Get Plotting Likert And Other Rating Scales Form

The difference between the Likert-type scale and a full-blown Likert scale is that the Likert-type scale only uses a five-point (or seven-point, or whatever you prefer) to answer on a single question. A full-blown Likert scale on the other hand uses a series of statements that explore different dimensions of a subject.

Likert items are used to measure respondents' attitudes to a particular question or statement. To analyse the data it is usually coded as follows. One must recall that Likert-type data is ordinal data, i.e. we can only say that one score is higher than another, not the distance between the points.

Inferential statistics For ordinal data (individual Likert-scale questions), use non-parametric tests such as Spearman's correlation or chi-square test for independence. For interval data (overall Likert scale scores), use parametric tests such as Pearson's r correlation or t-tests.

appropriate statistics are Mann-whitney U test and Chi sqaure test.

Various statistical models have been developed and are currently headed under the Item Response Theory framework. The simple answer is that Likert scales are always ordinal. The intervals between positions on the scale are monotonic but never so well-defined as to be numerically uniform increments.

VISUALIZE THE LIKERT-TYPE SCALE We can use pie or bar charts to capture the different responses to a Likert-type question or statement. Figure 2. Bar and Pie charts used to visualize Likert scale responses. However, the best way to visualize Likert scales is to build a Diverging Stacked Bar Chart.

The Likert scale ranges from one extreme to another, for example extremely likely to not at all likely. ... Likert scale is important for research because it can be used to measure someone's attitude by measuring the extent to which they agree or disagree with a particular question or statement.