Read this article to learn about:- 1. SPSS (Statistical Package for Social Sciences) Introduction and Uses 2. Use of SPSS 3. Overview.
SPSS (Statistical Package for Social Sciences) Introduction and Uses:
SPSS is a software package used for conducting statistical analyses, manipulating data, and generating tables and graphs that summarize data. Statistical analyses range from descriptive statistics, such as averages and frequencies, to advanced inferential statistics, such as regression models, analysis of variance, and factor analysis.
SPSS also contains several tools for manipulating data, including functions for recoding data and computing new variables as well as merging and aggregating datasets. SPSS also has a number of ways to summarize and display data in the form of tables and graphs.
SPSS is the most popular computer software for data analysis. The computer software provides a comprehensive set of flexible tools that can be used to accomplish a wide variety of data analysis tasks. SPSS is especially useful for social scientists and social science students, including scholars performing quantitative research and undergraduates working on their thesis? A more general guide is provided with the Windows version of SPSS.
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By using SPSS tutorial we can understand the steps of testing a simple research question like- Do voters? Opinions on how the president is handling the economy influence which party they will vote for in House elections? If a voter believes that the Democratic president is handling the economy poorly, for example, is she more likely to vote for the Republican House candidate?
We can divide this research question into two variables. The dependent variable, or the variable we are trying to explain, is the vote in House elections. The independent variable, or the variable that is supposed to be influencing the dependent variable, is voter opinion on how the president is handling the economy.
However, a relationship between opinions on the economy and the vote might be spurious. Maybe one’s party identification (whether one calls oneself a Republican or Democrat) drives both the vote in House elections and opinions on how the president is handling the economy. In the case, party identification is a control variable; it is another variable that might be influencing this relationship that needs to be held constant.
There are four main steps to manipulating data with SPSS:
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1. Reading Data, or how to translate raw data or data in another form into SPSS;
2. Transforming data, or how to either create new variables or change the values of existing variables;
3. Defining variables, or how to put levels onto data so that people can understand it, and how to structure data so that SPSS knows how to read it properly;
4. Creating tables.
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Most SPSS users prefer to use its Windows graphic interface that is, pointing with the mouse and clicking on the options they want. At Harvard, those who want the greater control of typing in commands tend to use other statistical packages. Nonetheless, SPSS provides a way to not only type commands but also switch between this syntax editor and the Windows point-and-click method.
Use of SPSS:
SPSS is the statistical package most widely used by social scientists.
There seem to be several reasons way:
1. Force of Habit–SPSS has been around since the late 1960s. (Political scientist Norman Nie, who co-authored the “The changing American Voter” with Sidney Verba, developed it. SPSS originally stood for Statistical Package for the Social Sciences, but the name has since been changed to reflect the marketing of SPSS outside the academic community);
2. Of the major packages, it seems to be the easiest to use for the most widely used statistical techniques;
3. One can use it with either a Windows point-and-click approach or through syntax (i.e., writing out of SPSS commands)? Each has its own advantages, and the user can switch between the approaches;
4. Many of the widely used social science data sets come with an easy method to translate them into SPSS; this significantly reduces the preliminary work needed to explore new data.
There are also two important limitations that deserve mention:
1. SPSS users have less control over statistical output than. For novice users, this hardly causes a problem. But, once a researcher wants greater control over the equations or the output, she or he will need to either choose another package or learn techniques for working around SPSS’s limitations;
2. SPSS has problems with certain types of data manipulations, and it has some built in quirks that seem to reflect its early creation. The best known limitation is its weak lag functions, that is, how it transforms data across cases. For new users working off of standard data sets, this rarely a problem. But, once a researcher begins wanting to significantly alter data sets, he or she will have to either learn a new package or develop greater skills at manipulating SPSS.
Overall, SPSS is a good first statistical package for people wanting to perform quantitative research in social science because it is easy to use and because it can be a good starting point to learn more advanced statistical packages.
Overview of SPSS for Windows:
SPSS for Windows consists of five different windows, each of which is associated with a particular SPSS file type. The two windows that are most frequently used in analyzing data in SPSS, the Data Editor and the Output Viewer windows. The Data Editor is the window that is open at start-up and is used to enter and store data in a spreadsheet format.
The Output Viewer opens automatically when you execute an analysis or create a graph using dialog box or command syntax to execute a procedure. The Output Viewer contains the results of all statistical analyses and graphical displays of data. The Syntax Editor is a text editor where you compose SPSS commands and submit them to the SPSS processor. All output from these commands will appear in the Output Viewer.