How SPSS Helps in Likert Scale Analysis?

Any sort of research is mainly based on the type of factual representation done by thorough assessments and data collection about the subject concerned. There are a series of steps in order to depict the analysis, that starts with understanding the topic, finding the issues, unwinding the key apprehensions for solving the problem, collecting data for the same, compiling these data for preparing a series of questions and finding solutions.Likert scale is way out of preparing questionnaires and leveling the responses recorded during the survey. However, all these are statistical progressions and hence can be measured accurately by some statistical tool like statistical package for the social science (SPSS). So, let’s have a glance that how SPSS helps in the likert scale analysis.

  • Likert scale is used when you need to get on the whole of your dissertation topic, outlook or knowledge. It involves questions which are interrelated with each other hence the trait measured finally can be summed up together for a particular category.
  • Once all the questions, related data and their variables are compiled up together, you need to make up a data set, data can be either added manually or can be introduced through excel. The first column should be of the number of variables or serial numbers and the proceedings should be the case.
  • Choose variable analysis option for both alphabetical and numeric variables. Nominal variables are chosen if the variables are in yes or no form and if the variables ranges between numeric value 1-4, then nominal variables are chosen for unmatched variables and ordinal variables are used for matched variables. After assigning variable analysis select Median option, select the variable and merge it with the median column. Submit the file by clicking on OK.
  • SPSS calculates the value and reflect it at the end of the table that can be used for descriptive explanation of the data.

Thus, SPSS analysis assists in the likert scale explanation and propounding dissertation aim.