To calculate cumulative frequency, you need a dataset or a frequency distribution table. Cumulative frequency is the running total of the frequencies up to a certain point in the dataset.
Here's a step-by-step guide on how to calculate cumulative frequency:
Step 1: Gather your dataset or frequency distribution table. Let's assume you have a dataset of numbers: 3, 5, 7, 8, 8, 10, 11, 12, 12, 15.
Step 2: If you have a raw dataset, sort it in ascending order. In our example, the sorted dataset would be: 3, 5, 7, 8, 8, 10, 11, 12, 12, 15.
Step 3: If you have a frequency distribution table, make sure you have two columns: one for the values or intervals and another for the corresponding frequencies. Ensure the data is sorted in ascending order based on the values or intervals.
Step 4: Create a new column for cumulative frequency. Start with a cumulative frequency of zero.
Step 5: For each value or interval in the dataset or frequency distribution table, add its frequency to the previous cumulative frequency. Write the result in the cumulative frequency column.
Here's an example using the sorted dataset mentioned earlier:
markdown
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Value Frequency Cumulative Frequency
---------------------------------------
3 1 1
5 1 2
7 1 3
8 2 5
10 1 6
11 1 7
12 2 9
15 1 10
The cumulative frequency for the first value is the same as its frequency because there are no previous values. For subsequent values, the cumulative frequency is the sum of the frequency of that value and the previous cumulative frequency.
In this example, the cumulative frequency represents the total count of values up to a certain point. For instance, a cumulative frequency of 5 for the value 8 means that there are five values in the dataset that are less than or equal to 8.
By calculating the cumulative frequency, you can analyze the distribution of your dataset and calculate various statistical measures such as percentiles and quartiles.
Step-by-step explanation:
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Answer:
To calculate cumulative frequency, you need a dataset or a frequency distribution table. Cumulative frequency is the running total of the frequencies up to a certain point in the dataset.
Here's a step-by-step guide on how to calculate cumulative frequency:
Step 1: Gather your dataset or frequency distribution table. Let's assume you have a dataset of numbers: 3, 5, 7, 8, 8, 10, 11, 12, 12, 15.
Step 2: If you have a raw dataset, sort it in ascending order. In our example, the sorted dataset would be: 3, 5, 7, 8, 8, 10, 11, 12, 12, 15.
Step 3: If you have a frequency distribution table, make sure you have two columns: one for the values or intervals and another for the corresponding frequencies. Ensure the data is sorted in ascending order based on the values or intervals.
Step 4: Create a new column for cumulative frequency. Start with a cumulative frequency of zero.
Step 5: For each value or interval in the dataset or frequency distribution table, add its frequency to the previous cumulative frequency. Write the result in the cumulative frequency column.
Here's an example using the sorted dataset mentioned earlier:
markdown
Copy code
Value Frequency Cumulative Frequency
---------------------------------------
3 1 1
5 1 2
7 1 3
8 2 5
10 1 6
11 1 7
12 2 9
15 1 10
The cumulative frequency for the first value is the same as its frequency because there are no previous values. For subsequent values, the cumulative frequency is the sum of the frequency of that value and the previous cumulative frequency.
In this example, the cumulative frequency represents the total count of values up to a certain point. For instance, a cumulative frequency of 5 for the value 8 means that there are five values in the dataset that are less than or equal to 8.
By calculating the cumulative frequency, you can analyze the distribution of your dataset and calculate various statistical measures such as percentiles and quartiles.
Step-by-step explanation: