Final answer:
Q-Q plots help visualize the distribution of data, comparing the dataset's quantiles with a theoretical distribution.
Step-by-step explanation:
Q-Q plots, also known as quantile-quantile plots, are used to visualize the distribution of data. They compare the quantiles of a dataset with the quantiles of a theoretical distribution, such as a normal distribution. If the data points fall along a straight line, it suggests that the dataset follows the theoretical distribution. If the data points deviate from the straight line, it indicates that the dataset has a different distribution.
For example, if we have a dataset of heights and we plot the quantiles of the dataset against the quantiles of a normal distribution, a Q-Q plot can help us determine if the dataset follows a normal distribution or if it has outliers or skewness.