Streuspanne-Lexicon

Blog and Podcast

From B to M

The entries of our »Streuspanne Lexicon« are not regular podcast episodes, but a separate section to briefly and concisely explain a mathematical term in an understandable way. If you have stumbled across a term in one of our Streuspanne episodes that is not yet explained in this lexicon, please contact us. [This podcast is only available in German]

B for Binomial Distribution

Why do you need the binomial distribution and what is it anyway?

As usual: explained briefly and clearly – in under five minutes.

D for Degrees of Freedom

In statistics, degrees of freedom describe the number of independent pieces of information that are included in an estimate.

C for Confidence Interval

The confidence interval is a range in which an unknown parameter is assumed to lie. The wider this range is, the more likely it is that the unknown value will be covered.

C for Critical Values

Critical values are used to determine the significance of results in statistical analyses. They therefore help to determine whether an observed effect is based on chance or is actually significant.

E for Estimate

What is the mathematical definition of an estimate? And how can I even define something so »imprecise«? In the »Streuspanne-Lexicon«, the team explains briefly and concisely using the example of the coin toss.

M for Mean and M for Median

Why aren't all »means« the same?

As usual: explained briefly and clearly – in under five minutes.

M for Monty Hall Problem

What considerations play a role in probability theory and what does game theory have to say in this context?

Back to the Podcast

Back to the overview page of our podcast »Streuspanne – Statistics and Its Curiosities«. Here you will always find the latest episodes and other news about the podcast.

Miniseries – Artificial Intelligence and Statistics

Miniseries – Part One

Is AI Just Glorified Statistics? AI Used To Be Called ML

What are »AI« and »machine learning« actually? How does an algorithm recognize the difference between children and adults? And what are random forests and decision trees all about? In this episode, we explain the basic concepts using concrete examples and show how data clouds and algorithms are connected.

[The podcast is only available in German]

Miniseries – Part Two

Neural Networks: How Machines Learn to Think

What are »neural networks«? How are they structured? What do cats have to do with them? And how are they similar to the learning process of the human brain?

In this episode, we explain how these »Artificial Brains« work and how machines learn to master complex tasks with the help of neurons.

[The podcast is only available in German]

Miniseries – Part Three

AI in Shallow Data Waters

What is »Shallow Learning«? And what is behind this concept?

In this episode, we shed light on how insufficient training data and historical biases affect the performance of AI systems. We also present concrete examples to illustrate this, such as UNESCO, space travel and the Microsoft chatbot »Tay«.

[The podcast is only available in German]

Miniseries – Part Four

Artificial Intelligence With Depth

What makes these models so powerful and how do large language models actually work? In the final episode of our mini-series on »Artificial Intelligence (AI) and Statistics«, we will be taking a deep dive – in the truest sense of the word.

Our podcast team ventures into the depths of the major language models and looks at GPT, Llama and Gemini, among others.

[The podcast is only available in German]