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Imputation is used when specific data is not available. If data is not received, imputation is used to make an estimate of what the received data would have been.

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Q: What does imputation mean in statistics analysis?
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How do I handle missing data in SPSS?

To handle missing data in SPSS and to perform SPSS data analysis for better outcomes, you have a few options. Firstly, you can choose to delete cases with missing data entirely, which may be appropriate if the missing data is minimal and randomly distributed. Alternatively, you can use list wise deletion, which removes cases with missing data for any variable involved in the analysis. Another option is to replace missing values using techniques like mean imputation (replacing missing values with the mean of the variable) or regression imputation (predicting missing values based on other variables). Additionally, you can utilise advanced methods like multiple imputation or maximum likelihood estimation to handle missing data more comprehensively. The choice of method depends on the nature and extent of missing data, as well as the assumptions of your analysis.


How do I deal with missing data in SPSS?

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