Most top research agencies use SPSS to analyze survey data and mine text data so that they can get the most out of their research and survey projects. In addition to the four programs mentioned above, SPSS also provides solutions for data management, which allow researchers to perform case selection, create derived data, and perform file reshaping.
SPSS also offers data documentation, which allows researchers to store a metadata dictionary. This metadata dictionary acts as a centralized repository of information pertaining to the data, such as meaning, relationships to other data, origin, usage, and format.
Thanks to its emphasis on analyzing statistical data, SPSS is an extremely powerful tool for manipulating and deciphering survey data. SAV format makes the process of pulling, manipulating, and analyzing data clean and easy.
Using the. SAV format, SPSS automatically sets up and imports the designated variable names, variable types, titles, and value labels, making the process much easier on researchers.
Once survey data is exported to SPSS, the opportunities for statistical analysis are practically endless. In the mids they introduced the first mainframe statistical package to appear on a personal computer.
SPSS Inc. In , Nie felt that it was time to turn over the day-to-day management of the Company to new leadership. Hull remained on the development side of the business where he is still currently involved in the development of SPSS and other key technologies. The Company strengthened its leadership in the analytical marketplace through acquisitions that expanded the depth and breadth of its analytical offerings. While customers and their industries vary, they share a common need to gather insight from the analysis of data.
The Company's analytical technology from its early beginnings has enabled organizations to learn from the past, understand what is happening today and anticipate the future in order to manage it effectively. Bent, distribute tapes of source code to a small, but enthusiastic, user community, while maintenance and enhancement was done by the original authors.
During this start-up phase, the business was organized and a number of development initiatives were undertaken. The business was focused on statistical products, and the acquisition strategy complemented this direction by bringing in other statistical products companies, such as SYSTAT and Jandel SPSS played a thought-leadership role in the emergence during of predictive analytics as an important, distinct segment within the broader business intelligence software sector.
Predictive analytics complements and enhances other information technologies. Organizations that employ predictive analytics not only know what has happened, they also know what is likely to happen next. Most importantly, they know what to do about it by using this knowledge to increase revenue, reduce costs, and improve outcomes.
SPSS saw a growing awareness of these benefits among the commercial, public sector, and academic organizations its serves. To enhance it focus on predictive analytics, SPSS acquired Dutch-based DataDistilleries, a provider of predictive analytic applications in November of Nie, then a year-old Ph. The application Nie was trying to use was created for biologists, not social scientists. With that in mind, Nie took detailed notes about what he needed in a software application and enlisted the help of Dale H.
Bent, a fellow doctoral candidate whose background was in operations research, to design a file structure. Once the manual was available in college bookstores, demand for the program took off. Nie, Bent, and Hull received a royalty from sales of the manual but nothing from distribution of the program. Mainly for that reason, Nie and Hull incorporated their operation.
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