Data Cleansing and Missing Data Quiz

What is the main goal of data cleansing?

• To delete irrelevant data

• To ensure data is accurate, consistent, and reliable

• To create duplicates of the data

• To remove outliers from the dataset

Which of the following best describes Missing Completely at Random (MCAR)?

• Data missing due to external reasons related to the data itself

• Data missing in a pattern linked to observed data

• Data missing without any identifiable pattern or reason

• Data missing due to systematic errors in collection

Outliers are:

• Data points that follow the same trend as the rest

• Data points that are duplicated in the dataset

• Data points that significantly differ from other observations

• Data points that are missing completely at random

What is a common issue when different data formats are used in a dataset?

• Outliers become more frequent

• The dataset becomes smaller

• Analysis can be inaccurate or fail entirely

• Data will automatically standardise

Which type of missing data is likely to occur due to a survey question that respondents prefer not to answer?

• Missing Completely at Random (MCAR)

• Missing at Random (MAR)

• Missing Not at Random (MNAR)

• Systematic Missing Data

Why are duplicates a significant problem in datasets?

• They provide too much data

• They skew analysis and results

• They increase the overall accuracy

• They improve data quality

Inconsistent data types (e.g., mixing text and numbers in a field) can cause issues because:

• It makes the dataset look messy

• It causes errors in calculations and analysis

• It results in more missing data

• It automatically corrects the data format

Which of the following describes Abnormal Trends in data?

• Data that contains duplicates

• Unusual patterns that differ from expected results

• Missing data that has been recovered

• Data that is consistently structured but incorrect

Why is addressing data quality issues important?

• To make datasets smaller and easier to handle

• To increase confidence in business decisions based on the data

• To ensure data is more readily available to everyone

• To remove unnecessary data permanently

What does data confidence refer to?

• The belief that data can be used without cleansing

• The reliance on data for analysis after it has been verified and cleansed

• The amount of data in a dataset

• The rate at which data is collected