Data sets commonly include observations with missing values for one or more variables. In some cases missing data naturally occur; these are called .....

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Question [CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]

Data sets commonly include observations with missing values for one or more variables. In some cases missing data naturally occur; these are called ____

A	legitimately missing data
B	data cleansing
C	illegitimate missing data
D	missing random data

Explanation:

Detailed explanation-1: -Imputation means replacing a missing value with another value based on a reasonable estimate. You use other data to recreate the missing value for a more complete dataset.

Detailed explanation-2: -These are data that are missing completely at random. That is, the missingness is independent from the data. There is no discernible pattern to this type of data missingness. This means that you cannot predict whether the value was missing due to specific circumstances or not.

Detailed explanation-3: -Expert-Verified Answer The missing data adds ambiguity to the data. It is represented as NA or NAN. If the dataset is small then every data point counts. The missing data creates imbalance in the observations and can even lead to invalid conclusions.

Detailed explanation-4: -In some cases missing data naturally occur; these are called. illegitimately missing data. In other cases missing data occur for different reasons; these are called. Missing completely at random (MCAR)

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