This lecture introduces the concepts of exploratory statistics, focusing on populations and samples. The instructor explains the definitions of populations and samples, illustrating how data is collected from a sample of individuals within a population. The discussion includes the types of variables, distinguishing between qualitative and quantitative variables, and further categorizing them into nominal and ordinal types. The instructor elaborates on statistical measures such as the mean and median, explaining how to calculate these statistics from a dataset. The concept of quantiles is introduced, including the median as the 50th percentile. The lecture also covers the importance of understanding data dispersion and the significance of outliers in statistical analysis. The instructor emphasizes the need for robust statistical methods that are resistant to outliers, highlighting the differences between various measures of central tendency and dispersion. The session concludes with a preview of upcoming topics, including graphical representations of data and further exploration of numerical characteristics.