Question

The Centers for Disease Control and Prevention (www.cdc.gov) lists causes of death in the United States during 2004: $$ \begin{array}{l|c} \text { Cause of Death } & \text { Percent } \\ \hline \text { Heart disease } & 27.2 \\ \text { Cancer } & 23.1 \\ \text { Circulatory diseases and stroke } & 6.3 \\ \text { Respiratory diseases } & 5.1 \\ \text { Accidents } & 4.7 \end{array} $$ a) Is it reasonable to conclude that heart or respiratory diseases were the cause of approximately \(33 \%\) of U.S. deaths in \(2003 ?\) b) What percent of deaths were from causes not listed here? c) Create an appropriate display for these data.

Short answer

a) Yes, it's reasonable. b) 33.6% of deaths were from causes not listed.

Step-by-step solution

Add Heart and Respiratory Disease Percentages

Calculate the combined percentage of deaths due to heart disease and respiratory diseases. Add the percentages for these two categories: \( 27.2\% + 5.1\% = 32.3\% \).

Evaluate the Reasonableness for 33%

Compare the calculated percentage of 32.3% from Step 1 to the claim of approximately 33%. Since 32.3% is very close to 33%, it is reasonable to conclude that heart or respiratory diseases were the cause of around 33% of U.S. deaths.

Calculate Percentage of Deaths from Unlisted Causes

To find the percentage of deaths from causes not listed, sum all given percentages and subtract from 100%. Sum: \( 27.2\% + 23.1\% + 6.3\% + 5.1\% + 4.7\% = 66.4\% \). Subtract from 100%: \( 100\% - 66.4\% = 33.6\% \).

Present Data in a Pie Chart

Create a pie chart with the following segments corresponding to the given percentages: Heart disease (27.2%), Cancer (23.1%), Circulatory diseases and stroke (6.3%), Respiratory diseases (5.1%), Accidents (4.7%), and Other causes (33.6%). This chart visually represents the distribution of causes of death in percentage form.

Key concepts

Data Visualization

Data visualization is a powerful tool used to communicate information clearly and efficiently. It involves creating visual representations of data sets, such as graphs, charts, and maps, to help users comprehend complex information quickly.
One popular method of data visualization is pie charts. Pie charts are circular charts divided into sectors, each representing a proportion of the whole dataset. Each sector's size is proportional to the quantity it represents. This makes it easy to compare different components of a dataset at a glance.

• Pie charts are best for displaying data that represents part of a whole.


• They make it easy to show percentage distributions and relationships between categories.


• For example, a pie chart can visually represent different causes of death, illustrating their relative frequency among the total set of causes.

By organizing data in a visually appealing manner, data visualization aids in better understanding and decision-making.

Percentage Calculation

Percentage calculation is fundamental in statistical analysis. It allows us to determine the parts of a whole in relative terms, offering a clear understanding of how different segments contribute to the total.
For example, when analyzing data on the causes of death, you might be interested in finding out how significant a particular cause is compared to the total number of cases.

• To calculate the percentage, divide the number of occurrences (or the numerical value) of a category by the total number, then multiply by 100.


• For instance, if heart disease accounts for 27.2% of deaths, the percentage is calculated using the formula:
  \[\text{Percentage} = \left( \frac{\text{Deaths due to heart disease}}{\text{Total deaths}} \right) \times 100\]


• Ensuring all percentages across categories total to 100% is crucial for accuracy in statistical analysis.

Understanding how to perform percentage calculations helps in analyzing and interpreting data correctly.

Cause of Death Statistics

Understanding cause of death statistics enables us to identify prevalent health problems within a population. These statistics highlight the most common ailments and accidents contributing to mortality rates.
By analyzing cause of death statistics, health organizations can design better prevention and intervention strategies, addressing the most pressing health issues effectively.
For 2004 in the U.S., heart disease and cancer were leading causes of death, indicating a need for increased awareness and health measures in these areas.

• Each cause is represented as a percentage of total deaths, helping to prioritize public health efforts.


• Such statistics are not only vital for health officials but also for policymakers to allocate resources efficiently.


• Visual representation, like pie charts, can further simplify these statistics for public comprehension.

Thoroughly understanding these statistics is crucial for informed health policy and improved public health outcomes.

Pie Chart

A pie chart is an effective way to depict allocations of data into different segments of a whole. In statistical analysis, it is particularly useful for showing the composition of datasets where each part contributes to a total.
To create a pie chart, determine each category's proportional representation of the total percentage.
For instance, when showcasing 2004 U.S. death causes, each segment of the pie chart represents a specific cause like heart disease or cancer, visually displaying its share of total deaths.

• The circle is divided based on the percentages assigned to each category, with all segments together forming a complete circle, i.e., 100% of data.


• This visual representation highlights which causes were more significant by showing them as larger segments.


• Pie charts are intuitive and provide a quick visual comparison between categories, which makes them especially useful when summarizing statistics for reports or presentations.

Pie charts offer a straightforward means for interpreting data, making complex information accessible at a glance.