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SPSS prediction

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Can you help me with SPSS prediction? I have a dataset containing 16 variables and I need to use at least 3 SPSS methods that can predict quantitative (2 methods) and logic (0,1) variable. It’s very important for my research paper!

1 comment to SPSS prediction

  • Afroze

    A prediction is a forecast about what will be happened in future which is used in SPSS research. By statistical prediction in SPSS research, we can predict the outcome overtime which can help us in policy making and planning for possible development. In SPSS research, this prediction can be easily done by regression. There are several regression methods and it is easy to do in SPSS research.

    Before set any regression model, SPSS researcher needs to concern about two things. One is Linearity and the second one is normality. If the variables follow these two assumptions, then you can click Analyze, then Regression, then Linear options respectively. After that you should have choose x and y variables and then check the option “Save”. After that, you need to check “mean” and “individual” under “Prediction intervals” by default it captures 95% confidence interval option. Then click “continue” and then “OK”. If prediction is for those x values which are not included in the sample data, you can add that x as additional values to the data file. However, you must leave the y value blank; otherwise these values will be treated as part of the data set and used for model fitting. Furthermore you can do logistic regression; it is a special type of prediction model which can allow the target variables as a categorical variable (0, 1). This binomial regression model has some benefits like it makes use of several predictor variables that may be either numerical or categorical. In SPSS research, binary logistic regression, sometimes called binomial logistic regression, is under Analyze, then Regression, then Binary Logistic. And the multinomial version is under Analyze, then Regression, then Multinomial Logistic. And finally, for checking error of the model, you should rely on the model’s F-statistic, significance, or multiple-r. These kinds of techniques can help you to cross validate of your model in SPSS research.

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