SPSS stands for Statistical Package for the Social Sciences and as the name suggests, it is a powerful suite of software programs that is used to analyse data related to social sciences which can be applied to surveys, data mining, market research, health research, etc. It is a popular data analysis software because of its point and click approach (no need to type out lines of commands and remember functions) and its ability to handle large amounts of data and present the pattern of the variables in different graphical forms. Instead of having your attention diverted by the calculations aspect of the research work, it lets you focus more on the decision making and discovering the relations between variables.
Importing and transforming data
The SPSS can handle data variables in a very large range of formats. Once you import the data, it can change it into different format types (by changing its structure) according to the framework detail and prerequisite. It has an exceptional ability to handle data and can merge files regardless of the variables and subjects. Data from online survey sites can be imported directly into the software as well. If you import a .sav file, it will automatically attach the labels and distribute the data in a table form. Even if you change the operating software, the old data will still be accessible because the software knows the exact location of the various variables and cases. This knowledge of the exact location of data is what makes the analysis functions in this software much faster than others. Data mining features are also very strong and you can perform smart searches, create decision trees to extract information,
Another very useful tool in filtering data is the Missing Values module. As missing data can really destroy the results of the thesis, this program detects the missing data values before analysis so that data can be validated.
Data management
SPSS stores and organises the data in such a way that the results do not affect the raw data at all. Its data storage system lets you create a metadata directory that helps you keep a centralised repository of data. You can perform case selection, derive data from the data sets, and reshape files (rearranging data without changing the content). It is possible to extract useful insights from the data through the comparison of two variables, cross tabulation, and frequencies counter. It can also perform algebraic, arithmetic, and trigonometric operations.
It has to be noted here that SPSS is also good with qualitative data analysis and using the Text analysis feature, it can sift through the data provided by open-ended questions and help you derive insights for your PhD research.
Regression analysis
This is extremely useful because it analyses the two variables in the data set and discovers a relationship between the two interdependent variables. This also helps in making predictions.
The Visualisation Designer feature is also pretty useful as it presents all this data in a graphical form to help you prepare reports with scatterplots, box plots, and histograms that show the patterns of your data to help you do the inferential work.
Data comparison- ANOVA, M ANOVA
ANOVA stands for Analysis of variance and M ANOVA stands for Multivariate analysis of variance. ANOVA is a statistical formula used to compare the variances of different groups and hence, help the researcher decide which method would be good to compare the different groups. M ANOVA takes into account multiple variables- multiple dependent variables by one or more factor variables or covariates- and performs regression analysis on them to tell us which variable affects the other.
Sample comparison- T-tests
This is done when you want to compare the mean of two groups. The T-test states that the null hypothesis (H0) is that the true difference between these group means is zero and the alternate hypothesis (Ha) is that the true difference is different from zero. These tests can be easily performed to test the difference in two sample types and their interests.
Conclusion
The SPSS is an expensive software but it makes up for its cost by the ease of use and the amount of data it can import. You may say that Excel can perform the same functions but the SPSS certainly is a specialised form of Excel that can handle a wide variety of tasks and data manipulation that you as a researcher might need during your PhD dissertation. If you employ other means of performing the same functions, it might take more time and the presentation of data might not be as elaborate either.
