Welcome to On Statistics

The binomial distribution is a fundamental concept in probability theory and statistics. It describes the probability of obtaining a certain number of successes (x) in a fixed number of independent experiments (n), where each experiment has only two possible outcomes: success (S) or failure (F). These outcomes are often represented as 1 (success) and 0…

Cluster sampling is a type of probability sampling where the population is first divided into clusters or groups, and then a random sample is selected from each of these clusters. This method is often used when it is not feasible or cost-effective to survey the entire population. In this tutorial, we will learn how to…

Systematic sampling is a probability-based method for selecting a subset of observations from a larger dataset. In this technique, we select every nth observation from the dataset, where n is a predefined number. This method is particularly useful when we want to ensure that the sample is representative of the population and that the data…

Hypothesis testing is a statistical method used to evaluate whether a hypothesis about a population parameter is true or false based on a sample. It is an essential tool in statistics and data analysis. In this article, we will discuss the concept of hypothesis testing, its importance, and how to perform it using Python. The…

Sampling with replacement, also known as resampling with replacement, is a statistical technique where you draw observations from a finite population and then return them to the pool before the next draw. This method is different from simple random sampling without replacement, where you draw an observation and do not replace it before the next…