This is a statistical method to establish a linear relationship between two quantitative variables such that one variable can give an estimate of the other....
PCA is one of the most often used dimension reduction techniques in data science. It is extensively used for projection of high dimensional data onto...
R and python are both extensive used in the field of data science and bioinformatics. Different people start learning programming from either languages. So it...
R by design is a functional programming language hence the original objects designed to represent variables, functions, environments and various language components are different than...
Vectors and matrices are heavily used in computer science (and data science) to store and perform multiple mathematical operations on a data set.Although, the concept...
Inference and Hypothesis testing are the two most important and the most confusing concepts in statistics. Inference is related to estimating the population parameters from...
T-test is a popular method of comparing means between two populations but if we want to extend it beyond two populations there is serious decrease...
Just like sampling distribution of sample mean, sample variance follows a distribution but it is slightly complex than, normal distribution followed sample mean. The shape...
Frequently called Expected value, expectation, expectancy, mathematical expectation, sometime referred simply as mean, average or first moment. For a random variable X it is found...
Degree of freedom (df) is a very important mathematical concept which is implemented in multiple disciplines like mechanics, physics, chemistry, and also in inferential statistics....