Uploaded August 2023 | Updated September 2026, 1 day ago
Causality (and the difference to correlation)
youtu.be/IeyQvFhFyiY
#statistics #datascience #dataanalysis #research #student #thesis #stats #researcher #thesiswriting #science #learning #education #datatab #SPSS #Minitab
Causality (and the difference to correlation)
youtu.be/IeyQvFhFyiY
#statistics #datascience #dataanalysis #research #student #thesis #stats #researcher #thesiswriting #science #learning #education #datatab #SPSS #Minitab
![Violin Plot [Simply explained]](https://i.ytimg.com/vi/Rw00VmP--qk/mqdefault.jpg "Violin Plot [Simply explained]
A violin plot is a method of plotting numeric data and can be understood as a combination of a box plot and a kernel density plot. It provides a visualization of data distribution.
But how do we interpret a violin plot?
Kernel Density Estimation:
This is the outer layer of the violin plot and displays the density of the data at different values. The width of the plot at different values indicates the density of the data: a wider section suggests a higher density (more data points), whereas a narrower section indicates lower density (fewer data points). The violin plot is typically symmetrical, meaning it mirrors the density estimation on either side of its axis.
Central Box Plot which is Optional:
Inside the violin, there is often a miniature box plot which provides additional details about the datas distribution. The central line in this box plot represents the median of the data, while the edges of the box represent the interquartile range, giving insights into the datas spread.
Whiskers which are Optional:
Like in a box plot, whiskers might extend from the box, indicating variability outside the upper and lower quartiles. They can provide a visual cue for identifying outliers.
► Make a Violin Plot online
https://numiqo.com/statistics-calculator/charts/violin-plot
► E-BOOK
https://numiqo.com/statistics-book")
![One Factor vs. Two Factor ANOVA [One Way vs Two Way]](https://i.ytimg.com/vi/SnlOUfT55So/mqdefault.jpg "One Factor vs. Two Factor ANOVA [One Way vs Two Way]
What is a factor in a Analysis of variance? A factor is, for example, the gender of a person with the characteristics male and female, the form of therapy used for a disease with therapy A, B and C or the field of study with, for example, medicine, business administration, psychology and math.
In the case of variance analysis, a factor is a categorical variable. You use an analysis of variance whenever you want to test whether these categories have an influence on the so-called dependent variable.
Tutorial:
https://numiqo.com/tutorial/two-factorial-anova-without-repeated-measures")
![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")
