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How to operate data decentralized SPSS

Publish: 2021-04-15 06:49:25
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. 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
3. Subtract the mean from each number
4. The factor is obtained by factor analysis, which is done in data reconciliation factor
5. Standardize the data, find out the mean and variance
analysis description statistics description, and then select "save standardized score as a variable" and confirm to get the processed standardized data, and then cluster, factor and regression analysis can be carried out
6. 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.
7.

1. Open SPSS and switch the interface to variable view. Create observation index and type in editing column. The example creates two indicators, one as the independent variable and the other as the dependent variable, namely GPD and urbanization, representing the per capita GDP and urbanization level

8. 1. Input data
2. Menu analysis - description statistics - Description
3. In the pop-up dialog box, select the variable to be standardized into the variable box on the right
4. There is a check box to save the variable as the standardized score, check
5 and OK to get the calculation result, return to the data inspection and get the new standard score variable
9.

Anorexia improvement, fatigue improvement, liver pain improvement, abdominal distension improvement, each column of a chi square test, the results are 4 x2 and 4 P values. Take the improvement of anorexia as an example

The input data are as follows:

because the P values are greater than 0.05, it shows that the treatment has no significant effect on anorexia, fatigue, liver pain and abdominal distension

for reference only, good luck

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