Tiêu đề SAMPLING TECHNEQUE WITH ANSWER.pdf ✅

20 MCQs on Sampling Techniques Instructions: Choose the best answer for each question. Q1. Which of the following is the primary goal of sampling in research? a) To collect data from every element in the population. b) To reduce the cost and time of data collection. c) To ensure absolute accuracy in research findings. d) To avoid any type of bias in the study. Solution: The correct answer is B) To reduce the cost and time of data collection. Explanation Explanation: While accuracy and bias reduction are important considerations in sampling, the fundamental purpose of sampling is to make research feasible when studying an entire population is too costly, time-consuming, or impossible. Sampling allows researchers to gather data from a smaller, manageable subgroup and generalize findings to the larger population. Q2. A researcher wants to study the prevalence of smartphone usage among university students in a specific city. She randomly selects 10 universities and then surveys all students within those selected universities. What type of sampling technique is this? a) Simple Random Sampling b) Stratified Random Sampling c) Cluster Sampling d) Systematic Sampling Solution: The correct answer is C) Cluster Sampling. Explanation Explanation: In cluster sampling, the population is divided into groups (clusters), and a random sample of these clusters is selected. All members within the selected clusters are then surveyed. Here, universities are the clusters, and all students within the chosen universities are included. Q3. Which sampling technique requires a complete and updated list of all individuals in the population (sampling frame)? a) Snowball Sampling b) Quota Sampling c) Simple Random Sampling d) Convenience Sampling Solution: The correct answer is C) Simple Random Sampling. Explanation Explanation: Simple random sampling involves selecting individual units from a complete list (sam- pling frame) of the population, where each unit has an equal chance of being selected. Techniques like snowball, quota, and convenience sampling do not necessarily require a comprehensive sampling frame. Q4. A professor wants to survey students in his class about their preferred learning methods. He decides to stand at the classroom door and survey every 5th student who enters. What type of sampling is he using? a) Quota Sampling b) Systematic Sampling c) Stratified Random Sampling 2
d) Purposive Sampling Solution: The correct answer is B) Systematic Sampling. Explanation Explanation: Systematic sampling involves selecting elements from a list or sequence at a fixed, periodic interval (e.g., every nth person). In this case, ”every 5th student” defines a systematic interval. Q5. Which of the following statements is true about Simple Random Sampling (SRS)? a) It requires dividing the population into meaningful subgroups. b) Each element has an equal and known chance of being selected. c) It is only suitable for very large and geographically dispersed populations. d) The selection of one element influences the selection of others. Solution: The correct answer is B) Each element has an equal and known chance of being selected. Explanation Explanation: By definition, Simple Random Sampling ensures that every member of the population has an equal probability of being selected. It does not involve dividing into subgroups (that’s stratified) or large geographic areas (that’s cluster), and the selection of one element does not influence others (assuming sampling with replacement, or with replacement conceptually for the odds of any single draw). Q6. A researcher divides the population of a city into different income groups (e.g., low, middle, high) and then selects a proportional number of individuals from each group randomly. Which sampling technique is being used? a) Cluster Sampling b) Stratified Random Sampling c) Convenience Sampling d) Snowball Sampling Solution: The correct answer is B) Stratified Random Sampling. Explanation Explanation: Stratified random sampling involves dividing the population into non-overlapping subgroups (strata) based on shared characteristics (like income groups), and then randomly selecting samples from each stratum. This ensures representation from all important subgroups. Q7. What is the primary reason for using stratified sampling over simple random sampling? a) To make the sampling process faster and cheaper. b) To ensure representation from diverse subgroups and potentially reduce sampling error. c) To allow for non-probability selection of participants. d) To simplify the construction of the sampling frame. Solution: The correct answer is B) To ensure representation from diverse subgroups and potentially reduce sampling error. Explanation Explanation: Stratified sampling is used when the population is heterogeneous and contains distinct subgroups that are relevant to the study. By ensuring proportional (or disproportional) representation from each stratum, it can lead to more precise estimates of population parameters and lower sampling error compared to SRS, especially if variability within strata is less than variability between strata. Q8. Which of the following scenarios is best suited for using Snowball Sampling? 3