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11
MISSING VALUES
Sometimes you don't have all of the fields or variables associated with a record or observation. Or, you may allow your respondents to not answer, or to answer with "not applicable".
You always want to code any "non-answers" and tell SPSS that these should be treated as missing data. This will make SPSS ignore those values in any analysis.
Example: Eye Color
1 = blue, 2 = green, 3 = brown, 4 = hazel, 5 = other
96 = Not applicable
99 = Missing
Both 96 and 99 should be designated as MISSING VALUES.
SPSS also uses the "DOT" to represent SYSTEM-MISSING values. These will always be treated as missing without any special designation. Leaving a field blank when entering data will treat it as missing.
You always want to code any "non-answers" and tell SPSS that these should be treated as missing data. This will make SPSS ignore those values in any analysis.
Example: Eye Color
1 = blue, 2 = green, 3 = brown, 4 = hazel, 5 = other
96 = Not applicable
99 = Missing
Both 96 and 99 should be designated as MISSING VALUES.
SPSS also uses the "DOT" to represent SYSTEM-MISSING values. These will always be treated as missing without any special designation. Leaving a field blank when entering data will treat it as missing.
Flashcard info:
Author: CoboCards-User
Main topic: Statistics
Topic: SPSS
School / Univ.: University of Rochester
City: Rochester
Published: 08.03.2014