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…