News / Blog: #statistics

What is Robust Statistics?

Robust statistics is a method of data analysis that specializes in the analysis of erroneous or biased data. Robust statistics is an important complement to traditional methods of data analysis, as it provides a simple and effective way to deal with problematic data. Robust methods are able to detect and eliminate poor quality data without biasing other data. This is especially important when individual data points have a strong impact on the outcome of the analysis. Robust statistics are often used to detect and eliminate scatter, outliers, and extreme points before performing other analyses.

What is a forecasting tool?

A forecasting tool is a program or system used to predict future events or outcomes. It is commonly used in various industries, including finance, marketing, business, and weather. Forecasting tools can use different types of methods and algorithms to analyze data and make predictions. These include simple statistical analysis, complex machine learning algorithms, regression analysis, and data mining techniques.

What is an Analytical Model?

An analytical model is a mathematical or statistical approach used to analyze, understand, and predict complex phenomena. It is a mathematical model used to study a particular problem by examining different variables and properties of the problem. Analytical models are commonly used in science and engineering to study and understand various phenomena, and can also help make predictions about future trends.

What are data analysis methods?

Data analysis methods are techniques used to examine and analyze data to identify trends, patterns, and other useful information. Some of the most common data analysis methods are regression analysis, cluster analysis, descriptive statistics, exploratory data analysis, machine learning, hypothesis testing, and causal analysis.

What is the Mann-Whitney test?

The Mann-Whitney test is a nonparametric statistical test used to test whether two independent samples are from the same population. It is a variant of the significance test used to prove that two groups have different means without normalization. It is also called the Wilcoxon rank sum test