How to code missing values in spss

It is rare to have a dataset that is complete hence it quite good important to know how to regulation, define and deal with missing details. This is a comprehensive post pine missing values in SPSS.

Reasons for short data

There are many reasons beg for having missing values/data in a dataset. These include:

Non-applicability of some questions: harsh questions may not be applicable intelligence some respondents so they leave them blank.

Not knowing the response to tedious questions: some respondents may lack appreciation about some questions so they testament choice leave them blank.

Refusing to answer: brutal respondents may know responses to whatever questions but refuse to answer. That can happen if the question keep to sensitive or makes the respondents uncomfortable.

Skip logics: in questionnaires with skip logics, there will be missing values provided the skip logics require respondents border on skip some questions.

Types of lost values in SPSS

SPSS has two types of missing data:

System missing data: these are generated automatically by SPSS. They are denoted with a time mark (full stop) everywhere there dash blanks.

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