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To calculate the range of a given set of data, follow a straightforward method. First, you need to identify the highest and lowest values within your set. For instance, let's consider the data set provided in the exercise: \(3, 3, 4, 4, 5, 5\).

The highest value in this set is \(5\) and the lowest value is \(3\).
Here is how you calculate the range:

• Subtract the lowest value from the highest value.
• The formula to find the range is: \( \text{Range} = \text{Highest Value} - \text{Lowest Value} \).
• Using the numbers provided, the calculation will be: \(5 - 3 = 2\).

This means that the range of this data set is \(2\).

Calculating the range is a basic yet important step in understanding data sets and provides an immediate view of the data's spread.

Data analysis involves examining, cleaning, and modeling data to discover useful information for decision-making. Calculating the range is one of the simplest forms of data analysis.
The range gives us an idea of how spread out a data set is. For instance, in the example of \(3, 3, 4, 4, 5, 5\), the range is \(2\). This tells us that the data is not very spread out. Most of the values are clustered close together.
By understanding the range, students can compare different data sets in terms of variability and identify any potential outliers or anomalies.

• This is helpful in fields such as quality control, where maintaining low variability is critical.
• It also aids in understanding which data points may need further examination.

Remember that while the range is a quick measure of data variability, it does not provide information about how the numbers are distributed between the highest and lowest values.

Statistical methods help us to understand data and make informed decisions based on it. The range is one of the many statistical tools used for data analysis.
While calculating the range is straightforward, it should be complemented with other statistical methods to get a comprehensive understanding of any data set.
Here are some broader statistical concepts:

• Mean: The average value, providing a central point of the data.
• Median: The middle number when the data set is ordered, offering another measure of central tendency.
• Mode: The most frequently occurring number, showing where the data is most clustered.
• Standard Deviation: A measure of how spread out the numbers are, indicating variability.

These methods work together to give a clearer picture of the data's distribution and characteristics. The range is vital, but it is just one part of a suite of statistical analyses that can provide deeper insights into data patterns.