1. The problem is to understand the concept of "échantillonnage" (sampling) in statistics. 2. Sampling is the process of selecting a subset (sample) from a larger set (population) to estimate characteristics of the whole population. 3. The key formula related to sampling is the sample mean: $$\bar{x} = \frac{1}{n} \sum_{i=1}^n x_i$$ where $n$ is the sample size and $x_i$ are the sample values. 4. Important rules: - The sample should be representative of the population. - Larger samples tend to give more accurate estimates. - Random sampling helps avoid bias. 5. Example: If you have a population of 1000 people and you sample 100, you calculate the average of those 100 to estimate the population mean. 6. This process helps in making decisions or predictions without surveying the entire population, saving time and resources.