Beginners Guide to SPSS
One of the most difficult things in the final degree projects, Master, doctoral, is when we must undertake analysis of statistics and, for example, do it through the SPSS (Statistical Package for the Social Sciences) program. One may be a person with great knowledge in an area, but, normally, one does not know how to face a job of this type.
To delve a bit into the issue, the most common thing when performing a statistical analysis is that we process it through the SPSS program developed by the IBM brand.
The most vital feature of this software is that it can process a large quantity of data and carry out analysis of different formats, such as text.
SPSS is a powerful statistical data analysis software with an intuitive graphical interface that is easy to use. It is very often used in the social sciences and more specifically by companies and market researchers. This software is very useful when conducting commercial research.
Why use SPSS?
SPSS makes it easy for you to create a data file in a structured way and also organize a database that can be analyzed with different statistical techniques offered by this software. It allows transforming a database created in Microsoft Excel into an SPSS database. The main reason for its great popularity lies in the ability of this powerful software to work with large databases.
Finally, with the statistical software SPSS, it is possible to predict with certainty what will happen in the future, and thanks to this, be able to make intelligent decisions, solve problems and improve results.
How does SPSS work?
The first thing we must do is load the data. These can be loaded manually, although the idea is to do it with an Excel format to facilitate it. SPSS can carry out a wide range of statistical analyses with a series of drop-down menus. However, it has the added benefit of allowing users to save frequently used procedures, such as programs that can be modified and used repeatedly.
The IBM SPSS Statistical Package – main functions:
- Regression Models: utilised when the value of a variable is about to be predicted depending on the value of another variable.
- Advanced Models: it is the usage of univariate/multivariate modeling to get more succinct conclusions in analyzing complex relationships.
- Data reduction: It allows creating synthetic variables from colonial variables through Factor Analysis.
- Classification: It allows us to carry out groupings of observations or variables (cluster analysis) using three different algorithms.
- Non-parametric tests: It allows performing different specialized statistical tests on non-normal distributions.
- Tables: Allows the user to give a special format to the data outputs for later use. There is a certain tendency among users and developers of the software to leave out the original TABLES system. Thus, to make more extensive use of CUSTOM TABLES calls.
- Categories: It allows multivariate analysis of variables normally categories. Metric variables can also be used as long as the appropriate recoding process is carried out.
- Joint Analysis: Allows the analysis of data collected for this specific type of statistical test.
- Maps: Likewise, it allows the geographical representation of the information contained in a file (discontinued for SPSS 16).
- Exact Tests: allows you to perform statistical tests on small samples.
- Missing Values Analysis: Simple regression based on imputations on missing values.
- Complex Samples: it allows the creation of stratified samples, by conglomerates or other types of samples.
- SamplePower: sample size calculation.
- Classification Trees: allows the formulation of classification and/or decision trees with which the formation of groups can be identified, and their members’ behavior can be predicted.
- Data Validation: Allows the user to perform logical reviews of the information contained in a “.sav” file and obtain reports of the values considered outliers. It is similar to the use of syntax or scripts to make revisions of the files, in the same way that these mechanisms are after the digitization of the data.
SPSS Programmability Extension (SPSS 14 onwards). It allows the Python programming language to be used to better control various processes within the program until now were mainly carried out through scripts (with the SAX Basic language). Also, there is the possibility of using Microsoft .NET technologies to make use of SPSS libraries. Although some users have questioned the need to include other languages, it does not have this among its immediate objectives.
What kind of statistical analysis can be performed with the SPSS program?
SPSS allows for both basic and advanced statistical analysis. In most cases, organizations need reports.
For example, an institution that collected information about its students will want to have a student profile that includes a description of the type of student attending the institution, its characteristics of age, interests, family income, place of origin, etc.
The SPSS will be able to support the development of this profile through various basic descriptive analysis of its database.
In other cases, the characteristics of two or more groups are compared concerning various variables: for example, to find out if there is a difference in the performance of students according to their gender. SPSS allows you to answer this question through more advanced procedures like the T-Test. Likewise, if you want to compare the performance of students depending on their socioeconomic level, there are other procedures for statistical analysis, such as ONE-way ANOVA with which more than two groups can be compared.
Advantages of using SPSS
- It allows a significant saving of time and effort, performing in a matter of seconds a job that would require hours and days.
- It allows us to transfer the attention from the mechanical tasks of the data calculations to the most important areas, conceptual such as decisions on processes, interpretation of results, critical analysis, projections, trend analysis that allow planning future decisions, etc.
- It allows working with large amounts of data efficiently, using larger samples and including more variables.
- It makes exact calculations possible, thus avoiding rounding, approximations, and, most importantly, errors in manual calculation.
- It allows you to take data from other software (e.g., Microsoft Excel), make it your own, and work with it.
Disadvantages of SPSS:
- Since this software contains many options and results, it requires serious effort to understand and make use of it.
- Sometimes it carries unnecessary sophistication by allowing complex techniques to be used to answer simple questions.
- One of the biggest disadvantages is that most results reports contain an excessive level of information that, rather than clarify, confuses the user.
- Although it is relatively easy to use, if you do not have a little experience, it is difficult.
Misconception about using SPSS
It is quite true that the SPSS program seems complex; however, one doesn’t have to be a master programmer of the SPSS syntax to use a program. It is not necessary to write syntax, although an expert in such syntax could write a program. To save a procedure like the SPSS program for future use, all you have to do after selecting the appropriate commands is to click the “Paste” command in the SPSS program instead of the “OK” command. ). The “Paste” command saves the syntax in a separate file, which can be saved and modified for future use.
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