Additional power supply device (abbreviation of Supplementary Power Supply Set)
General usage. SPSS is very easy to use, so it is most easily accepted by beginners. It has a clickable interactive interface, and you can use the drop-down menu to select the command to be executed. It also has a way to learn its "syntax" language by copying and pasting, but these syntax are usually very complicated and not very intuitive.
Data management. SPSS has a user-friendly data editor similar to Excel, which can be used to input and define data (missing values, numerical values).
Sign, etc. It is not a powerful data management tool (although SPS
1 1 version adds some commands to add data files, with limited effect). SPSS is also mainly used to operate a single file, so it is difficult to handle multiple files at the same time. Its data file has 4096 variables,
The number of records is limited by disk space.
Statistical analysis. SPSS can also do most statistical analysis (regression analysis, logistic regression, survival analysis, analysis of variance, factor score).
Multivariate analysis). Its advantages lie in variance analysis (SPSS can test many special effects) and multivariate analysis (multivariate variance analysis, factor analysis, discriminant analysis, etc. ), SPSS 1 1.5 version.
The function of mixed model analysis is also added. Its shortcomings are that there is no robust method (robust regression can not be completed or robust standard deviation can be obtained) and there is a lack of survey data analysis (SPSS 12 adds a module to complete part of the process).
Block).
Drawing function. The interactive interface of SPSS drawing is very simple. Once the graph is drawn, you can modify it by clicking it as needed. This kind of graphics is of high quality.
Ok, and you can also paste it into other files (Word
Documents or Powerpoint, etc. ). SPSS also has programming statements for drawing, but it can't produce some interactive interface drawing effects. This statement is more difficult than Stata statement, but simpler than SAS statement.
Single (less functional).
SPSS software video tutorial
To sum it up. SPSS is committed to simplicity (its slogan is "real statistics, real simplicity") and has achieved success. But if you are an advanced user, you will lose interest in it over time. SPSS is a strong hand in cartography. Due to the lack of robust investigation methods, dealing with the statistical process at the forefront is its weakness.
Stata
General usage. Stata is popular with beginners and advanced users for its simplicity and powerful functions. When using, you can only enter one command at a time (suitable for beginners), or you can enter multiple commands at a time through a Stata program (suitable for advanced users). In this way, even if there is an error, it is easier to find and correct it.
Data management. Although Stata is not as powerful as SAS in data management, it still has many powerful and simple data management commands, which can
Enough to make complex operations simple. Stata is mainly used to manipulate one data file at a time, and it is difficult to process multiple files at the same time. With the introduction of Stata/SE, there are now Stata data files.
The number of variables in the file can reach 32,768, but when a data file exceeds the allowable range of computer memory, you may not be able to analyze it.
Statistical analysis. Stata can also do most statistical analysis (regression analysis, logistic regression, survival analysis, variance analysis, factor analysis)
Analysis and some multivariate analysis). Stata's greatest advantages may lie in regression analysis (including easy-to-use regression analysis feature tools) and logistic regression (with explanations).
Logistic regression result program, which is easy to be used for ordered and multivariate logistic regression). Stata also has a series of good robust methods, including robust regression, robust standard deviation regression and
Other commands that contain reliable standard miscalculations. In addition, in the field of survey data analysis, Stata has obvious advantages and can provide regression analysis, logistic regression, Poisson regression, probability regression and other surveys.
Data analysis. Its shortcomings lie in variance analysis and traditional multivariate methods (multivariate variance analysis, discriminant analysis, etc.). ).
Drawing function. Just like SPSS, Stata can provide some interactive interfaces for commands or mouse clicks to draw. Unlike SPSS, it has no charts.
Shape editor. Among the three softwares, its drawing command syntax is the simplest, but its function is the most powerful. The graphic quality is also very good, which can meet the requirements of publishing. In addition, these charts have played a very good role in supplementing statistical analysis.
Functions, for example, many commands can simplify the production of scatter plot in the process of regression discrimination.
Stata software video tutorial
To sum it up. Stata is a good combination of simple use and powerful functions. Although it is easy to learn, its functions in data management and many cutting-edge statistical methods are still very powerful. Users can easily download other people's existing programs, or write them themselves, and make them closely integrated with Stata.
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General usage. SAS is very popular with advanced users because of its powerful functions and programmability. It is also based on this that it is one of the most difficult softwares to master. When using SAS, it is necessary to write a SAS program to process and analyze data. If there is an error in the program, it is difficult to find and correct it.
Data management. SAS is very powerful in data management. It allows you to handle your data in any possible way. It contains SQL (structure
Query language), SQL queries can be used in SAS datasets. But it takes a long time to learn and master the data management of SAS software. In Stata or SPSS, many complicated tasks have been completed.
The commands used in data management are much simpler. However, SAS can handle multiple data files at the same time, which makes this work very easy. It can handle 32,768 variables as well as your hard disk.
The maximum number of records allowed by disk space.
Statistical analysis. SAS can perform most statistical analysis (regression analysis, logistic regression, survival analysis, analysis of variance, factor analysis,
Multivariate analysis). The advantages of SAS may lie in its variance analysis, mixed model analysis and multivariate analysis, while its disadvantages are mainly ordered and multivariate logistic regression (because these commands are very
Difficult), and robust methods (it is difficult to complete robust methods such as robust regression). Although it supports the analysis of survey data, it is still quite limited compared with Stata.
Drawing function. Among all statistical software, SAS has the most powerful drawing tool, which is provided by SAS/Graph module. However, the learning of SAS/Graph module is also very professional and complicated, and the graphic production mainly uses programming language. Although SAS 8 can draw interactively by clicking the mouse, it is not as simple as SPSS.
SAS software video tutorial
To sum it up. SAS is suitable for advanced users. Its learning process is hard, and the initial stage will be frustrating. However, due to its powerful data management and the function of processing a large number of data files at the same time, it is still favored by advanced users.
comprehensive assessment
Every software has its own uniqueness, and it is difficult to avoid its own weaknesses. Generally speaking, SAS, Stata and SPSS are a set of tools that can be used for various statistical analysis. get through
Stat/Transfer can convert different data files in a few 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 mix
To analyze the model, you can choose SAS；; For logistic regression, Stata is selected; If you want to analyze variance, the best choice is of course SPSS. If you often make statistical scores,
Analysis, it is strongly recommended that you collect the above software into your toolkit for data processing.