1. Intro to Stats and Collecting Data
Intro to Stats
2:20 minutesProblem 1.2.3.c
Textbook Question
Discrete/Continuous Data Which of the following describe discrete data
c. The exact times that randomly selected students spend on smart phones during the preceding week
Verified step by step guidance1
Understand the difference between discrete and continuous data. Discrete data refers to countable items, often integers, while continuous data can take any value within a range, often involving measurements.
Consider the nature of the data described: 'The exact times that randomly selected students spend on smartphones during the preceding week.'
Recognize that time is typically measured in units such as seconds, minutes, or hours, which can be divided into smaller increments, suggesting a continuous nature.
Reflect on whether the data can take any value within a range or if it is limited to specific countable values. Time, in this context, can be measured to any level of precision, indicating it is continuous.
Conclude that the data described is continuous because it involves measuring time, which can take any value within a given range.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Discrete Data
Discrete data refers to countable values that can only take specific, distinct values. Examples include the number of students in a class or the number of cars in a parking lot. Discrete data cannot be divided into smaller parts meaningfully, as it represents whole units.
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Continuous Data
Continuous data, in contrast, can take any value within a given range and can be divided into infinitely smaller parts. This type of data is often measured rather than counted, such as height, weight, or time. Continuous data allows for more precise measurements and can include fractions or decimals.
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Data Classification
Data classification involves categorizing data into types, primarily discrete and continuous. Understanding this classification is crucial for selecting appropriate statistical methods and analyses. Recognizing whether data is discrete or continuous helps in determining how to visualize and interpret the data effectively.
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