What do you do with data taken from a likert scale?

The data is from a questionnaire asking 5 questions, strongly agree to strongly disagree. What would i do with the data to make it a graph or something else

What do you do with data taken from a likert scale?
The analysis of Likert scales is tricky (I personally don't use them b/c of this). You probably want software like SPSS or Visio to do cool graphics. Check this stuff out which may help. Good luck!





--- For Likert Items there is a special method. You begin as for any multiple choice item by giving the number of people and the percentage of people who marked Strongly Agree, Agree, Undecided, Disagree, and Strongly Disagree. But then you take an additional step.


--- The point of this extra step is that you can combine how people answered different items to get an overall response for each person, and for each group of people. This enables you to compare how two different groups answered the same group of questions.


--- To do this you calculate very simply what is called a weighted average response. Assign 5 points for each Strongly Agree, 4 points for each Agree, 3 for Undecided, 2 for Disagree, and 1 for Strongly Disagree. Add up all the points for all the people answering the question in that group. Divide by the number of these people.


--- Try to find interesting differences or comparisons between different groups of people. For more information on how to tell whether a difference in Likert value between two groups is big enough to be worth mentioning, see the webpages on statistics and experimental research. http://academic.brooklyn.cuny.edu/educat...





Additional Resources:


http://www.math.com/homeworkhelp/Statist...


http://www.statisticssolutions.com/Tips_...


http://www.businessbookmall.com/free-stu...


http://www2.chass.ncsu.edu/garson/PA765/...
Reply:depends on what your aim of collecting those data. I used likert scaling as the first step to create consumer perceptual map. The most important thing in using Likert scale is that you should transform the data collected before using it. Your raw data (in form of ordinal measuring scale), should be transformed first to get interval measuring scale, by using MSI (Method of Sucessive Interval). and as in my case, the next step was using MDS to create my consumer perceptual map
Reply:The main idea of statistical inference is to take a random sample from a population and then to use the information from the sample to make inferences about particular population characteristics such as the mean measure of central tendency the standard deviation measure of spread or the proportion of units in the population that have a certain characteristic. Sampling saves money, time, and effort. and a sample can in some cases, provide as much information as a corresponding study that would attempt to investigate an entire population careful collection of data from a sample will often provide better information than a less careful study that tries to look at everything i think thats what you mean
Reply:measure positive and negativve responses from people