Data Science · Intermediate level

Intermediate level · Module 1 of 6 · 15 guided hours

Data Collection and Survey Data

Design questionnaires and samples, collect data digitally and prepare survey data correctly, including weights.

Learning objectives

  • Design clear questionnaires and digital forms
  • Choose sampling designs and apply survey weights
  • Clean survey data with skip logic and coded responses

Topics

  • questionnaire design
  • digital collection with KoboToolbox or ODK
  • sampling designs
  • survey weights
  • skip logic and coded answers
  • data quality checks during collection

Lessons

  1. Lesson 1 Designing Questionnaires and Digital Forms

    Write clear, unbiased questions and build digital forms that prevent errors at the point of collection.

    question wordingresponse optionsvalidation constraintsskip logic

  2. Lesson 2 Sampling and Survey Weights

    Understand common sampling designs and why weights are needed to make survey estimates represent the population.

    stratified samplingcluster samplingsampling weightweighted estimate

  3. Lesson 3 Cleaning Survey Exports

    Prepare exported survey data: codes and labels, skipped questions, multiple-choice columns and quality checks.

    codes and labelsnot applicable vs missingselect-multiple columnsconsistency checks

Practical activity

Design a short digital questionnaire for a school attendance check, then clean a provided survey export and calculate weighted indicators.

Expected outcomes

  • Better data at the source
  • Correctly weighted survey estimates

Assessment

Questionnaire review and a practical on weighted versus unweighted estimates.

Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.