Decentralize all variables

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. Subtract the mean from each number

3. Not necessarily, centralization is only for the convenience of explanation, and does not affect the regression coefficients Central treatment of regulatory effect of South Heart Network

4. Only iron pick can dig ore and water in the mine cave. It's better to bring some wood and a fire into the mine cave. You can only knock round stones by the river to have a small chance to proce iron ore. The Iron pick is not useful for iron ore. It's the same to decide what equipment you wear. The iron spear and crossbow must be available, and then according to the cold and hot conditions of the mine cave you want to go to at that time

5. 1. The dependent variable does not need to be centralized; 2. The first step is that the independent variable enters 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;

6. The so-called centralization refers to subtracting the mean value of a variable from its expected value
for sample data, subtracting the sample average value from each observation value of a variable, the transformed variable is centralized.

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. The significance of data centralization and standardization in regression analysis is to eliminate the errors caused by different dimensions, self variation or large difference in values. Data standardization refers to subtracting the mean value from the value and then dividing it by the standard deviation; Centralization refers to subtracting the mean value of a variable.

9. 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.