Counted and Measured Outcomes

Introduction

Welcome back to Reading and Describing Distributions! In the first two lessons, you learned that a distribution captures the likelihood of every possible outcome and that you can read a distribution graph by pairing positions on the horizontal axis with heights on the vertical axis. Now we will build on that graph-reading skill by asking why distribution graphs sometimes use bars and other times use smooth curves . In this third lesson, you will discover that the choice of graph style is not a matter of taste; it is determined by the kind of outcome the quantity produces. By the end, you will be able to look at any everyday variable and confidently say whether its distribution should appear as bars or as a curve.

3

5

Be a part of our community of 1M+ users who develop and demonstrate their skills on CodeSignal

Feature	Counted outcomes	Measured outcomes
How obtained	Counting whole units	Measuring along a range
Possible values	Separate whole numbers ( $0, 1, 2, \ldots$ )	Any value in an interval ( $2.71$ , $3.0$ , $3.004$ , …)
Gaps between values?	Yes	No
Graph style	Separate bars	Smooth curve
Example	Number of texts received per day	Temperature outside