Practice Data Preparation and Cleaning - 5.6.1 | Module 5: Empirical Research Methods in HCI | Human Computer Interaction (HCI) Micro Specialization
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is data transcription?

πŸ’‘ Hint: Think about how we make raw data usable in statistical software.

Question 2

Easy

Why is error checking important in data preparation?

πŸ’‘ Hint: Consider what happens if mistakes go unnoticed.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the first step in data preparation?

  • Data Cleaning
  • Data Entry
  • Data Analysis
  • Data Visualization

πŸ’‘ Hint: Think about how data starts its journey in research.

Question 2

True or False: Imputation is always a better method than exclusion when dealing with missing data.

  • True
  • False

πŸ’‘ Hint: Consider when each method may be appropriate.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You have a dataset with 30% of its values missing. Discuss how you would evaluate the impact of this missing data on your research conclusions.

πŸ’‘ Hint: How does the missingness relate to the study design?

Question 2

Analyze the effect of outliers on a linear regression model and suggest a method for addressing them.

πŸ’‘ Hint: What methods exist that minimize the influence of outliers?

Challenge and get performance evaluation