Given the following data table: Which of the following data editing methods is the best to use to make the data usable for analysis?

The correct answer is D. Imputation. Imputation is the process of replacing missing or incomplete values (e.g., "N/A") in a dataset with meaningful values, such as the mean, median, or mode of the column. In this case, imputation is necessary to handle the missing values in the "Temperature" and "Count" columns…

Data Governance, Quality, and Controls

Question

Given the following data table:

Which of the following data editing methods is the best to use to make the data usable for analysis?

Exhibit

Options

AConcatenation
BNormalization
CTransposition
DImputation

How the community answered

(34 responses)

A
3% (1)
B
3% (1)
D
94% (32)

Explanation

Imputation is the process of replacing missing or incomplete values (e.g., "N/A") in a dataset with meaningful values, such as the mean, median, or mode of the column. In this case, imputation is necessary to handle the missing values in the "Temperature" and "Count" columns, ensuring that the data becomes usable for analysis without introducing biases or gaps.

Topics

#Data preprocessing#Missing data#Imputation#Data quality

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