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A frequency distribution is indeed a tabular summary that organizes data into categories and shows the frequency of observations within those categories. This allows for a clear and concise view of how often each value or group of values occurs in a dataset. By summarizing the data in this way, it makes it easier to identify patterns, trends, and the overall distribution of the data.

For example, if you have data on the ages of participants in a study, a frequency distribution would categorize ages into specific ranges (like 0-10, 11-20, etc.) and count how many participants fall into each range. This visualization helps in comprehending how the ages are spread out across the different categories.

The other options do not accurately define a frequency distribution. A graphical representation of data over time refers to different types of charts or graphs, while predicting future trends based on historical data involves forecasting techniques rather than summarizing current data. Finally, a statistical tool for comparing different sets of data pertains more to comparative statistics rather than simply organizing and displaying frequencies within a single dataset. Thus, the choice defining frequency distribution as a tabular summary showing the frequency of observations in categories is the most accurate and relevant.