Uploaded April 2023 | Updated September 2026, 20 hours ago
Standard Deviation Part 4/4 #statistics #datascience #dataanalysis #dataanalytics #research #thesis #stats #researcher #science #datatab #SPSS
Standard Deviation Part 4/4 #statistics #datascience #dataanalysis #dataanalytics #research #thesis #stats #researcher #science #datatab #SPSS
![Likert-Scale [Simply Explained]](https://i.ytimg.com/vi/Tf_71r1Ve5w/mqdefault.jpg "Likert-Scale [Simply Explained]
Why do we need a Likert scale? Lets assume you have formulated a hypothesis in which a variable that cannot be measured directly, a so-called latent variable, occurs. So how do you measure this variable in your questionnaire?
Latent variables are, for example, physical well-being or environmental awareness. Why are these variables not directly measurable? Of course, you could simply ask in your questionnaire, What is your level of environmental awareness?
However, you will find it very difficult or very inaccurate to measure environmental awareness with just this one question, because environmental awareness consists of several dimensions.
In order to be able to adequately measure latent variables such as environmental awareness, likert scales are now used.
https://numiqo.com/tutorial/likert-scale")
![Hierarchical Cluster Analysis [in 60 sec.] #shorts](https://i.ytimg.com/vi/W9j5pAIYbQQ/mqdefault.jpg "Hierarchical Cluster Analysis [in 60 sec.] #shorts
A hierarchical cluster analysis is a clustering method that creates a hierarchical tree or dendrogram of the objects to be clustered. The tree represents the relationships between objects and shows how objects are clustered at different levels.
#statistics #datascience #dataanalysis #research #student #thesis #stats #researcher #thesiswriting #science #learning #education #datatab #SPSS #machinelearning #cluster #clustering")
