Data distribution refers to how data points are spread out across a range of values. It helps in understanding the overall pattern and characteristics of a dataset. Common types of data distributions include normal distribution, uniform distribution, and binomial distribution. Each type has unique properties that can influence statistical analysis and decision-making. Analyzing data distribution is crucial for various fields, including statistics, data science, and machine learning. By visualizing data through graphs like histograms or box plots, one can identify trends, outliers, and the central tendency of the data, which aids in making informed conclusions and predictions.