Table of contents

1. Intro to Stats and Collecting Data1h 14m
2. Describing Data with Tables and Graphs1h 55m
3. Describing Data Numerically2h 5m
4. Probability2h 16m
5. Binomial Distribution & Discrete Random Variables3h 6m
6. Normal Distribution and Continuous Random Variables2h 11m
7. Sampling Distributions & Confidence Intervals: Mean3h 23m
8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
9. Hypothesis Testing for One Sample3h 29m
10. Hypothesis Testing for Two Samples4h 50m
11. Correlation1h 6m
12. Regression1h 50m
13. Chi-Square Tests & Goodness of Fit1h 57m
14. ANOVA1h 57m

1. Intro to Stats and Collecting Data

Intro to Stats

Statistics

1. Intro to Stats and Collecting Data

Intro to Stats

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2:08 minutes

Problem 1.2.3.1

Textbook Question

Discrete/Continuous Data Which of the following describe discrete data?

a. The exact heights of all NBA basketball players

Verified step by step guidance

Understand the difference between discrete and continuous data. Discrete data refers to countable items, often integers, where there are distinct, separate values. Continuous data, on the other hand, can take any value within a range and is often measured rather than counted.

Consider the nature of the data described in the problem: 'The exact heights of all NBA basketball players.'

Recognize that height is typically measured in units such as inches or centimeters, which can take on any value within a range, including fractions or decimals.

Identify that because height can be measured to any level of precision, it is not countable in distinct, separate values, which is characteristic of continuous data.

Conclude that the exact heights of NBA basketball players describe continuous data, not discrete data.

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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 data points that can only take specific values, often represented as whole numbers. Examples include the number of students in a classroom or the number of cars in a parking lot. Discrete data cannot be subdivided meaningfully, as it represents distinct and separate values.

Continuous Data

Continuous data, in contrast to discrete data, can take any value within a given range and can be measured rather than counted. Examples include height, weight, and temperature, where values can be infinitely divided into smaller increments. Continuous data is often represented using real numbers and can include fractions and decimals.

Examples of Data Types

Understanding the difference between discrete and continuous data is crucial for statistical analysis. For instance, the exact heights of NBA players are considered continuous data because height can vary and be measured in fractions of an inch. In contrast, the number of players on a team is discrete, as it can only be a whole number.

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