Analysing data with
Data analysis has become the most important part of every research, irrespective of the area of research. The dependence on the statistical analysis and the interpretation has increased, especially in the social sciences. There are various statistical software packages available and Statistical Package for Social Science (SPSS) is one of them.
Introduction to SPSS
SPSS is one of the widely used software for data analysis among academician and also in the business circles. Using SPSS various statistical analysis can be performed which include both the descriptive and inferential analysis. The following articles will provide step wise procedure which can be followed to perform basic data analysis using SPSS. Researchers with basic statistical knowledge can also perform the data analysis by following the given procedure. Performing data analysis using SPSS is not very complex even though it can handle highly complex data. The following articles will provide the basic idea about SPSS along with the data management procedure.
Data analysis procedure
There has been lot of confusion among the researchers when it comes to the selection of appropriate data analysis procedure for the research. There are numerous methods which can be applied depending upon the research. The following articles will provide the step wise data analysis procedure which is the most common procedure in the area of human resource, business administration and other social science subjects.
- Introducing data in SPSS
- Interpreting multivariate analysis with more than one dependent variable
- Frequency analysis with SPSS
- Cross tabulation in SPSS
- Factor analysis using SPSS
- Interpretation of factor analysis using SPSS
- Correlation of variables in SPSS
- Linear regression analysis using SPSS
- Selecting cases for analysis in SPSS
- Multivariate analysis with more than on one dependent variable
Apart from the above mention inferential analysis, various other tests can be performed using SPSS. This tests will not only help us to make our results robust but also provide important insights about the data. These tests can also be used to examine whether the collected data is relevant to fulfil the aims and objectives of the research or not.