Inferential vs Descriptive Statistics: Discover the Secret Weapons of Data Science!

In my work as a Data Analyst, I’ve come to appreciate the distinct roles that descriptive and inferential statistics play in interpreting data. Descriptive statistics focus on summarizing and understanding the characteristics of a data set we have in hand. They provide simple summaries about the sample and the measures. On the other hand, inferential statistics are used to make predictions or inferences about a broader population from which a sample is drawn. This distinction is crucial because it guides the statistical methods we choose for analysis. Understanding the core differences starts with grasping basic concepts such as measures of central tendency, which are foundational in descriptive statistics. These measures include the mean, median, and mode, which help us understand the central point around which data points cluster. Inferential statistics, however, often rely on making estimations about the broader population through hypothesis testing and confidence intervals, aiming to draw conclusions beyond the immediate data sets. <a href="https://blog.mirkopeters.com/inferential-vs-descriptive-statistics-discover-the-secret-weapons-of-data-science-575c4eb6c0e1">Website</a>