Introduction Machine learning is a common topic in the technology and business world. Machine learning is a technology that processes the raw data, provides helpful information, including data prediction and analysis, and releases final statistics reports. In short, ML helps process the data and produces reports to achieve the set ... Read More

Introduction The Grubbs test is a statistical hypothesis testing method to detect outliers in a dataset. Outliers are the observations that disburse the data distribution and are also known as anomalies. The dataset with outliers tends to overfit more than data with a Normal/Gaussian distribution. Hence, it is necessary to ... Read More

Statisticians use F-test to check whether the two datasets have the same variance or not. F-test is named after Sir Ronald Fisher. To use the F-Test, we make two hypotheses, a null hypothesis, and one alternate hypothesis. Then we select any of these two hypotheses approved by the F-Test. Variance ... Read More

Introduction Data Scientists often use statistical methods for hypothesis testing to gain insights from the datasets. While there are multiple statistical methods available, this article will discuss the Chi-Square Goodness of fit test with its implementation in Python. The Chi-Square test validates the observed distribution of categorical variables to the ... Read More

The Brown-Forsythe test is a statistical test used to determine whether the variances of two or more groups are equal. While Levene's test uses the absolute deviations from the mean, the Brown-Forsythe test uses the deviations from the median. The null hypothesis used in the test is as follows − ... Read More