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 semantic web or "internet of knowledge" is an extension of the current web. Unlike the latter, the semantic web is based on proportional [...]
Read More »Churn, or customer churn rate, is a constant challenge for today's businesses. The ability to retain customers is a constant challenge for today's companies.
Read More »What is Digital Transformation? The industrial revolution profoundly changed the society of the 19th century, but the digital transformation of the [...]
Read More »The Big Data market is booming. Although the need to transform data into information for decision making is not new, the need to [...]
Read More »
