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Automatic preparation of data for analysis

Data preparation plays a key role in data analysis and machine learning processes. Its importance stems from several important aspects that affect the quality and reliability of the results. High-quality data influences more accurate and reliable statistical models. Raw, unprocessed data often cont…

Coefficient of determination R²: what is it and how to interpret it?

The coefficient of determination, denoted R² (R-square), is one of the most commonly used statistical tools for model evaluation. It offers a measure of how well a model under test fits the data. In this article, we'll look at what exactly the R² coefficient is and what role it plays in data analys…

Median

The median is a statistic that we classify as a measure of central tendency.  It is one of the most popular descriptive statistics next to the arithmetic mean. For students of analytics, it is a statistic with which they become familiar as one of the first. In addition to its simple interpretation …

Predictive AI vs. Generative AI – characteristics and differences

Artificial intelligence (AI) is one of the most exciting and rapidly developing areas of technology in the modern world. From self-learning algorithms to advanced image recognition systems to autonomous vehicles, AI is revolutionizing various areas of our lives. What exactly is artificial intellige…

Story of a pie

You may not know this but this year is the 217th birthday of the humble pie chart. Its first known, and purposeful, application was the visualisation of the geographical distribution of the Turkish Empire across three continents: Asia, Europe, and Africa. It was first presented in Statistical Brevi…

Parametric versus non-parametric tests. Which test to choose for analysis?

Statistical analysis is an integral part of scientific research and working with data. In order to draw valid conclusions, the use of appropriate statistical tests is essential. The analyst is often faced with the choice of which test to choose in a given situation. This is important because the wr…

Meta-analysis as an analytical tool

In today's scientific and research world, analysts are often confronted with the problem of analysing large amounts of data coming from different studies. In such situations, meta-analysis becomes an indispensable tool. It allows the results of many studies to be assessed collectively and more prec…

General linear models and generalised linear models - differences and similarities

In data analysis, the use of general linear models is common due to their simplicity and ease of interpretation of the results obtained. However, there are times when the analyst encounters situations where the assumptions of classical linear models are difficult or impossible to meet. This may be …

Bayesian inference

Bayesian inference is a method of statistical inference. It is named after Thomas Bayes, the British mathematician and pastor who first formulated Bayesian probability theory in the 18th century. It is a method of data analysis that allows the probability of certain events to be determined not only…

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