How to adjust the calculation of effect decentralization

1. Decentralized computing, also known as decentralized computing, allocates hardware and software resources to each indivial workstation or office. In contrast, centralized computing exists when most functions are performed, or is obtained from remote centralized locations. Distributed computing is a trend in modern business environment. This is contrary to the centralized computing popular in the early days of computer. The distributed computer system has many advantages over the traditional centralized network. The development of desktop computers is so rapid that their potential performance far exceeds the requirements of most commercial applications. This causes most desktop computers to remain idle (relative to their full potential). Decentralized systems can use the potential of these systems to maximize efficiency.

2. 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.

3.

Center

1. Click "start" in the menu bar above word

2. Select the words you want to put in the middle

3. Click the center alignment in "paragraph"

4. This process of decentralization is very painful.

5.

If you can't sell it, you can only keep it by yourself. Let's wait for appreciation or take over. Of course, the probability of this happening is very small. If it happens, there may be the following possibilities:

1. China, the United States or the European Union suddenly announced the ban on bitcoin and its circulation

2. Bitcoin exposes fatal weaknesses and defects, which are difficult to overcome, especially security factors

3. Bitcoin has not been used as a killer for a long time, and its application scenarios are strictly limited, so people graally lose information about bitcoin

4. The emergence of a better alternative to bitcoin or the global joint issue of a virtual currency has won global recognition

6. Cloudleopard network, technology can be trusted

7. Please help me. I'm sure I'll give you the most. He had a car accident. Could it be the cause of hyperopia? How to correct it Hello! First of all, I wish your nephew good health! Let me tell you something about

8. The relationship between Y and X is described by regression coefficient a + cm, which is a linear function of M, and C measures the moderating effect, When the independent variable is a category variable and the regulatory variable is also a category variable, the analysis of variance of two factor interaction effect is used, and the interaction effect is the regulatory effect; When the regulatory variable is continuous, the independent variable uses pseudo variable, centralizes the independent variable and regulatory variable, and does the hierarchical regression analysis of y = ax + BM + CXM + e: 1. Do the regression of y to X and m to get the measurement coefficient r 12.2, do the regression of y to x, m and XM to get r 22, if R 22 is significantly higher than R 12, then the regulatory effect is significant; When the independent variable is a continuous variable, the regulating variable is a category variable. Grouping regression: group according to the value of M, and do the regression of y to X. if the difference of regression coefficient is significant, then the regulating effect is significant. When the regulating variable is a continuous variable, do the hierarchical regression analysis of y = ax + BM + CXM + E, Independent variable is latent variable; When the moderator is a category variable, the group structural equation analysis is done. The method is to limit the regression coefficients of the two groups of structural equations to be equal, and get one χ Then we remove this restriction, re estimate the model and get another one χ 2 and the corresponding degrees of freedom χ 2 minus the following χ 2 get a new one χ 2, the degree of freedom is the difference between the degrees of freedom of the two models χ If the test result is statistically significant, the moderating effect is significant; There are many different analysis methods when both the regulatory variable and the independent variable are latent variables. The most convenient one is the unconstrained model proposed by marsh, Wen and Hau. 3. The definition of the intermediate variable is the influence of the independent variable x on the dependent variable y. if x affects y by influencing the variable m, then M is called the intermediate variable. Y = CX + E1, M = ax + E2, y = C ′ x + BM + E3, When there is only one mediating variable, there is C = C ′ + AB between the effects, and the size of the mediating effect is measured by C-C ′ = ab. 4. Mediating effect analysis method mediating effect is indirect effect, no matter whether the variables involve latent variables or not, we can use structural equation model to analyze the mediating effect, If C is not significant and y has no significant correlation with X, the mediating effect analysis will be stopped. If C is significant, the second step will be carried out; The second step is to test a and B once. If they are all significant, then test C ′, C ′, and the mediating effect is significant. If C ′ is not significant, then the complete mediating effect is significant; If at least one of a and B is not significant, do Sobel test, significant mediating effect is significant, not significant mediating effect is not significant, ^5. The comparison between moderator and mediator moderator m moderator m research purpose when does x affect y or when does x have a greater impact? How does x affect the moderating effect, interaction effect, mediating effect of y-related concepts When the influence of X on y is considered, the influence of strong x on y is strong and stable. The typical model is y = am + BM + CXM + e, M = ax + E2, y = C ′ x + BM + E3. The position of m in the model is x, M is in front of Y, M can be in front of X, the function of m after X and before y affects the direction (positive or negative) and strength of the relationship between Y and X. x influences the relationship between Y, m and X, X and X through it The correlation between M and X, y can be significant or not (the latter is ideal) the correlation between M and X, y is significant effect regression coefficient C regression coefficient proct AB effect estimate ^ C ^ A ^ B effect test whether C is equal to zero, AB is equal to zero test strategy do hierarchical regression analysis, test the significance of partial regression coefficient C (t test); 6. SPSS operation method of mediating effect and moderating effect. First, descriptive statistics, including M SD and internal consistency reliability (a) are used. Second, all variables are correlated, including statistical variables and hypothetical x, y, y, The independent variable and m should be centralized first, that is, subtracting their respective mean 1. Now, input m (regulatory variable or intermediary variable), y dependent variable, and demographic variable related to any of the independent variable, dependent variable, and M regulatory variable into independent 2 Then press next to input the independent variable of X (the intermediate variable ends here). 3. To do the analysis of the adjustment variable, we should also input the opportunity of X and m in next for further regression. The test mainly depends on whether f is significant

9. The mediating and moderating effects can be realized by hierarchical regression in SPSS, that is, in which dialog box of multiple linear regression analysis, there is a
Block dialog box, you can move the independent variables and moderating variables to which dialog box one by one, and the regression results will show the changes of moderating effects