Author: Saim Khalid

In statistics, data can be classified into different types depending on its characteristics and the kind of analysis that is needed. One of the fundamental types is nominal data. Understanding when to use nominal data is essential for conducting accurate research, analyzing survey results, and interpreting results correctly. Nominal data is primarily used for categorization…

In statistics and research, data can take many forms, each with distinct characteristics that determine how it is collected, analyzed, and interpreted. One of the most fundamental types is nominal data. Understanding nominal data is crucial for anyone engaged in research, business analytics, social sciences, healthcare studies, or any field involving categorization, classification, or labeling…

In statistics, understanding the type of data you are working with is foundational for selecting the appropriate methods of analysis, summarizing results correctly, and making meaningful inferences. Data represents information collected from observations, surveys, experiments, or measurements. However, not all data is the same. The type of data determines what statistical tools, graphs, and formulas…

In the field of statistics and research, one foundational concept influences all data collection, analysis, and decision-making—the understanding of population and sample. These two terms may appear simple at first glance, but they hold great importance in shaping how studies are designed, how conclusions are drawn, and how accurate or trustworthy the results are. The…

In statistics and research, one of the most important decisions a researcher must make is determining how many observations, participants, or units should be included in a study. This number is known as the sample size. The size of a sample plays a critical role in the accuracy, reliability, and credibility of study results. A…

In research, particularly in medical and scientific fields, the concept of population plays a fundamental role in designing studies, drawing conclusions, and making informed decisions. A population refers to the entire group of individuals, cases, or objects that a researcher wants to study. In medical research, for example, the population may include all individuals suffering…

Introduction In today’s competitive business world, companies cannot afford to launch products or services blindly. Before investing massive budgets in advertising, production, and distribution, businesses want to know how customers will react. This is where statistics becomes a powerful tool. It helps organizations make smart, data-driven decisions rather than relying on assumptions or guesswork. One…

In the world of statistics and research, two primary methods are used to collect data: census and sampling. Both techniques serve the purpose of gathering information about a population, but they differ significantly in scope, cost, time, and practicality. Understanding the difference between census and sampling is essential for students, researchers, analysts, policymakers, and anyone…

In statistics and research, a biased sample refers to a sample that does not accurately represent the population from which it was drawn. When the selected individuals or units differ in meaningful ways from the population, the results become misleading, unreliable, and invalid. A biased sample produces distorted findings because certain groups are overrepresented or…

A representative sample is one of the most essential concepts in statistics and research methodology. When researchers want to understand a population, they often cannot collect information from every single member because doing so may be costly, time-consuming, or practically impossible. Instead, they select a smaller group known as a sample. However, not all samples…