
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Transcribed Image Text:### Health Care Expenditures Educational Overview
#### Description
The accompanying data represent health care expenditures per capita and health care services as a percentage of GDP in a particular country from the years 2007 to 2013. GDP stands for Gross Domestic Product, which is the total value of all goods and services created during the year.
##### Data Table:
```
Year Health Care per Capita Health Care as a Percent of GDP
2007 7627 5.5
2008 7897 3.5
2009 8143 3.1
2010 8412 3.1
2011 8644 2.8
2012 8924 3.2
2013 9121 2.2
```
#### Tasks:
1. **Construct a time-series plot that the health care industry would use to support the position that health care has become more expensive over time. Refer to Graph A below.**
**Graph A Details:**
- X-axis: Year (from 2007 to 2013)
- Y-axis: Cost (in USD, ranging from 7,000 to 11,000)
- The plot shows a steady upward trend in health care costs per capita over the years.
2. **Construct a time-series plot that the health care industry would use to support the position that health care costs are decreasing as a percent of GDP. Refer to Graph D below.**
**Graph D Details:**
- X-axis: Year (from 2007 to 2013)
- Y-axis: Percent (ranging from 0 to 6)
- The plot indicates fluctuations but generally shows a downward drift in the percentage of GDP spent on health care over the years.
3. **Explain how different measures may be used to support two completely different positions.**
- **Option A:** Values can be left out of the graph so that the graph supports the position.
- **Option B (Correct):** The type of graph used to display the data can significantly affect the message. For example, using a bar graph versus a time series plot can make a large difference.
- **Option C:** The scales used in the graph can significantly affect the message. Also, the variable used to convey the message on the graph can make a large difference as

Transcribed Image Text:### Health Care Expenditures Analysis: 2007-2013
The accompanying data represent health care expenditures per capita (per person) as a percentage of the U.S. gross domestic product (GDP) from 2007 to 2013. Gross domestic product is the total value of all goods and services created during the course of the year. Complete parts (a) through (c) below.
#### (a) Construct a time-series plot that a politician would create to support the position that health care expenditures are increasing and must be slowed.
- **Option A**
- Description: A graph with a clear upward trend in health care expenditures from 2007 to 2013, indicating a consistent rise.
#### (b) Construct a time-series plot that the health care industry would create to refute the opinion of the politician.
- **Option B**
- Description: A graph showing fluctuations in health care expenditures over the years without a consistent upward trend, potentially showing periods of decrease from 2007 to 2013.
#### (c) Explain how different measures may be used to support two completely different positions.
- **Analysis:**
- Different graphical representations can be used to highlight specific aspects of the data. For instance, focusing on short-term fluctuations or specific years where expenses decreased could argue that expenditures are stable or decreasing. In contrast, emphasizing the long-term trend could support the argument that expenditures are on the rise. Visual presentation plays a crucial role in interpretation.
### Graphs and Diagrams Explained
The graphs provided show health care expenditures per capita on the vertical axis and the years from 2007 to 2013 on the horizontal axis. Each graph includes a time-series plot representing changes in expenditures over time.
- **Graph A:** Shows a steady increase in expenditures, likely used by politicians to argue for intervention.
- **Graph B:** Displays variable trends with ups and downs, likely employed by the health care industry to counter the argument for stringent control.
Understanding how data can be visualized to present different viewpoints is essential in data analysis, policy-making, and industry advocacy.
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