How do you identify outliers in Likert scale data?

How do you identify outliers in Likert scale data?

Outliers do not really exist in Likert-scales.

1. Outliers do not really exist in Likert-scales.
2. In reality, many outliers are detected by perceived non-conformity with prior expectations based on the investigator’s experience, pilot studies, evidence in the literature, or just common sense.

What is Likert scale in SPSS?

Likert scales – strongly agree, agree, neither agree nor disagree, disagree, strongly. disagree. Scale data. In SPSS this covers discrete and continuous data. Discrete data comprise variables that can only take integers (whole numbers).

How do you check for outliers in SPSS?

To check for outliers in SPSS:

1. Analyze > Descriptive Statistics > Explore…
2. Select variable (items) > move to Dependent box.
3. Click Statistics… >
4. In Output window: Go to Boxplot > Look at circles and *.
5. If there are circles or *, then there are potential outliers in your dataset.

How do you score Likert scale?

The traditional way to report on a Likert scale is to sum the values of each selected option and create a score for each respondent. This score is then used to represent a specific trait — satisfied or dissatisfied, for example — particularly when used for sociological or psychological research.

How do you check for outliers in multiple regression SPSS?

ARCHIVED: In SPSS, how do I find outliers in my regression?

1. From the Analyze menu, select Regression, and then Linear.
2. In the dialog box that appears, click Save.
3. In the next dialog box that appears, check Leverage values.

Is Likert scale ordinal SPSS?

The simple answer is that Likert scales are always ordinal.

What is Tukey’s rule for outliers?

Tukey’s rule says that the outliers are values more than 1.5 times the interquartile range from the quartiles — either below Q1 − 1.5IQR, or above Q3 + 1.5IQR.