Class 11 Economics (Statistics for Economics) Chapter 2 Collection of Data

Key Concept: Census vs Sample

c) A sample collects data from a subset of the population.

[Solution Description] A census involves collecting data from every individual within the entire population, providing comprehensive insights. In contrast, a sample collects data from a selected subset of the population, which is then used to infer information about the whole population.

Key Concept: Data Collection Methods

d) Online Surveys

[Solution Description] According to the syllabus, the three basic methods of data collection are Personal Interviews, Mailing Surveys, and Telephone Interviews. Online Surveys are not listed as a method.

Key Concept: Frequency of Census

b) Every 10 years

[Solution Description] The Census in India is conducted every 10 years. This decadal exercise provides detailed data on the country’s population and its characteristics.

Key Concept: Survey Methods

d) Online Chats

[Solution Description] The syllabus mentions personal interviews, mailing surveys, and telephone interviews as methods of data collection. Online chats are not mentioned.

Key Concept: Equal Chance

c) Ensuring equal selection probability for all units

[Solution Description] In random sampling, every individual in the population must have an equal probability of selection to eliminate bias.

Key Concept: Data Collection Methods

a) Personal Interviews

[Solution Description] Primary data is collected firsthand by researchers using methods like interviews and surveys.

Key Concept: Method Comparison, In-depth Analysis

b) Mailed questionnaires

[Solution Description] The study requires methods that allow observation of non-verbal cues, which are typically not possible with telephone interviews due to the lack of visual interaction. Personal interviews provide the opportunity to observe such cues, making them more suitable in this scenario.

Key Concept: Sampling Method

d) Random Sampling

[Solution Description] Random sampling is a method where each member of the population has an equal opportunity to be included in the sample, ensuring unbiased representation.

Key Concept: Random Number Tables

b) By selecting numbers at random from the table

[Solution Description] Random number tables are used to ensure the randomness of a sample selection process. To select a sample using a random number table, each member of the population must be assigned a unique number. Then, numbers are selected at random from the table. This ensures that every individual has an equal chance of being chosen, eliminating bias.

Key Concept: Leading Question

d) Do you agree that our product is the best?

[Solution Description] A leading question suggests how a respondent should answer, often by implying a particular response within the question itself. Option d) “Do you agree that our product is the best?” suggests agreeing with the statement.

Key Concept: Variable Application

d) All of the above

[Solution Description] In this scenario, the variables are factors that can change or have different values in the experiment. The type and amount of fertilizer used can vary, as well as the growth measured (height of plants). These represent variables in the study. Therefore, all these options combined reflect the variables in the context given.

Key Concept: Definition Recall

c) Judgment and convenience

[Solution Description] The primary basis for selecting samples in non-random sampling is judgment or convenience rather than random selection. This type of sampling does not give every unit an equal chance of being selected.

Key Concept: Non-Response Errors

b) An error caused by some people not participating in the survey

[Solution Description] Non-response errors occur when some individuals in the sample do not respond or cannot be contacted, leading to incomplete data collection from that portion of the sample.

Key Concept: Census vs. Sample

a) A census requires data collection from every individual in the population.

[Solution Description] A census involves collecting information from every member of the population, ensuring complete coverage and accuracy of data, whereas a sample survey collects information from only a subset of the population.

Key Concept: Source Identification

c) Census reports

[Solution Description] Secondary data is obtained from processed sources like reports, publications, journals, and records that have been previously compiled by others.

Key Concept: Primary Data

b) Data collected from a survey conducted by the researcher

[Solution Description] Primary data is collected directly by the researcher through methods like surveys or experiments.

Key Concept: Agency Identification

b) Labour Bureau

[Solution Description] According to the syllabus, the Labour Bureau is responsible for collecting data on employment and unemployment in India.

Key Concept: Data Source Evaluation

b) Time-consuming

[Solution Description]

Primary data collection can be more accurate and relevant since it is collected directly for the specific research purpose. However, a significant disadvantage is that collecting primary data tends to be more time-consuming and expensive compared to using existing secondary data.

Key Concept: Sampling Bias

d) Sampling bias

[Solution Description] This scenario describes sampling bias as it includes only gym-goers and excludes other individuals who may have different fitness habits. The sample is not representative of the entire population.

Key Concept: Errors in Data Acquisition

c) Data acquisition error

[Solution Description]

When different people measure the same object and record different measurements, this results in an error in data acquisition. This happens because of variability in data collection processes, leading to inconsistent data.

Key Concept: Collection Methods

c) Personal interview

[Solution Description] The personal interview is a method where the researcher interacts face-to-face with the respondents to collect data.

Key Concept: Basic Comparison

c) It is based on convenience or judgment

[Solution Description]

Non-random sampling differs from random sampling in that it does not give all units in the population an equal chance of being selected; instead, selection is based on certain criteria like convenience or judgment.

Key Concept: Pilot Survey Purpose

c) To pre-test the questionnaire

[Solution Description] A pilot survey is conducted to pre-test the questionnaire. This helps in identifying any shortcomings or issues in the questions and allows for improvements before the full survey is launched.

Key Concept: Definition Recall

d) It is a subgroup representing the entire population

[Solution Description] A sample is a smaller group selected from the population, used to infer information about the whole. It is representative of the population and typically smaller than it.

Key Concept: Application Scenario

d) Mailing Questionnaire Surveys

[Solution Description] Mailing questionnaire surveys are particularly suitable for reaching respondents spread across various locations because they do not require physical presence or travel, which may not be feasible in remote areas.

Key Concept: Mode of Data Collection

c) Mailing Surveys

[Solution Description] Mailing surveys are suitable for reaching a wide audience across large geographical areas without needing face-to-face interaction, making them cost-effective and efficient for widespread distribution.

Key Concept: Sampling Techniques

c) Stratified Sampling

[Solution Description] Stratified Sampling is a technique where the population is divided into different ‘strata’ or groups based on a characteristic, and random samples are then taken from each group. This ensures representation across key subgroups within the population.

Key Concept: Source Identification

b) Experimentation

[Solution Description]

Primary data is data collected directly from the original source. An experiment is a direct way of collecting new data firsthand.

Key Concept: Question Order

a) How often do you use public transportation?

[Solution Description] The question order in a questionnaire typically moves from general to specific. Hence, the most general question should be placed first.

Key Concept: Sampling Error

a) The discrepancy between estimated sample value and true population value

[Solution Description] Sampling error is the difference between a sample estimate and the actual population parameter.

Key Concept: Agency Function

b) Collecting and disseminating statistical data

[Solution Description] The Central Statistics Office (CSO) primarily functions to provide statistical services, such as compiling national accounts statistics, conducting economic censuses, and other socio-economic data collection.

Key Concept: Purpose of Sampling

a) To reduce cost and time

[Solution Description] Samples are used in research to reduce cost and time because studying an entire population can be very costly and time-consuming. By taking a representative sample, researchers can make inferences about the whole population.

Key Concept: Agency Identification

c) Directorate General of Commercial Intelligence and Statistics (DGCI & S)

[Solution Description] The Directorate General of Commercial Intelligence and Statistics (DGCIS) is assigned the responsibility of collecting and publishing trade statistics in India.

Key Concept: Concept Identification

c) Error due to non-response

[Solution Description] Non-response errors are not considered sampling errors as they occur due to individuals not responding or being unreachable, which does not directly affect the difference between sample estimates and population parameters.

Key Concept: Primary vs. Secondary Data

c) Primary Data

[Solution Description]

Primary data refers to information gathered directly by researchers through various means such as surveys, experiments, or observations specifically for their research purpose. This contrasts with secondary data, which is pre-existing data collected by others.

Key Concept: Sampling Error Analysis, Non-sampling Error Identification

c) Non-sampling error due to coverage issues.

[Solution Description]

Sampling errors occur when a sample is not representative of the population. In this case, excluding certain demographics leads to bias:

1. If specific groups are omitted, this creates a coverage error—a type of non-sampling error.

2. Coverage errors result from the survey design where certain sections of the population don’t have an equal chance of being selected.

This bias is likely caused by non-sampling error due to coverage issues in how the sample was drawn.

Key Concept: Leading Question Identification

b) Don’t you think our new product is amazing?

[Solution Description]

A leading question suggests its own answer, usually steering the respondent toward a particular response. In this case, Option b includes a suggestion that might influence the respondent’s answer by implying a positive quality about the product.

Key Concept: Leading Question

b) Are you satisfied with your salary despite many employees feeling underpaid?

[Solution Description] A leading question suggests an answer that the person being asked may feel compelled to provide. Option B suggests that people are generally dissatisfied with their salaries.

Key Concept: Error Type Recognition

c) Non-response error

[Solution Description] Non-response error occurs when individuals in the sample do not respond or cannot be contacted.

Key Concept: NSS Data Release

c) Reports and the journal ‘Sarvekshana’

[Solution Description] The NSS releases its data through official reports and the journal ‘Sarvekshana’, providing detailed insights into socio-economic conditions.

Key Concept: Comparison of Methods

c) Telephone Interviews

[Solution Description] Telephone interviews provide quick responses because data is gathered in real-time during the call. However, they lack personal contact since there’s no face-to-face interaction.

Key Concept: Source Type

b) Secondary Data

[Solution Description] Data published by a government agency that has been processed and presented in reports is referred to as secondary data. This is because it was collected by someone other than the user and involves interpretations or analyses provided by external sources.

Key Concept: Census Definition

b) A complete enumeration of a population

[Solution Description] A census is a complete enumeration of a population, which means it involves collecting data from every member of the population.

Key Concept: Agency Identification

c) Census of India

[Solution Description] The Census of India is responsible for conducting demographic surveys every ten years. These surveys collect data on population size, density, sex ratio, literacy, migration, and rural-urban distribution.

Key Concept: Comparative Analysis

c) 2.16%

[Solution Description] The average annual growth rate is calculated by finding the difference between the populations at two points in time and dividing by the number of years, then converting it to a percentage. Let’s assume $P_{1991} = 846387888$ and $P_{2001} = 1028737436$.

Growth Rate = $\left(\dfrac{P_{2001} – P_{1991}}{P_{1991}}\right) \times \dfrac{1}{10} \times 100$

$Growth Rate = \left(\dfrac{1028737436 – 846387888}{846387888}\right) \times \dfrac{1}{10} \times 100 \approx 2.16%$

Key Concept: Basic Definition

c) To conduct nationwide socio-economic surveys

[Solution Description] The primary purpose of the National Sample Survey Organisation (NSSO) is to conduct nationwide socio-economic surveys for collecting data on various aspects like literacy, employment, and consumer expenditure among others.

Key Concept: Data Collection Methods

c) Personal Interview

[Solution Description] Personal interviews involve direct, face-to-face interaction between the interviewer and the respondent, making it a primary data collection method.

Key Concept: Data Sources

d) Central Statistics Office

[Solution Description] The Central Statistics Office (CSO) is a national level agency in India responsible for collecting, processing, and tabulating statistical data related to various economic and social aspects.

Key Concept: Error Source Analysis

a) A telephone survey conducted at an inconvenient time for respondents

[Solution Description] Non-response errors occur when individuals in the sample cannot be contacted or refuse to respond. In this scenario, if participants are not available or unwilling during a phone survey, it can lead to non-response errors.

Key Concept: Census Method Understanding

b) Every ten years

[Solution Description] A census in India is conducted every ten years to achieve a complete enumeration of the population.

Key Concept: Data Type Distinction

c) Primary data

[Solution Description] Telephone interviews involve gathering firsthand information from participants and hence are classified as primary data.

Key Concept: Basic Definition

b) A survey that includes every element of the population

[Solution Description] A Census or Complete Enumeration refers to a survey that includes every element of the population, rather than just a sample.

Key Concept: Sampling vs Census

b) Cost-effectiveness

[Solution Description] The primary advantage of a sample survey is its cost-effectiveness and time efficiency compared to a census, which involves surveying every individual in the population.

Key Concept: Scenario Application

c) Interviewing a small group of key stakeholders for an in-depth analysis

[Solution Description] Personal interviews are ideal when detailed and in-depth data collection is required, and when direct personal contact can lead to more comprehensive responses from the respondent.

Key Concept: Non-Sampling Error Sources

b) Mistakes made during data entry and recording responses.

[Solution Description] Non-sampling errors can arise from data acquisition mistakes, non-response issues, or biases in selection processes. They are unrelated to the process of selecting the sample itself but rather involve inaccuracies in collecting or processing data.

Key Concept: Purpose and Use

c) To plan developmental policies

[Solution Description] The Census of India provides demographic data that are critical for government policy-making. These data help in understanding population size, density, sex ratio, literacy rates, migration patterns, and rural-urban distribution, which forms the basis for planning and development strategies.