What happens if the selection of samples is not based on a random procedure?

When the selection of samples is not based on a random procedure, it typically results in a biased sample. This bias can distort the representation of the population being sampled, leading to inaccurate conclusions. Random sampling ensures that every member of the population has an equal chance of being selected, which helps to avoid favoritism or unintentional influences that could skew the data. Without a random selection process, certain segments of the population might be overrepresented or underrepresented, compromising the reliability of the results. Therefore, a biased sample fails to truly reflect the characteristics or quality of the overall population, making it difficult to draw valid inferences from the findings.