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Types of Data

• The tutorial contrasts two main types of data:

  • 1. Discrete Data

  • 2. Continuous Data

  • 3. Discrete and Continuous Data in Practice

Terms to Know

Discrete Data

• Definition: Data that can take only certain distinct values.

• Examples from Usain Bolt's data:

  • Gold medals: 8 (whole numbers only)

  • World records: 3 (whole numbers only)

• Additional examples:

  • Number of rail cars in a train

  • Shoe sizes (e.g., size 9 and ½)

• Key Point: Discrete data cannot include fractions; it is restricted to whole or specific incremental values.

Continuous Data

• Definition: Data that can take any value within a specific range or interval.

• Examples:

  • Temperature (e.g., between 50 to 80 degrees)

  • Commute time (e.g., 30 minutes and 5 seconds or 32 minutes and 17 seconds)

  • Weight (e.g., 150.75 pounds, 102.62 pounds)

• Key Point: Continuous data can take on any numeric value within a range, allowing for more precision.

Discrete and Continuous Data in Practice

• Questions to determine if data is discrete or continuous:

  • Is barometric pressure discrete or continuous? Continuous

  • Is the number of pairs of shoes someone owns discrete or continuous? Discrete

  • Is the time for a light bulb to burn out discrete or continuous? Continuous

  • Number of green M&M- Discrete

Summary

• Quantitative data is categorized into two types:

  • Continuous Data: Can take any value in a range.

  • Discrete Data: Can only take certain values.

• Every quantitative measurement obtained will be either discrete or continuous.

• The tutorial emphasizes understanding of discrete and continuous data through examples and practice.