Stata variable decentralization command

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. 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.

The cost of mining equipment is mainly mining equipment cost, electricity cost, time cost (technology network cost is ignored)

I. mining equipment cost

with the popularity of bitcoin, more and more people join in mining, and the difficulty of mining also increases. Mining equipment is also developed from ordinary computer to professional mining machine, and mining machine cost fluctuates, If the currency price is high, the cost will be high, and if the currency price is low, the cost will be lower

and the prices of bitcoin machines with different models and parameters are also different. At present, the well-known bitcoin machines on the market are ant S9 and Shenma m3. The current price of bitcoin is 50000, and the cost is less than 10000

Electricity cost and technical management electricity cost is also a very important cost for mining. The power consumption of bitcoin mining machine is relatively large, which will inevitably proce a large amount of electricity cost when the mining machine is running 24 hours, while the cost of household electricity is relatively high, so the current trend of mining is transformed into the centralized mining of large mines, Generally, the electricity price will be lower and cheaper than that at home, and the mine has professional technicians to solve certain technical problems

if you want to know more about the mining field, please send me a private message

if you want to know more about the mining field, you can send me a private message

6. 显示居中，大多用于文本显示的选项这是一个选项
justification(justificationstyle) specifies how the text is to be "horizontally" aligned
in the box. Choices include left, right, and center. Think of the textbox as being
horizontal, even if it is vertical when specifying this option.

7. First of all, we need to know why we need to do Vif. Variance expansion factor is used to test multicollinearity, and multicollinearity is not a problem that must be solved. Only when you are interested in the coefficients of variables with multicollinearity, you need to deal with it. For example, among the four variables x1, X2, X3 and x4, X1 and X2 have multicollinearity. If you are only interested in the coefficients of X3 and x4, you can ignore them. That is to say, as long as the Vif values of X3 and X4 do not exceed 10. Just input Vif directly.

8. 2006-08-07 11:22 strategically using general purpose Statistics Packages: a look at Stata, SAS and SPSS. It can be thought that each software has its own unique style, has its own advantages and disadvantages. This paper makes an overview of this, but it is not a comprehensive comparison. People often have a special preference for the statistical software they use. I hope most people can agree that this is a real and fair comparative analysis of these software. SAS general usage. SAS is very popular with advanced users because of its powerful function and programmability. Based on this, it is one of the most difficult software to master. When using SAS, you need to write SAS program to process data and analyze. If an error occurs in a program, it will be difficult to find and correct it. Data management. SAS is very powerful in data management. It allows you to process your data in any possible way. It contains SQL (Structured Query Language) process, which can be used in SAS dataset. But it takes a long time to learn and master the data management of SAS software. In Stata or SPSS, the commands used to complete many complex data management tasks are much simpler. However, SAS can process multiple data files at the same time, making this work easier. It can handle 32768 variables and the maximum number of records allowed by your hard disk space. Statistical analysis. SAS can do most statistical analysis (regression analysis, logistic regression, survival analysis, ANOVA, factor analysis, multivariate analysis). The advantages of SAS may lie in its ANOVA, mixed model analysis and multivariate analysis, while its disadvantages are mainly ordered and multivariate logistic regression (because these commands are difficult), and robust methods (it is difficult to complete robust regression and other robust methods). Although it supports the analysis of survey data, the comparison with Stata is still quite limited. Drawing function. Among all the statistical software, SAS has the most powerful drawing tool, which is provided by SAS / graph mole. However, the learning of SAS / graph mole is also very professional and complex, and the proction of graphics mainly uses programming language. SAS 8 can draw interactively by clicking the mouse, but it is not as simple as SPSS. Summary. SAS is suitable for advanced users. Its learning process is hard, and the initial stage can be frustrating. However, it is still a powerful data management and processing a large number of data files at the same time, which is favored by advanced users. Stata is generally used. Stata is popular among beginners and advanced users for its simplicity and powerful functions. When using, you can only input one command at a time (suitable for beginners), or you can input multiple commands at a time through a Stata program (suitable for advanced users). In this way, even if errors occur, it is easier to find out and correct them. Data management. Although Stata's data management ability is not as powerful as SAS, it still has many powerful and simple data management commands, which can make complex operations easier. Stata is mainly used to operate one data file at a time, so it is difficult to process multiple files at the same time. With the introction of Stata / SE, the number of variables in a Stata data file can reach 32768, but when a data file exceeds the range allowed by computer memory, you may not be able to analyze it. Statistical analysis. Stata can also perform most statistical analysis (regression analysis, logistic regression, survival analysis, ANOVA, factor analysis, and some multivariate analysis). Stata's greatest advantages may lie in regression analysis (it contains easy-to-use regression analysis feature tools) and logistic regression (it has additional proceres to explain the results of logistic regression and is easy to be used for ordinal and multivariate logistic regression). Stata also has a series of good robust methods, including robust regression, robust standard error regression, and other commands including robust standard error estimation. In addition, Stata has obvious advantages in the field of survey data analysis, which can provide regression analysis, logistic regression, Poisson regression, probability regression and other survey data analysis. Its disadvantages lie in the analysis of variance and traditional multivariate methods (multivariate analysis of variance, discriminant analysis, etc.). Drawing function. Just like SPSS, Stata can provide some commands or mouse click interface for drawing. Unlike SPSS, it has no graphical editor. Among the three kinds of software, its syntax of drawing command is the simplest, but its function is the most powerful. The quality of graphics is also very good, which can meet the requirements of publishing. In addition, these figures play a very good role in supplementing statistical analysis. For example, many commands can simplify the making of scatter diagram in the process of regression discrimination. Summary. Stata realizes the combination of easy to use and powerful function. Although it is easy to learn, it is very powerful in data management and many frontier statistical methods. Users can easily download other people's existing programs, or write their own, and make it closely combined with Stata. General usage of SPSS. SPSS is very easy to use, so it is most accepted by beginners. It has a clickable interactive interface, and can use the drop-down menu to select the command to be executed. It also has a way to learn its "syntactic" language by ing and pasting, but these syntax are usually very complex and not very intuitive. Data management. SPSS has a friendly data editor similar to excel, which can be used to input and define data (missing values, numeric labels, etc.). It is not a powerful data management tool (although some commands to enlarge data files have been added in SPS 11, its effect is limited). SPSS is also mainly used to operate on one file, which is not competent for processing multiple files at the same time. Its data file has 4096 variables, and the number of records is limited by your disk space. Statistical analysis. SPSS can also do most statistical analysis (regression analysis, logistic regression, survival analysis, ANOVA, factor analysis, multivariate analysis). Its advantages lie in ANOVA (SPSS can complete the test of many special effects) and multivariate analysis (multivariate ANOVA, factor analysis, discriminant analysis, etc.), and the mixed model analysis function is added in SPSS 11.5. Its disadvantages are that there is no robust method (unable to complete robust regression or get robust standard error), and lack of survey data analysis (spss12 version added a mole to complete part of the process). Drawing function. The interactive interface of SPSS drawing is very simple. Once you draw a graph, you can modify it by clicking as needed. The graphics are of excellent quality and can be pasted into other files (word documents or PowerPoint, etc.). SPSS also has programming statements for drawing, but it can't proce some effects of interactive interface drawing. This statement is more difficult than Stata statement, but simpler than SAS statement. Summary. SPSS is committed to simplicity (its slogan is "true statistics, true simplicity") and has been successful. But if you're an advanced user, you'll lose interest in it over time. SPSS is a strong hand in cartography. Due to the lack of robust and survey methods, it is weak to deal with the frontier statistical process. Overall evaluation each software has its own unique, but also inevitably has its weaknesses. In general, SAS, Stata and SPSS are a set of tools that can be used in a variety of statistical analysis. Through stat / transfer, different data files can be converted in seconds or minutes. Therefore, you can choose different software according to the nature of the problem you are dealing with. For example, if you want to analyze with a hybrid model, you can choose SAS; Stata was selected for logistic regression; If we want to do ANOVA, the best choice is SPSS. If you are often engaged in statistical analysis, it is strongly recommended that you collect the above software into your toolkit for data processing.

9. The coefficient of the interaction factor should be tested for the moderating effect. If the coefficient is significant, the moderating effect can be explained. Your model can be supported by literature

excluded variables
you should put two variables in the first sheet and three variables in the second sheet, and the regression method you choose is enter. But instead of putting variables in your order, SPSS adds all the variables you choose to the model and excludes the extra variables ring the first regression, so this table will appear. If you don't want this table to appear, you can do the regression twice. For the first time, put the center D, center h, and then put the result in the center D, center h, Center D multiplied by H. if you do it twice, you won't have it.