Statistics

Working with normal distributions in Python

Normal distribution is describing random variables with bell-shaped probability density functions. Normal distribution is widely used in data science because…

11 months ago

Calculate point-biserial and biserial correlations using R

When a correlation, usually Person type correlation, is calculated, two variables have to be continuous. But this requirement does not…

11 months ago

Using t-distribution and t-test with R

A Student t-distributed random variable is modeling the ratio between a standard Normal random variate and square root of a…

1 year ago

Poisson distribution implementation in Python

Poisson distribution is a discrete distribution. It is frequently used to model the counts of event occurrence during a specified…

1 year ago

Calculating Type I Error and Type II Error in Hypothesis Testing using Python

In hypothesis testing, the possibility of the other side than the conclusion usually exists, and the analysis commits so-called Type…

1 year ago

Calculating The Power of a Test in Hypothesis Testing with R

In hypothesis testing, the analyst has chance to commit both Type I and Type II errors. The Type I error…

1 year ago

Calculating Type I Error and Type II Error of Hypothesis Testing using R

In statistical hypothesis testing, there are usually two types of errors that the process will encounter, namely Type I and…

1 year ago

Using Weibull distribution in R programming

Weibull distribution, named after Swedish mathematician Waloddi Weibull, is a continuous distribution which is widely used to model the distribution…

1 year ago

Using Lognormal distributions in R programming

Lognormal distribution in probability and statistics is used to model the distribution of a positive random variable Y, if Y…

1 year ago

Implementing beta distribution in R programming

Beta distribution is a family of distributions which are used to model the probability of continuous random variables defined on…

1 year ago