Collection, Organisation and Presentation of Data

Unit – 2: Collection, Organisation and Presentation of Data (12 Marks)

AHSEC Class 11 Economics Chapterwise Notes

Q.1. Define the following: survey/Enquiry, Statistical design, Statistical units, Statistical data, variables and attributes.

Ans: Survey/Enquiry: Survey or enquiry is a device of obtaining the desired data. (2016)

Statistical design: It involves identifying a decision problem and choosing an approach to solving the problem.

Statistical units: The units in which the investigator counts or measures the variables for enumeration, analysis and interpretation is known as statistical unit.

Data/Statistical data: Data refers to any group of measurements which provide information which the decision maker uses for better decision.

Variables: A variable is a characteristics that may take on different values at different times, places or situations.

Attributes: Qualitative observations of elementary units is called attributes.

Q.2. What are various types of Statistical Data? Mention their merits and demerits.       2015

Ans: Statistical data are of two types

(a) Primary data

(b) Secondary data.

Primary Data: Data which are collected for the first time for a specific purpose are known as Primary data. For example: Population census, National income collected by government, Textile Bulletin (Monthly), Reserve bank of India Bulletin (Monthly) etc.

Secondary Data: Data which are collected by someone else, used in investigation are knows as Secondary data. Data are primary to the collector, but secondary to the user. For example: Statistical abstract of the Indian Union, Monthly abstract of statistics, Monthly statistical digest, International Labour Bulletin (Monthly).

Merits and Demerits of Primary Data:


(a) They are reliable and accurate.

(b)  It is more suitable if the field of enquiry is small.


(a) It the field of enquiry is too wide, it is not suitable.

(b) Collection of primary data is costly and time consuming.

(c) Personal Bias may affect the data.

Merits and Demerits of Secondary Data:


(a) While using secondary data, time and labour are saved.

(b) It may also be collected from unpublished form.


(a) Degree of accuracy may not be acceptable.

(b) Secondary Data may or may not fit the need of the project.

(c) Data may be influenced by personal bias.

Q.3. What points are taken into consideration while choosing between primary data and secondary data.

Ans: Choice between primary data and secondary data:: The investigator must decide at the outset whether he will use primary data or secondary data in an investigation. The choice between the two depends mainly in the following considerations:

a) Nature and scope of the enquiry.

b) Availability of financial resources.

c) Availability of time.

d) Degree of accuracy desired, and

e) The collecting agency.

Q.4. Distinguish between Primary data and Secondary data.

Ans: Difference between Primary Data and Secondary Data:

(a) Primary data are those which are collected for the first time and thus original in character. While Secondary data are those which are already collected by someone else.

(b) Primary data are in the form of raw-material, whereas Secondary data are in the form of finished products.

(c) Data are primary in the hands of institutions collecting it while they are secondary for all others.

Q.5. What are various sources of Secondary Data? Mention the points which should be considered before using secondary data.      2017

Ans: Sources of Secondary Data

1. Official publication by the central and state governments, district Boards.

2. Publication by research institutions, Universities etc.

3. Economic Journals.

4. Commercial Journals.

5. Reports of Committees, commissions.

6. Publications of trade associations, Chamber of Commerce etc.

Precautions in the use of Secondary Data: The following aspects should be considered before use of secondary data:

(i) Suitability: The investigator must check before using secondary data that whether they are suitable for the present purpose or not.

(ii) Adequacy: After satisfying about the suitability of data, the investigator has to determine whether they are adequate for the present purpose of investigators.

(iii) Dependability: Dependability of secondary data is determined by the following factors:-

  1. The authority which collected the data.
  2. Procedure of Sampling followed.
  3. Status of Investigator.

(iv) Units in which data are available.

Q.6. What are various essential qualities of Secondary data? Explain some effective methods of collecting primary data.

Ans: Qualities of Secondary Data:

(a) Data should be reliable.

(b) Data should be suitable for the purpose of investigator.

(c) Data should be adequate.

(d) Data should be collected by trained investigator.

Methods of collecting primary Data

(a) Direct Personal Observation: Under this method, the investigator collects the data personally from the persons concerned.

(b) Indirect Oral Investigation: Under this method, the investigator collects the data from third parties capable of supplying the necessary information.

(c)  Schedule and questionnaire: A list of question regarding the enquiry is prepared and printed and send to the person concerned.

(d)  Local reports: This method gives only approximate results at a low cost.

Q.7. What are various stages involved in statistical investigation? Explain them briefly.

Ans: Various stages in statistical investigation: There are five stages in a statistical investigation which are given below:

(i) Collection of Data: It is the first step in statistical investigation. Collection of data means assembling for the purpose of particular investigation which are not available in published sources.

(ii) Organisation of Data: Organising of data involves three steps which are (a) Editing of data (b) Classification of data according to some common characteristics and (c) Tabulation.

(iii) Presentation of Data: Presentation of data means presenting the collected data in the form of diagram and graph for better understanding.

(iv) Analysis: After collection, organisation and presentation, data are analysed. Analysis of data means obtaining the desired information from the data so collected.

(v) Interpretation: The last stage is interpretation which is a difficult task and requires a high degree of skill.

Q.8. What is classification? Mention its essentials.

Ans: Classification of Data: The process of arranging the data in groups or classes according to their common characteristics is technically known as classification. Classification is the grouping of related facts into classes. It is the first step in tabulation.

In the words of Secrist, “Classification is the process of arranging data into sequences and groups according to their common characteristics or separating them into different but related parts.”

Essentials of classification

  1. The classification must be exhaustive so that every unit of the distribution may find place in one group or another.
  2. Classification must conform to the objects of investigation.
  3. All the items constituting a group must be homogeneous.
  4. Classification should be elastic so that new facts and figures may easily be adjusted.
  5. Classification should be stable. If it is not so and is changed for every enquiry then the data would not fit for an enquiry.
  6. The data must not overlap. Each item of the data must be found in one class. 

Q.9. What are various types of classification of data? Mentions merits of classification.                2016

Ans: Data can be classified on the following four bases:

a) Geographical

b) Chronological

c) Qualitative

d) Quantitative

Merits of classification:

a) It facilitates comparison of data.

b) It focuses mainly on important data and unnecessary data are dropped out.

c) It enable statistical treatment of the material collected.

Q.10. What is tabulation? Mention its objectives, merits and limitations.

Ans: Tabulation: Tabulation refers to the systematic arrangement of the information in rows and columns. Rows are the horizontal arrangement. In simple words, tabulation is a layout of figures in rectangular form with appropriate headings to explain different rows and columns. The main purpose of the table is to simplify the presentation and to facilitate comparisons. According to Neiswanger, “A statistical table is a systematic organisation of data in columns and rows.”

The principal objectives of tabulation are stated below:

(i) To make complex data simple: When data are arranged systematically in a table, such data become more meaningful and can be easily understood.

(ii) To facilitate comparison: When different data sets are presented in tables it becomes possible to compare them.

(iii) To economize space: A statistical table furnishes maximum information relating to the study in minimum space.

(iv) To make data fit for analysis and interpretation: Tabulation serves as a link between the collection of data on the one hand and analysis of such data on the other. In other words, after tabulating the data, it becomes possible to find out their averages, dispersion and correlation. Such statistical measures are necessary for their interpretation.

(v) To provide reference: A statistical table can be used as a source of reference for other studies of similar nature.

Importance of Tabulation are stated below:

  1. Tabulation makes the data brief. Therefore, it can be easily presented in the form of graphs.
  2. Tabulation presents the numerical figures in an attractive form.
  3. Tabulation makes complex data simple and as a result of this, it becomes easy to understand the data.
  4. This form of the presentation of data is helpful in finding mistakes.
  5. Tabulation is useful in condensing the collected data.
  6. Tabulation makes it easy to analyze the data from tables.
  7. Tabulation is a very cheap mode to present the data. It saves time as well as space.
  8. Tabulation is a device to summaries the large scattered data. So, the maximum information may be collected from these tables.

Tabulation suffers from the following limitations:

  1. Tables contain only numerical data. They do not contain details.
  2. Qualitative expression is not possible through tables.
  3. Tables can be used by experts only to draw conclusions. Common men do not understand them properly.

Q.11. What are various parts of the table?

Ans: In general, a statistical table consists of the following eight parts. They are as follows:

(i) Table Number: Each table must be given a number.

(ii) Title of the Table: Every table should have a suitable title.

(iii) Caption: Caption refers to the headings of the columns.

(iv) Stub: Stub refers to the headings of rows.

(v) Body: It contains a number of cells. Cells are formed due to the intersection of rows and column.

(vi) Head Note: The head-note contains the unit of measurement of data.

(vii) Foot Note: A foot note is given at the bottom of a table.

(viii)Source Note: The source note shows the source of the data presented in the table.

Q.12. What is Questionnaire? What are its essential characteristics?

Ans: Questionnaire: A Questionnaire is simply a list of questions in a printed sheet relating to survey which the investigators asks to the informants and the answers of the informants are noted down against the respective questions on the sheet.

Characteristics of an ideal Questionnaire:

(i) The Schedule of question must not be lengthy.

(ii) It should be clear and simple.

(iii) Questions should be arranged in a logical sequence.

(iv) The Units of information should be Cleary shown in the sheet.

Q.13. Define the term population and sample. What is sample and census survey? Distinguish between them. 2017

Ans: Population: Statistics is taken in relation to a large data. Single and unconnected data is not statistics. In the field of a statistical enquiry there may be persons, items or any other similar units. The aggregate of all such units under consideration is called “Universe or Population”.

Sample: If a part is selected out of the universe then the selected part or portion is known as sample. Sample is only a part of the universe.

Sample survey and Census Survey:

Sample survey: It is a survey under which only a part taken out of the universe is investigated. It is not essential to investigate every individual item of the Universe.

Census survey and complete enumeration: Under Census survey detail information regarding every individual person or item of a given universe is collected.

Difference between Census and Sample survey: The following are the differences between Census and Sample method of investigation:

(a) Under Census method, each and every individual item is investigated whereas under sample survey only a part of universe is investigated.

(b) There is no chance of sampling error in census survey whereas sampling error cannot be avoided under sample survey.

(c) Census survey is more time consuming and costly as compared to sample survey.

(d) Census survey is an old method and it less systematic than the sample survey.

Q.14. Mention the Merits and Demerits of Census and Sample Survey.                  2015

Ans: Merits and Demerits of Census:


(a) Since all the individuals of the universe are investigated, highest degree of accuracy is obtained.

(b)  It is more suitable if the field of enquiry is small.


(a) It the field of enquiry is too wide, it is not suitable.

(b) Collection of data is costly and time consuming.

Merits and Demerits of sample survey: (Merits of sampling over census)


(a) Time and labour are saved.

(b) It may also be collected from unpublished form.

(c) If secondary Data are available, they are much quicker to obtain than primary data.


(a) Degree of accuracy may not be acceptable. (b) Data may or may not fit the need of the project. (c) Data may be influenced by personal bias of investigator.

Q.15. What are various types of diagrams and graphs?

Ans: Types of diagrams and Graphs:

a) Simple Bar Chart

b) Multiple Bar Chart or Cluster Chart

c) Staked Bar Chart or Sub-Divided Bar Chart or Component Bar Chart

d) Simple Component Bar Chart

e) Percentage Component Bar Chart

f) Sub-Divided Rectangular Bar Chart

g) Pie Chart.

Types of Diagrams/Charts:

a) Histogram

b) Frequency Curve and Polygon

c) Lorenz Curve

d) Histogram

Q.16. Distinguish between diagrams and graphs. What are the uses and limitations of diagrams and graphs?

Ans: Difference Between Diagrams And Graphs:

1. A graph needs a graph paper but a diagram can be drawn on a plain paper.

2. As diagramsare attractive to look at, they are used for. Graphs on the other hand are more useful to statisticians and research workers for the purpose of further analysis.

3. For representing frequency distribution, diagrams are rarely used when compared with graphs. For example, for the time series graphs are more appropriate than diagrams.

Uses of Diagrams and Graphs:                   2017

Diagrams and graphs are extremely useful due to the following reasons:

(i) Information presented though diagrams and graphs can be understood easily just in a bird’s eye view.

(ii) Diagrams and graphs produce a greater lasting impression on the mind of the readers.

(iv) They facilitate ready comparison of data over time and space.

However, graphic and diagrammatic presentations have some limitations:

1. Unlike a table a diagram or a graph does not show the exact value of a variable.

2. Further, a limited set of facts can be presented through such devices like diagram and graph.

Q.17. What is Sampling? Mention it essentials. Mention its merits and demerits.                             2016

Ans: A Sample is that part of the universe which we select for the purpose of investigation. Sampling is the process of learning about the population on the basis of sample drawn from it. In sampling technique only a part of the universe is studied instead of every unit of the universe.

Characteristics of the sampling technique (Essentials of a Good sampling)

  1. Representative: The sample should truly represent the characteristics of the verse.
  2. Adequacy: The size of the sample should be adequate.
  3. Homogeneity: There should be homogeneity in the nature of all the units selected.
  4. Independent ability.

Advantages of sampling

  1. Very accurate.
  2. Economical in nature.
  3. Very reliable.

Disadvantages of sampling

  1. Inadequacy of the samples.
  2. Chances for bias.
  3. Problems of accuracy.

Q.18. What are its various types? Explain them.

Ans: Some of the most common types of random sampling methods are:

(1) Simple random sampling,

(2) Systematic sampling,

(3) Stratified sampling, and

(4) Cluster sampling.

Simple random sampling ensures that each possible sample has an equal probability of being selected, and each item in the entire population has an equal chance of being included in the sample.

In systematic sampling the items are selected from the population at a uniform interval defined in terms of time, order or space.

In stratified sample the entire population is divided in relatively homogeneous group.

In cluster sampling the population is divided into groups or clusters, a sample of these clusters may be drawn.

Q.19. What are various types of Statistical errors?

Ans: Types of Statistical errors: 1] Sampling errors 2] Non-sampling errors

Sampling Errors: The results derived from a sample study may not be exactly equal to the true value in the population because estimates are based on a part and not on the whole population. Sampling gives rise to these errors which are known as sampling errors.

Non-Sampling Errors: When a complete enumeration of units is made, it is sure that data will be free from errors. Errors arises in case of complete enumeration are called non-sampling errors.


Part A: Introductory Micro Economics

Introduction to Micro Economics

Consumer Behaviour and Demand

* Law of Demand

* Elasticity of Demand

Producer Behaviour and Supply

* Laws of Return to Scale

Forms of Market and Price Determination:

* Monopoly 

* Perfect Comptetition

* Monopolistic Competition

Simple Applications of Tools of Demand & Supply

Part B: Statistics for Economics

Introduction to Statistics

Collection, Organisation and Presentation of Data

Statistical Tools & Interpretation 

* Measure of Central Tendency

* Dispersion

* Index Number

Correlation analysis

Summary Notes of Statistics for Economics available here

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