**Frequency Distribution:**
A frequency distribution is a tabular arrangement of data by classes together with the corresponding class frequencies. It is used to organize and summarize raw data in a meaningful way. The purpose of a frequency distribution is to provide a clear representation of the data and to identify patterns or trends.

**Tabular Arrangement of Data:**
A frequency distribution involves arranging the data in a table format, where each row represents a particular class or category, and each column provides information about that class. The classes are typically determined based on the range of values in the data set, and they help to group similar data points together.

**Class Frequencies:**
In a frequency distribution, the class frequencies represent the number of data points that fall within each class. These frequencies are determined by counting the number of observations or occurrences of values within each class. The class frequencies provide information about the distribution of the data and the frequency with which certain values occur.

**Importance of Class Size:**
The class size refers to the range of values included in each class. It helps determine the width of the class intervals and ensures that each class has a sufficient number of data points for analysis. The class size should be chosen carefully to avoid too few or too many classes, as this can affect the accuracy and interpretation of the frequency distribution.

**Example:**
Let's consider an example to illustrate the concept of a frequency distribution. Suppose we have a data set of exam scores for a class of 30 students. The scores range from 60 to 100. We want to create a frequency distribution to analyze the distribution of scores.

First, we need to determine the class intervals. Let's choose a class size of 10. The first class interval would be 60-69, the second 70-79, and so on until the last class interval of 90-99. The class intervals are mutually exclusive and collectively exhaustive, meaning that each score falls into one and only one class.

Next, we count the number of scores that fall within each class interval. For example, if there are 5 scores between 60 and 69, the frequency for that class interval would be 5. We continue this process for each class interval and record the frequencies in the frequency distribution table.

Once the frequency distribution is complete, we can analyze the data more easily. We can identify the most common range of scores, observe any patterns or outliers, and make comparisons between different class intervals. The frequency distribution provides a visual representation of the data and helps to summarize and interpret the information effectively.