Their data can be divided into these two types, as they are associated with separate methods of analysis. A good Likert scale, as above, shows a symmetry of categories around a center with clearly defined linguistic qualifiers. In such a symmetric scale, equidistant attributes are usually observed more clearly or, at the very least, deduced. When a Likert scale is symmetrical and equidistant, it behaves more like a measurement at regular intervals. While a Likert scale is actually ordinal, if it is well represented, it can nevertheless approach an interval measure. This can be beneficial, because if it were only treated as an ordinal scale, some valuable information could be lost if the “distance” between the Likert elements was not available. The important idea is that the appropriate type of analysis depends on how the Likert scale was presented. Na answers can be difficult to integrate into your analysis. There is no uniform answer. You need to determine whether NA logically fits your scale and what its value is. It depends on the theme and scale.

I was recommended to standardize the data, but I don`t understand why (since my articles all have the same 1-4 Likert scale). Can you explain that to me? When I standardize variables, I have problems with my descriptive statistics, because interpreting standardized indices is quite difficult (which counts as favorable and which is not). My goal was to show frequencies that divide the sample into people who agree (including agree and strongly agree) and those who don`t. • Group by a median or mode (no average, as these are ordinal data); The mode is probably best suited for simple interpretation. To use a Likert scale in a survey, present participants with Likert-like questions or statements and a continuum of elements, usually with 5 or 7 possible answers to capture their degree of compliance. I am currently working on my final thesis and I have some doubts about how to analyze the questionnaire data. I study whether attention control is different between two groups of infants (typical probability and increased probability) aged 10 to 14 months with a behavioral paradigm. I also check if attention control after 14 months is correlated with the Capacity variable.

Regulability is a measure of the temperament characteristic of the infant behaviour questionnaire (which uses a response on the 7 Likert scale). I looked at descriptive statistics (averages and SD) and data relating to the increase in probabilities have a Skew value of -1559. My question is whether the regulatory capacity of the variable must follow a normal distribution to correlate the variable with the measure of attention control (behavioral data). Should I take care of the transformation of this variable? Fortunately, Dr. a. . .