Inferential statistics is a branch of statistics that focuses on making inferences and drawing conclusions about a population from a sample of data. It is used to make estimates and projections about a population based on limited information. Unlike descriptive statistics which only seeks to summarise and organise the information in a data set. descriptive statistics which only seeks to summarize and organize the information in a data set.
In artificial intelligence and machine learning, inferential statistics is used to make generalisations from a sample of data for the entire population, and to make predictions about future outcomes based on historical data. For example, it can be used to predict user behaviour on a digital platform, the demand for a product, or the efficacy of a medical treatment.
Some of the most common inferential statistics techniques include hypothesis testing, confidence interval, regression analysis, and analysis of variance. These techniques allow data scientists to make informed decisions about a data set and make accurate predictions.
The integration of tools for predictive analytics is already commonplace in large companies, but thanks to the evolution and, above all, to the dem [...]
Read More »If you don't know the difference between an ERP (Enterprise Resource Planning) system and a CRM (Customer Relationship Management) system, here's what you need to know about the [...]
Read More »There is a consensus among executives of the world's leading companies about the crucial impact that Artificial Intelligence (AI) will have on the [...]
Read More »In order to identify the customer's needs, it is necessary to know their opinion, as this helps to detect where you should improve, what acceptance you [...]
Read More »
