Creating Frequency Tables
Creating frequency tables is a Grade 11 Algebra 1 statistics skill from enVision Chapter 11 that organizes raw data by counting how many values fall within each interval. The sum of all frequencies equals the total number of data points. For the dataset {12, 15, 18, 22, 25, 28, 31, 34, 37} grouped by 10-unit intervals: [10-19] has frequency 3, [20-29] has 3, [30-39] has 3. For test scores with 5-unit intervals, [75-79] gets 2, [80-84] gets 1, and so on. Intervals must be equal-width, non-overlapping, and cover all data values.
Key Concepts
A frequency table organizes data by counting how many values fall within each interval or category. The sum of all frequencies equals the total number of data points: $\sum f = n$.
Common Questions
What is a frequency table?
A table that organizes data by counting how many values fall in each interval or category. The sum of all frequencies equals the total number of data points.
How do you choose intervals for a frequency table?
Select equal-width intervals that cover all data values without overlapping. Intervals of 5 or 10 units are common choices depending on data range.
Create a frequency table for {12,15,18,22,25,28,31,34,37} with width-10 intervals.
[10-19]: 12, 15, 18 = frequency 3. [20-29]: 22, 25, 28 = frequency 3. [30-39]: 31, 34, 37 = frequency 3. Total = 9.
Must every data point belong to exactly one interval?
Yes. Intervals must be non-overlapping and exhaustive so each value is counted exactly once.
How do you verify your frequency table is correct?
Sum all the frequencies. The total must equal the number of data points in the original dataset.
What is the difference between a frequency table and a relative frequency table?
A frequency table shows counts. A relative frequency table divides each count by the total to show proportions, making comparison across different-sized datasets easier.