Economics: Class 11 (Part 2) — Chapter 2: Collection of Data

A Variable is a characteristic that can take different values (e.g., food grain production, income). It is typically represented by letters like $X$, $Y$, or $Z$. Each specific value of a variable is called an Observation.

• Primary Data: Data collected by an investigator first-hand through direct enquiry or survey. It is original in character.
• Secondary Data: Data that has already been collected, processed, and tabulated by some other agency (e.g., government reports, websites, books).

• Should not be too long; questions should be kept to a minimum.
• Should be easy to understand, avoiding ambiguous or difficult words.
• Questions should move from general to specific.
• Questions should be precise and clear, avoiding double negatives (e.g., "Don't you think...").
• Should not be leading questions that bias the respondent.

• Closed-ended (Structured) Questions: These can be two-way (Yes/No) or multiple-choice. They are easy to use, score, and analyze, but can restrict respondents' choices.
• Open-ended (Unstructured) Questions: These allow for individualized, detailed responses but are difficult to interpret and score.

A Pilot Survey (or pre-testing) is a try-out of the questionnaire with a small group before the actual survey. It helps identify shortcomings, assess question suitability, and estimate the time and cost of the main survey.

A Census is a survey that includes every element of the population. In India, the Census is carried out every ten years to collect demographic data (birth/death rates, literacy, employment, etc.).

• Population (Universe): The totality of items under study possessing certain characteristics.
• Sample: A smaller, representative group or section selected from the population to provide information.

• Random Sampling: Every individual unit in the population has an equal chance of being selected (e.g., Lottery Method, Random Number Tables). It is unbiased.
• Non-Random Sampling: Units are selected based on judgment, convenience, or quota. Not every unit has an equal chance of selection, introducing potential bias.

A Sampling Error is the difference between the sample estimate and the actual population parameter.

Sampling errors can be minimized by increasing the sample size.

These are more serious than sampling errors and cannot be easily minimized by increasing sample size. They include:

• Sampling Bias: Occurs when the sampling plan excludes certain parts of the target population.
• Non-Response Errors: Occurs when selected respondents cannot be contacted or refuse to respond.
• Errors in Data Acquisition: Arise from recording incorrect responses, measurement differences, or transcription mistakes.