Write the different steps of constructing a grouped frequency distribution
Determine the Range:
Find the range of the data by subtracting the minimum value from the maximum value. Range = Maximum Value – Minimum Value.
Choose the Number of Intervals (Classes):
Decide on the number of intervals or classes you want to use. A common rule of thumb is to use between 5 and 20 classes, depending on the size of your dataset.
Calculate the Class Width:
Divide the range by the number of intervals to determine the class width. Class Width = Range / Number of Intervals.
Determine the Starting Point of the First Class:
Decide on a starting point for the first class. It should be a convenient value that includes the minimum data value.
Create the Class Intervals:
Based on the starting point and class width, create the intervals or classes. The intervals should not overlap, and each data point should fall into one and only one interval.
Tally and Count:
Go through the data set and count how many observations fall into each interval. You can use tally marks to keep track.
Construct the Frequency Distribution Table:
Create a table with columns for the class intervals and their frequencies. The table should have at least two columns: one for the class intervals and another for the corresponding frequencies.
Calculate Cumulative Frequencies (Optional):
If desired, add a column for cumulative frequencies. Cumulative frequencies show the running total as you move down the table.
Create a Histogram (Optional):
If you want to visualize the distribution, you can create a histogram using the class intervals and frequencies. The x-axis represents the class intervals, and the y-axis represents the frequencies.
Title and Label the Table and Graph:
Provide a title for the frequency distribution table and the histogram (if created). Label the axes with the variable name and units.
Check for Accuracy:
Double-check your calculations to ensure accuracy. The sum of the frequencies should equal the total number of observations in the dataset.
By following these steps, you can construct a grouped frequency distribution to better understand the distribution of data and identify patterns or trends.