We must first of its profits. Speaking the truth they know everything, but when you want to start learning all kinds of retreat. Little do they know a good data analysis tool that lets you do more with less, and instantly improve learning efficiency.
Although the countless data analysis tools, together remain the same. It is nothing more than data acquisition, several aspects of data storage, data management, data computation, data analysis, data display and so on. And SAS, R, SPSS, python, excel are most frequently mentioned data analysis tools. So, these tools themselves in the end What are the characteristics of it?
Excel
Excel is a Microsoft Office suite of important components, it can handle a variety of data, statistical analysis and decision support operations, widely used in management, finance and economics fields statistics, finance and so on.
1, pivot function
Data show a perspective view 10 showing several variants reports, only Chuihuizhili. A novice, as long as careful using the wizard so-so 1-2 hours on the road.
2, statistical analysis
In fact, it included in the pivot function, but very unique, commonly used test methods get a key.
3, charting capabilities
It is almost a private work force Excel, and other programs hold a candle to commit suicide.
4, Advanced Filter
This is an advanced query functions provided by Excel, and the simple operation. Enjoy great value.
5, automatic summary function
Other programs have this feature, but Excel is simple and flexible.
6, advanced math
As long as one or two functions easy to get
SAS software
SAS is one of the world's largest software company, is a statistical analysis of the United States NORTH CAROLINA State University in 1966 to develop software. SAS data access, management, analysis and presentation organically integrated.
The main advantages are as follows:
1, powerful statistical method Qi, full, new
SAS provides a number of statistics from basic computing to a variety of experimental design analysis of variance, correlation and regression analysis process a variety of statistical analysis and multivariate analysis, including almost all of the latest analytical methods, its analysis of advanced technology, reliable. Realization of analysis done by procedure calls. Many processes while providing a variety of algorithms and options.
2, easy to use, flexible operation
SAS to a common data (DATA) to produce a data set step and then, in a different procedure call for various data analysis.
Its programming statements simple, short, usually only a few small statements to complete a number of complex operations, satisfactory results.
The results are given prompt output in a concise English, standardized and easy to understand statistical terms, with English and preliminary statistical basis can be.
Just tell the user SAS "what to do", without having to tell their "how to do."
While SAS is designed so that any SAS able to "guess" what the users do not have to tell it (that is, without setting), and can automatically correct some minor errors (for example, the DATA DATA statement spelled DATE, SAS will be assumed to be DATA continues to run, given only explanatory notes) in the LOG. Runtime error it gives the wrong reasons and ways to correct them as much as possible. Thus SAS statistical science, rigorous and accurate organically combined with the convenience of the user, which greatly facilitates the users.
3, provide online help function
The course of pressing the function key F1, you can get help information at any time, get a simple user guide.
R Software
R is a complete data processing, computing and graphics software systems.
The main advantages are as follows:
Data storage and processing system
Array of computing tools (its vector, matrix operations aspects particularly powerful)
Complete and coherent statistical analysis tools
Excellent statistical mapping function
Easy and powerful programming language: manipulate data input and output, enabling branches, loops, user-customizable features
R is a statistical software so much, might as well say that R is a mathematical computing environment, because R is not just to provide some statistical procedures, the user need only specify the database and a number of parameters can be carried out a statistical analysis.
R is the idea: it can provide integrated statistical tool, but a lot more is that it offers a variety of mathematical calculations, statistical calculation functions, so that users can be flexible data analysis, and even create new suits your needs statistical calculation method.
Similar language syntax of the surface C, but semantically languages variant function (functional programming language) and APL and Lisp and strong compatibility. In particular, it allows "computing language" in (computing on the language). This makes it possible to expression as a function of input parameters, and this approach is useful for plotting and statistical simulation.
R is a free free software, it has a UNIX, LINUX, MacOS and WINDOWS version is free to download and use. In the R to R homepage where you can download the installation program, a variety of plug-in applications and documents. In the Setup R contains only eight base module, other modules can be obtained by external CRAN.
SPSS
SPSS is the world's first statistical analysis software.
The main advantages are as follows:
Simple: very friendly interface, in addition to data entry and some command and a few other programs work to enter the keyboard to type, but most operations by dragging the mouse, click on the "menu", "button" and "dialog" to complete.
Programming Convenient: has the characteristics of fourth-generation language, tell the system what to do without telling what to do. As long as understand the principles of statistical analysis, proficient in a variety of algorithms without the need of statistical methods, statistical analysis to obtain the desired results. For common statistical methods, SPSS command statement, the vast majority of sub-commands and select options to complete the operation "dialog" in. Therefore, users do not need to spend a lot of time to remember a lot of commands, procedures, selection.
Powerful: a complete data entry, editing, statistical analysis and reporting, graphics production and other functions. 11 types 136 comes functions. SPSS provides a sophisticated statistical analysis of multivariate statistics to describe the simple, such as exploratory data analysis, descriptive statistics, contingency table analysis, two-dimensional correlation, rank correlation, partial correlation, ANOVA, non-parametric test, multiple regression, survival analysis, covariance analysis, discriminant analysis, factor analysis, cluster analysis, nonlinear regression, Logistic regression.
Data Interface: the ability to read multiple file formats and the output. For example, generated by dBASE, FoxBASE, FoxPRO * .dbf files, text editor software-generated ASCⅡ data file, Excel * .xls files, etc. can be converted into SPSS data file for analysis. SPSS graphical able to convert seven kinds of graphics files. The results can be saved as * .txt and html format.
Module combination: SPSS for Windows software is divided into several functional modules. Users can configure the actual needs and circumstances of the flexibility to choose according to their own computer analysis.
Targeted: SPSS for beginners, experts were proficient and those who are more applicable. And many groups only need to master a simple operation analysis, mostly in favor of SPSS.
Python
Python is an object-oriented, interpreted computer programming language. Python syntax is simple and clear, with rich and powerful library. It is often nicknamed glue language, the other language can make various modules (especially C / C ++) easily linked together.
One common application is the case, the use of Rapid Prototyping Python program (sometimes the final program interface), then some of which special requirements, a more suitable language rewriting, such as 3D graphics rendering module in the game, performance requirements are particularly high, it can be rewritten in C / C ++, and then packaged as Python be extended library call. Note that the platform may need to consider the issue when you are using extension libraries, some may not be available for cross-platform.
The main advantages are as follows:
Simple: Python is a simple language on behalf of ideology. Reading a good Python program feels almost like reading the same in English. It allows you to focus on solving the problem rather than the language itself.
To learn: Python is extremely easy to use, since Python has an extraordinarily simple documentation.
Speed: the underlying Python is written in C language, a lot of standard libraries and third-party libraries are written in C, runs very fast.
Free, open source: Python is one of FLOSS (free / open source software). Users can freely distribute copies of this software, read its source code, make changes to it, it's part of the new free software. FLOSS is based on the concept of sharing knowledge of a group.
High-level language: the Python programming language regardless of when the low-level details such as how to manage a class of memory used by your program.
Portability: Because of its open-source nature, Python has been ported on many platforms (changed to make it work on different platforms).
Explanatory: a such as C or C ++ programs written in compiled language can be converted from the source file (ie C or C ++) to the language (binary code ie 0 and 1) a computer you use. This process by the compiler and various flags and options. When running the program, the linker / loader software to copy your program from the hard disk into memory and run. Python, the program does not need to be compiled into binary code. You can run the program directly from the source code.
Inside the computer, Python interpreter converts the source code into an intermediate form called bytecode, then translates it into a machine language using the computer and run. This makes using Python much easier. Python also makes the program easier to transplant.
Object-Oriented: Python supports both process-oriented programming also supports object-oriented programming. In the "procedure-oriented" language, it is constructed from a program or process is simply a function of reusable code together. In the "object-oriented" language, the object program is a combination of data and functionality from the build up.
Scalability: If a critical section of code required to run faster or some desirable algorithms are not disclosed, may be part of a program written in C or C ++, and then use them in Python programs.
Embeddable: you can embed Python C / C ++ program, to provide script functionality to the user program.
Rich library: Python Standard Library is huge indeed. It can help deal with a variety of work, including regular expressions, documentation generation, unit testing, threading, databases, web browsers, CGI, FTP, email, XML, XML-RPC, HTML , WAV files, cryptography, GUI ( the graphical user interface), Tk, and other system-related operations. This is called Python's "fully functional" concept. In addition to the standard library, there are many other high-quality libraries such as wxPython, Twisted, Python Imaging Library and so on.
Specification code: the Python forced indented way that the code has better readability. Python, the program does not need to be compiled into binary code.
Tools are not a panacea, business and data modeling is the source of all Law. Do not be dazzled fans tool Oh!
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