1) Population Growth Over a Decade
Scenario: Demographers and urban planners use spline graphs to track smooth population growth patterns.
Data Example (in Millions):
| Year |
2010 |
2012 |
2014 |
2016 |
2018 |
2020 |
2022 |
2024 |
| Population |
1.2 |
1.5 |
1.8 |
2.3 |
2.7 |
3.0 |
3.1 |
3.3 |
Purpose: Spline graphs show smooth population growth trends over time. This helps urban planners make informed decisions about infrastructure and resources.
Download the
file to examine the population trends over the decade and analyze them with a smooth spline graph.
2) Patient Recovery Progress in Healthcare
Scenario: Doctors use spline graphs to track patient recovery data post-surgery or treatment.
Data Example (in %):
| Week |
Week 1 |
Week 2 |
Week 3 |
Week 4 |
Week 5 |
Week 6 |
Week 7 |
| Mobility Score |
20 |
40 |
55 |
70 |
85 |
95 |
96 |
Purpose: Spline graphs help visualize patient recovery progress with smooth transitions over time. This allows doctors to monitor improvements and identify any delays in recovery.
To examine the patient recovery process over weeks, download the
file and plot it using a spline graph to observe continuous recovery progress.
3) Speed of a Vehicle During a Test Drive
Scenario: Car manufacturers monitor speed variations during test drives for performance analysis.
Data Example (in km/h):
| Time |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
| Speed |
25 |
30 |
35 |
40 |
45 |
50 |
53 |
56 |
58 |
60 |
Purpose: Spline graphs smoothly track speed changes, helping analyze acceleration and braking efficiency.
Retrieve the
file to track the vehicle’s speed changes during the test drive, and represent them smoothly with a spline graph.