SPSS combined mean and decentralized processing
Publish: 2021-04-16 10:54:04
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.
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. Subtract the mean from each number
4. 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
and then use the data after centralization to do regression, instead of centralization and aggregation
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
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.
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. Yes, that's right
8. Why watch it? After data centralization, the mean value should be 0 and the standard deviation should be 1
analysis -- descriptive
statistics --- descriptive
analysis -- descriptive
statistics --- descriptive
9. The common Standardization (x-mu) / sqrt (delta)
centralization (x-mu)
Mu is the mean value and delta is the variance
centralization (x-mu)
Mu is the mean value and delta is the variance
10. It's wrong to say factor analysis downstairs. Factor analysis is because there are too many variables. In order to facilitate analysis, variables are merged. The two variables are not merged in this way. Here I don't understand whether the two problems mentioned by LZ refer to two variables. If so, the general liner model will be used. Then select the variables you want to integrate in the model, but not all variables can be directly combined in this way. Moreover, this model belongs to difference comparison and non-linear correlation analysis, which is only applicable to the case that the values of two variables are limited (i.e. nominal variables), such as gender, age group, region, etc“ The value of the variable is multiple-choice questions 1-5 "also did not understand what it means, this is a scoring question, right? In addition, I don't understand whether you want to do correlation analysis or regression analysis. Regression is a further processing based on correlation. You can use the multinomial logistic method in the region, which is similar to the general liner model.
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