statistics blog: spss

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PSPP, A Free Alternative of SPSS, Free Download PSPP

PSPP is a free alternative software for SPSS.

It is a program for statistical analysis of sampled data. It is a Free replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions.
website for PSPP is http://www.gnu.org/software/pspp/pspp.html
PSPP-data-view

PSPP-data-view

PSPP-variable-view

Functional option

Output-view

The features of PSPP are follows:

Supports over 1 billion cases.
Supports over 1 billion variables.
Syntax and data files are compatible with SPSS.
Choice of terminal or graphical user interface.
Choice of text, postscript or html output formats.
Inter-operates with Gnumeric, OpenOffice.Org and other free software.
Easy data import from spreadsheets, text files and database sources.
Fast statistical procedures, even on very large data sets.
No license fees.
No expiration period.
No unethical “end user license agreements”.
Fully indexed user manual.
Free Software; licensed under GPLv3 or later.
Cross platform; Runs on many different computers and many different operating systems.

PSPP is particularly aimed at statisticians, social scientists and students requiring fast convenient analysis of sampled data.

For free download PSPP click here

For learn more, click here

How SPSS statistical package for the social sciences works

SPSS (Statistical Package for the Social Sciences)

Interfaces of SPSS

SPSS Versions and date of publishing

SPSS 15.0.1 – November 2006
SPSS 16.0.2 – April 2008
SPSS Statistics 17.0.1 – December 2008
PASW Statistics 17.0.3 – September 2009
PASW Statistics 18.0 – August 2009
PASW Statistics 18.0.1 – December 2009
PASW Statistics 18.0.2 – April 2010
PASW Statistics 18.0.3 – September 2010
IBM SPSS Statistics 19.0 – August 2010
IBM SPSS Statistics 20.0 – August 2011

How spss(statistical package for the social sciences) works

You always begin by defining a set of variables, and then you enter data for the variables to create a number of cases. For example, if you are doing an analysis of automobiles, each car in your study would be a case. The variables that define the cases could be things such as the year of manufacture, horsepower, and cubic inches of displacement. Each car in the study is defined as a single case, and each case is defined as a set of values assigned to the collection of variables. Every case has a value for each variable. Variables have types. That is, each variable is defined as containing a specific kind of number. For example, a scale variable is a numeric measurement, such as weight or miles per gallon. A categorical variable contains values that define a category; for example, a variable named gender could be a categorical variable defined to contain only values 1 for female and 2 for male. Things that make sense for one type of variable don’t necessarily make sense for another. For example, it makes sense to calculate the average miles per gallon, but not the average gender.

After your data is entered into SPSS — your cases are all defined by values stored in the variables — you can run an analysis. You have already finished the hard part. Running an analysis on the data is much easier than entering the data. To run an analysis, you select the one you want to run from the menu, select appropriate variables, and click the OK button. SPSS reads through all your cases, performs the analysis, and presents you with the output.

You can instruct SPSS to draw graphs and charts the same way you instruct it to do an analysis. You select the desired graph from the menu, assign variables to it, and click OK. When preparing SPSS to run an analysis or draw a graph, the OK button is unavailable until you have made all the choices necessary to produce output. Not only does SPSS require that you select a sufficient number of variables to produce output, it also requires that you choose the right kinds of variables. If a categorical variable is required for a certain slot, SPSS will not allow you to choose any other kind. Whether the output makes sense is up to you and your data, but SPSS makes certain that the choices you make can be used to produce some kind of result.

SPSS (Statistical Package for the Social Sciences)

Interfaces of SPSS

PSPP is a free alternative software for SPSS. Free Download

SPSS (Statistical Package for the Social Sciences)

SPSS is a comprehensive, interactive, general-purpose package for data analysis and it includes most routine statistical techniques. SPSS is a true Windows package being mouse-driven with movable, scalable windows, drop-down menus and dialog boxes. Underlying the graphical interface is a command language consistent with previous versions of the package. A very important and useful feature is the Data Editor, which can be used to enter, view or edit data. The Data Editor makes your data immediately visible so that you can see what you are dealing with. The package also has high-resolution graphics which are easily edited and an extensive help system.

On the other hand,

SPSS is a computer program used for survey authoring, data mining, text analytics, statistical analysis etc. SPSS (Statistical Package for the Social Sciences) was released in 1968, developed by Norman. SPSS is one of the widely used programs for statistical analysis in social science. SPSS manual is considered as “sociology’s most influential books”.
Some of the statistics function used in the base software is Descriptive Statistics: Cross tabulation, Frequencies, Explore and Ratio Statistics. Bivariate Statistics: Mean, t-test, ANOVA, Correlation. Prediction for numerical outcomes and prediction for identifying groups. Students who are struggling with these concepts can make use of SPSS Homework Help services.
The first version of SPSS was designed for batch processing and mainframes. Now the version 16.0 runs under Windows, Mac OS X and Linux. SPSS was developed IBM corporations. It runs on the JAVA platform.
SPSS is used widely in most of the industrial sectors. It is used by market researchers, health researchers, survey companies, government educational researchers, marketing organizations and others.

SPSS is probably one of the easiest major statistics package to use. It allows even inexperienced users to run complicated statistical analyses at the click of a few buttons. When you are at the PC you are in charge of the package and it will attempt to do whatever you ask it, whether your instructions are sensible or not! The adage of garbage in, garbage out applies! It is therefore essential that you get a good understanding of the commands that you need to use and what the results mean.

How SPSS statistical package for the social sciences works

Interfaces of SPSS

PSPP is a free alternative software for SPSS, Free Download

Interfaces of SPSS

Interfaces of SPSS:

More than one way exists for you to command SPSS to do your bidding. And you don’t have to choose one and stick with it — you can perform tasks using whichever of the four interfaces you prefer. You can use any of the four approaches to perform any of the SPSS functions, but which one is best for you depend, to an extent, on the task to be performed and which interface you prefer.

GUI (graphic user interface): SPSS has a windowing interface and commands can be issued by the mouse through menu selections that cause dialog boxes to appear. This is a fill-in-the-blanks approach to statistical analysis that guides you through the process of making choices and selecting values. The advantage of the GUI approach is that, at each step, SPSS will make sure that you enter everything necessary before proceeding to the next step. This is the preferred interface for those just starting out — and if you don’t do much with SPSS, this may be the only interface you ever use.

Syntax: This is the internal language used to command actions from SPSS. It was known as the command syntax of SPSS, hence its name. It is often referred to as the command language. You can write Syntax a command to directly command SPSS to do anything it is capable of doing. In fact, when you use menu and dialog box selections to command SPSS, you are actually generating Syntax commands internally that do your bidding. That is, the GUI is nothing more than the front end of a Syntax command-writing utility. Writing (and saving) command language programs are a good way to store processes that you expect to repeat. You can even grab a copy of the Syntax commands generated by the GUI and save them to be repeated later.

Python: This is a general-purpose language that has a collection of SPSS modules written for it, making it possible to write programs that work inside SPSS. It can be run with the Syntax language to command SPSS to perform statistical functions. One advantage of using Python is the fact that it is a modern language and gives you the power and convenience that come with languages today, including the ability to construct a more readable program. In addition, because it’s a general-purpose language, you can read and write data from other applications and from other files.

Scripts: The items that SPSS calls scripts are actually programs written in BASIC. This language is simple and many people are familiar with it. Also, a BASIC program can be written as an autoscript — a script that executes automatically when SPSS produces certain output.

SPSS (Statistical Package for the Social Sciences)

Data Analyst Career

Today there is an increasing demand for data analysts in the world job market. The demand for data analysts is very high all across the United States.

Qualifications for data analyst job:

To be an ideal candidate for the job of data analyst, you need to have knowledge and experience in analyzing the statistical data, and should be a graduate degree in any field related to statistics. You also need to be well versed in data analyze software like Excel, SAS, SPSS, and Minitab.

Skills for data analyst job:

Data analysis requires intensive research work. A data analyst should also have very strong problem solving skills. The main skill required by a data analyst is to extract information related to a topic from raw data. Therefore, you should possess abilities with reference to data mining, data mapping and data warehousing. Data tracking and identifying the trends and patterns in the marketplace are very important tools in the hands of a data analyst.

Statistical and mathematical knowledge is also required. You also need to have knowledge in specialized data management software, and should be able to analyze data statistically, and have the ability to generate reports, and audit and validate them. This will help to analyze the data accurately, which in turn will produce the report according to client requirements.

Other skills required are verbal and writing skills, along with data interpretation and presentation skills.

Work for a Data Analyst

A data analyst is a person who has to search for information related to the particular requirements of a client. Therefore, you must have the ability to question yourself in relation to the content of a topic. You then have to keep researching until an appropriate solution is found. You have to discover the source of the original data and be able to evaluate it.

You should be able to compare data statistically and provide appropriate solutions. Therefore, as a data analyst you have to refer to a large number of data sources and work on your reporting skills, so that you can present it in a simple and effective manner. You also have to audit the report, and the report has to be presentable and appealing to the client.

Job Titles:

Junior Data Analyst: A junior analyst searches for the appropriate data and provide sufficient material to be analyzed. They have to prepare statistical diagrams and flowcharts.

Senior Data Analyst: A senior analyst has to consult and communicate with the client. He/she has to prepare the final report and present it.

Data Analysis Project Manager: Duties include project organization and methodology. The project manager has to audit the reports and make sure that they fulfill the needs of the client

Since all these are specialized skills, which are in great demand in today's technological world, data analysts have high growth prospects. If you have the required qualifications and skills, and are keenly interested in pursuing a career in this field, then being a data analyst is a good option for you.