in, internet, RBI portal, MoSPI).

Data are raw measurements; Information is processed meaning. Data processing is the collection-to-interpretation chain. Footnotes clarify source, units and caveats. Primary sources collect first-hand data. Secondary sources: government publications, international organisations, books and journals, newspapers and electronic media.

Secondary data are collected by specialised agencies and then published for everyone's use. At the national level India has the Census of India, NSSO, Ministry of Statistics and Programme Implementation (MoSPI), RBI and other line ministries. At the international level the United Nations, FAO, WHO, UNESCO, World Bank and IMF lead. An index number is a single ratio that captures the relative change in a value (price, production, population) between a base year and a current year, scaled to 100. It is indispensable for comparison across time.

• (i) Agencies for secondary data. National agencies. Census of India, conducted by the Office of the Registrar General every ten years; the country's biggest population dataset. National Sample Survey Office (NSSO), now under MoSPI, runs large rounds on employment, consumption, education and health. Ministry of Statistics and Programme Implementation (MoSPI) publishes the Statistical Abstract and household-survey reports. Reserve Bank of India (RBI) publishes banking, monetary and macroeconomic data. Other line ministries include Ministry of Agriculture and Farmers' Welfare (crop statistics), Ministry of Earth Sciences (IMD weather data), and Department of Land Resources (land records). International agencies. United Nations system (UN Statistical Division, UNDP for HDR). FAO (food and agriculture data). WHO (health data). UNESCO (education and culture data). World Bank and IMF (development and financial data). Other bodies include WTO (trade), ILO (labour), OECD, IUCN (biodiversity), IEA (energy) and IPCC (climate).
• (ii) Importance and calculation of an index number. An index number is the most compact way to express relative change. It is used in almost every field: the Consumer Price Index measures inflation; the Index of Industrial Production tracks industry; the Human Development Index ranks countries. Without an index number, comparison across time and place is messy and incomparable. The simplest form is: Index (t) = (Value in year t / Value in base year) x 100. Example: if rice price in 2020 (base year) was Rs 40 per kg and in 2025 it is Rs 52 per kg, then Index (2025) = (52 / 40) x 100 = 130. So rice has become 30 percent more expensive over five years. For a basket of items, weighted formulae (Laspeyres, Paasche, Fisher) extend this idea.

Secondary data come from national agencies (Census, NSSO, MoSPI, RBI) and international agencies (UN, FAO, WHO, UNESCO, World Bank, IMF). An index number compresses relative change into a single ratio scaled to 100; e.g. rice price rising from Rs 40 to Rs 52 gives an index of 130 (a 30 percent rise).