DA Data Cleaning and Preparation

Question 1

What is the most common method for handling missing numeric values in a dataset?

Accepted Answer

Replace with the column mean, median, or mode

Answer

Imputing missing values with the mean, median, or mode preserves dataset size and is a standard starting point for handling missingness.

Question 2

What is data normalization?

Accepted Answer

Scaling numeric values to a common range such as 0 to 1

Answer

Normalization rescales features to a standard range so that no single feature dominates due to its magnitude.

Question 3

Which of the following best describes an outlier?

Accepted Answer

A value significantly different from the rest of the dataset

Answer

An outlier is a data point that lies far outside the typical range of values and can skew analysis results.

Question 4

What does data deduplication mean?

Accepted Answer

Identifying and removing duplicate records

Answer

Deduplication removes redundant rows that represent the same entity, preventing double-counting in analysis.

Question 5

What is a data type mismatch issue?

Accepted Answer

When a column stores values in an incorrect format for its intended data type

Answer

A data type mismatch occurs when values are stored in the wrong format, such as dates stored as strings, causing calculation errors.

DA - Data Analyst Practice Test