Questionnaire Design & Survey Sampling Methods

1. What Is a Questionnaire?

A Questionnaire is a formalized set of questions designed to collect facts, opinions, and behavioral data from respondents to achieve the objectives of a statistical study.

2. Essential Qualities of an Ideal Questionnaire

Designing an effective questionnaire is both a science and an art. An ideal questionnaire must satisfy the following golden criteria:

7 Golden Principles of Questionnaire Design

1. Limited Number of Questions

Keep it short (12–18 questions). Lengthy questionnaires cause respondent fatigue and abandonment.

2. Simple, Clear & Unambiguous

Avoid complex vocabulary, double negatives, or vague phrases like 'regularly' or 'often'.

3. Logical & Sequential Flow

Start with easy, non-threatening questions (demographics), progressing logically to specific opinions.

4. Avoid Leading / Biased Questions

Never suggest the desired answer (e.g., Don't ask: 'Don't you agree that our brand is superior?').

5. Avoid Personal / Sensitive Questions

Questions regarding exact salary, political opinions, or private habits must be optional or categorized into broad ranges.

6. Cross-Check Questions

Include verification questions (e.g., Date of Birth and Age in completed years) to detect falsified answers.

7. Pre-Testing (Pilot Survey)

Always test the questionnaire on 10–15 sample respondents first to iron out confusing questions before full rollout.

3. Practical Activity 1: Ready-to-Use College Student Questionnaire

Theme: Survey on Daily Screen Time & Online Shopping Habits of BBA Students in Indore

CAMPUSNOTES STUDENT RESEARCH QUESTIONNAIRE
Project: "Digital Habits and E-Commerce Consumption among BBA Undergraduates"
(All responses will remain completely confidential and used strictly for academic research)

Section A: Demographic Profile
1. Full Name (Optional): _________________________
2. Gender: [ ] Male   [ ] Female   [ ] Prefer not to say
3. College / Department: ________________________
4. Semester: [ ] Sem 1   [ ] Sem 2   [ ] Sem 3   [ ] Sem 4   [ ] Sem 5   [ ] Sem 6

Section B: Mobile & Screen Time Habits
5. What is your average daily smartphone screen time?
   [ ] Less than 2 hours   [ ] 2 to 4 hours   [ ] 4 to 6 hours   [ ] More than 6 hours
6. Which app category consumes the majority of your daily mobile usage?
   [ ] Social Media (Instagram, Snapchat)   [ ] Study & Notes (CampusNotes, YouTube)
   [ ] Gaming                              [ ] OTT Streaming (Netflix, Hotstar)

Section C: Online Shopping Behavior
7. How frequently do you purchase goods online (Amazon, Flipkart, Myntra, Blinkit)?
   [ ] Weekly   [ ] Monthly   [ ] Once in 2-3 months   [ ] Rarely / Never
8. What is your typical monthly online spending budget?
   [ ] Below ₹500   [ ] ₹500 - ₹1,500   [ ] ₹1,500 - ₹3,000   [ ] Above ₹3,000
9. Which payment method do you trust the most?
   [ ] UPI (PhonePe, GPay, Paytm)   [ ] Cash on Delivery (COD)   [ ] Credit/Debit Card
10. What is the single biggest factor influencing your purchase decision?
    [ ] Heavy Discount / Price   [ ] Brand Reputation   [ ] Fast 10-Minute Delivery   [ ] Customer Reviews

4. Census vs. Sampling Method

When collecting data, a researcher must decide between studying every individual or studying a subset:

Parameter	Census Method (Complete Enumeration)	Sample Method (Partial Enumeration)
Meaning	Every single unit in the population is investigated.	Only a representative fraction of the population is studied.
Scope	Complete universe (100% population).	Representative subgroup (e.g., 5% to 10%).
Cost & Budget	Huge financial cost and logistics.	Highly economical and cost-effective.
Time Required	Very slow; takes months or years.	Fast; results obtained in days or weeks.
Feasibility	Impossible when testing destroys the item (e.g., testing bullet firing or bulb lifespan).	The only feasible choice when testing is destructive.
Standard Example	National Decennial Population Census by Government of India.	Exit polls, Nielsen TV ratings, Quality testing batches.

5. Types of Sampling Methods

Sampling methods are broadly classified into two major categories:

Classification of Sampling Techniques

A. Probability (Random) Sampling

Every unit has a known, non-zero mathematical probability of being selected. Eliminates researcher bias.

1. Simple Random Sampling: Lottery method or random number generator.

2. Stratified Random Sampling: Dividing heterogeneous population into homogeneous strata (e.g., Year 1, Year 2, Year 3 students) and drawing random samples from each.

3. Systematic Sampling: Selecting every kth item from an ordered list (e.g., every 10th student roll number).

4. Cluster / Multistage Sampling: Dividing large population into geographic clusters (city wards) and sampling entire clusters.

B. Non-Probability (Non-Random) Sampling

Units are selected based on researcher discretion, convenience, or subjective judgment.

1. Convenience Sampling: Choosing respondents who are easiest to reach (e.g., interviewing friends sitting in the college canteen).

2. Judgment / Purposive Sampling: Handpicking experts who possess specialized insight (e.g., interviewing senior fund managers for stock market research).

3. Quota Sampling: Setting fixed demographic quotas (e.g., exactly 50 boys and 50 girls), but filling quotas non-randomly.

4. Snowball Sampling: Existing respondents refer their contacts (useful for rare or hidden groups).

Questionnaire Design & Survey Sampling Methods | BBA Notes