Question

What additional piece of information would be most helpful in determining the number of people in the U.S. over age 84 who had a new case of cancer in the years \(2007-2011 ?\) (A) The total number of new cancer cases between 2007 and 2011 in the United States (B) The total number of male cancer patients between 2007 and 2011 (C) The total number of lung cancer cases in the elderly between 2007 and 2011 (D) The total number of emergency room visits by the elderly between 2007 and 2011

Short answer

Option A is the most helpful for estimating new cancer cases for people over 84 using additional age-specific data.

Step-by-step solution

Understanding the Question

To find the number of people in the U.S. over the age of 84 who had a new case of cancer between 2007 and 2011, we need a piece of information that is very specific to that demographic group and timeframe.

Evaluate Option A

Option A provides the total number of new cancer cases in the U.S., but does not specify the age group or gender. This information would not help in isolating the number of new cancer cases for those over age 84 specifically.

Evaluate Option B

Option B gives the total number of male cancer patients. Like option A, it doesn't specify the age group and thus wouldn't directly help in finding data specific to people over the age of 84.

Evaluate Option C

Option C specifies the number of lung cancer cases in the elderly. While it specifies elderly, it focuses on only one type of cancer and does not provide a comprehensive view about all new cancer cases for people over age 84.

Evaluate Option D

Option D mentions the total number of emergency room visits by the elderly. This does not relate directly to cancer cases and is more about healthcare utilization in general.

Choosing the Most Helpful Information

The most helpful piece of information would be one that directly mentions new cancer cases for individuals over age 84. Since none of the options exactly fit this criterion, we conclude that option A is the most helpful because it provides information on the total number of cancer cases, allowing for potential estimates when combined with other age-specific data, if available.

Key concepts

Data Analysis

Data analysis involves collecting and examining data to extract useful information, identify trends, and support decision-making. In the context of the exercise, analyzing cancer data involves identifying patterns in disease incidence among certain groups in the population.

For this exercise, to determine how many people over the age of 84 developed cancer from 2007 to 2011, specific data is needed. This process would generally include:

• Collecting data on all new cancer cases within the period
• Filtering for individuals aged over 84
• Calculating rates per demographic to find age-specific trends

With appropriate demographic filters and thorough analysis, researchers can provide valuable insights into how cancer affects different age groups over time. This understanding can guide resource allocation and health policy decisions.

Demographic Analysis

Demographic analysis focuses on characteristics such as age, gender, and race to understand how different segments of the population are affected by various factors. In this case, we are particularly interested in those over 84 with new cancer cases.

To perform a demographic analysis:

• Identify the target demographic – here, people over the age of 84
• Use age-specific data to evaluate health trends
• Analyze data to find any peculiar trends or patterns specific to that age group

This type of analysis helps in understanding specific needs and challenges faced by different demographics. It also aids in planning health services and interventions more effectively for the target population.

Problem-Solving Strategy

Having an effective problem-solving strategy is key to tackling complex questions. In the given exercise, we need to identify information that would directly help answer the main question about new cancer cases in the elderly.

Here’s a structured problem-solving approach:

• Understand the question: What specific data is required?
• Break it into parts: Analyze all given options for relevance to the target data
• Eliminate unsuitable choices: Remove options that do not directly address the age-specific requirement
• Focus on the best available option: Sometimes choosing the closest fit can also help, as seen with option A

Such strategies not only streamline the decision-making process but can also improve efficiency and accuracy in problem-solving, especially in standardized tests.

Standardized Testing

Standardized testing, like the PSAT/NMSQT, is designed to assess a student's aptitude in various subjects, including mathematics. It evaluates problem-solving, analytical, and reasoning skills under time constraints.

In mathematics problems involving data or demographic analysis, students are required to apply these skills by:

• Quickly interpreting presented data
• Choosing the most relevant information needed for the solution
• Using logic and reasoning to confirm their choice

These tests prepare students for higher education by fostering critical thinking and the ability to make logical deductions. They aim not only to test knowledge but also to gauge how students use that knowledge to solve real-world problems.