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The class width is a critical component when creating a frequency distribution table. It represents the interval size between each of the frequency classes in a dataset. Understanding how to calculate it is key to effectively organizing data for analysis.

To compute the class width, you first need to understand the range and number of classes you want. In general, the class width is calculated by dividing the range of the dataset by the number of desired classes. It's important to note we typically round up the result to ensure all values fit into a class. This approach prevents any data from being left out between class intervals.

For example, if our data range is 110 and we want 5 classes, we divide 110 by 5, giving 22. By rounding up, we confirm our class width is 22, which helps in systematically arranging the data into clear, concise segments.

Class limits are the boundaries that separate one class in a frequency distribution from another. They provide a clear demarcation between classes, helping to organize data neatly. Each class typically has a lower limit and an upper limit, and understanding how to determine these limits ensures accurate data categorization.

When calculating class limits, you start with the lowest value in your dataset as the lower limit of your first class. Each subsequent class lower limit is found by adding the class width to the previous class's lower limit. The upper limit is then obtained by subtracting one from the next class lower limit, ensuring no overlap between classes except for the relationship of the next class starting right after the previous ends.

This method is displayed in the original solution, where the first class limit starts at 10 (the dataset's low value). Each class continues sequentially, maintaining this boundary framework.

Calculating the range is a foundational step in setting up a frequency distribution. It defines the extent of your data by measuring the spread or difference between the highest and lowest values in your dataset. The range calculation gives you a quick glimpse into the variation within your data, which is essential for further statistical analyses.

The formula for calculating range is straightforward: subtract the smallest value from the largest value in the dataset. For instance, if the highest number is 120 and the lowest is 10, then the range is 120 - 10, which equals 110.

This step is crucial as it helps define the parameters for subsequent calculations, such as determining class width. Without knowing the range, it becomes challenging to divide the data into meaningful segments or classes.