Distinguish between Cluster sampling and Multi-stage sampling. In order to find out the incidence of Malnutrition among rural households in a given distinct, how would you collect the data by multi-stage sampling? Illustrate.

Cluster Sampling vs. Multi-stage Sampling:

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1. Cluster Sampling:

• Definition: Involves dividing the population into clusters (groups) and randomly selecting entire clusters for inclusion in the study.
• Process: Randomly select clusters, then include all individuals within the selected clusters in the sample.
• Advantages: Cost-effective, especially when clusters are geographically concentrated. It simplifies data collection logistics.

1. Multi-stage Sampling:

• Definition: A more complex sampling method that involves multiple stages of sampling. It combines various sampling techniques in a hierarchical structure.
• Process: Involves selecting clusters at the initial stage and then randomly selecting subgroups or individuals within those clusters in subsequent stages.
• Advantages: Allows for a more nuanced and detailed representation of the population. It can be adapted to various study designs.

Collecting Data on Malnutrition Among Rural Households using Multi-stage Sampling:

1. Stage 1 – Selection of Primary Sampling Units (PSUs):

• Identify distinct regions within the given district as primary sampling units (PSUs), such as villages or townships.
• Randomly select a predetermined number of PSUs to represent the entire district.

1. Stage 2 – Selection of Secondary Sampling Units:

• Within each selected PSU, identify clusters, which could be specific neighborhoods or communities.
• Randomly select a subset of clusters from each chosen PSU.

1. Stage 3 – Selection of Tertiary Sampling Units:

• Within each selected cluster, identify individual households.
• Randomly select households from each cluster for data collection.

1. Data Collection:

• Design a survey questionnaire or checklist to assess malnutrition indicators.
• Train fieldworkers to administer the survey and collect anthropometric measurements.
• Collect data on household demographics, socio-economic status, and dietary habits.

1. Analysis:

• Analyze the collected data using appropriate statistical methods to determine the incidence of malnutrition.
• Consider stratification based on socio-economic factors, demographics, or other relevant variables.

1. Reporting:

• Present findings, including the overall incidence of malnutrition and any significant variations within different clusters or stages.

By employing a multi-stage sampling approach, this method allows for a comprehensive understanding of malnutrition in the given district while considering the diversity within the population. It ensures that the sample is representative of the entire population while allowing for efficient data collection.