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Decentralization of SPSS variables

Publish: 2021-04-20 16:48:16
1. According to Hou Jietai: the so-called centralization refers to subtracting the mean value of a variable from its expected value. For sample data, each observation value of a variable is subtracted from the sample average value of the variable, and the transformed variable is centralized
for your question, subtract the mean from each measurement.
2. Centralization is to subtract the mean and Z-score is to divide it by the standard deviation. Both of them are centralization methods.
3. In fact, when describing statistics, check the Save option to get a standardized variable. The space is limited. You can take a look at this tutorial. http://jingyan..com/article/9f7e7ec04ee5c56f28155416.html
4. Subtract the mean from each number
5. Yes, subtract the mean value of the cases corresponding to the project
and then use the data after centralization to do regression, instead of centralization and aggregation
6.

The purpose of centralization is to unify the units, that is, to unify the dimensions, because the units of different variables are different, which will cause the errors of various statistics

first calculate the average value of variables

in this way, the work of centralizing variables is completed

7. There are several methods, here are the two most commonly used, one is to subtract the average, one is the Z-score
subtract the average value: first perform a description statistics to get the descriptive statistical results, with the average and standard deviation. Then use the compute command to create a new variable = original variable average
the Z-score is similar to the above result, except that the new variable is divided by the standard deviation to get a score

the question is your description: a variable has multiple items. What does that mean? I can't think of it.
8. 1. The dependent variable does not need to be centralized
2. The first step is for the independent variables to enter the regression equation; The second step is that independent variables and regulatory variables enter together; The third step is that the independent variable, regulatory variable and interaction item enter together
3. The adjustment variables were divided into high and low groups, and the regression analysis of independent variables and dependent variables was done. Then the influence coefficient of high and low groups of independent variables on dependent variables was compared, and the slope test was carried out
9. Yes, that's right
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