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KNN means k-nearest neighbors (KNN). KNN imputation method seeks to impute the values of the missing attributes using those attribute values that are nearest to the missing attribute values.

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saketh varma

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4y ago

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How do I deal with missing data in SPSS?

To deal with missing data in SPSS: Identify the missing data patterns in your dataset. Decide on an appropriate missing data handling strategy (e.g., deletion, imputation). For listwise deletion, go to "Data" > "Select Cases" and choose "Exclude cases listwise." For pairwise deletion, no specific action is needed in SPSS as it is the default option. For imputation, go to "Transform" > "Missing Value Analysis" and select the desired imputation method (e.g., mean substitution, regression imputation). Analyse your data after applying the chosen missing data handling strategy. If you need professional SPSS help for issues with the software, then you can get professional help also. You can find multiple online platforms providing services regarding SPSS software and different data analysis techniques.


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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.