Cer Analyzing Data And Tiger Sharks Answer Key

CER Analyzing Data and Tiger Sharks: A Comprehensive Guide

This article delves into the process of Claim, Evidence, Reasoning (CER) analysis, specifically focusing on its application in analyzing data related to tiger sharks. We'll explore how to construct strong CER arguments, address common pitfalls, and provide examples using hypothetical tiger shark data. This guide is designed for students, researchers, and anyone interested in improving their scientific reasoning and data interpretation skills.

Understanding the CER Framework

The CER framework is a crucial tool in scientific communication and critical thinking. It provides a structured approach to constructing arguments based on evidence and logical reasoning. Each component plays a vital role:

1. Claim:

The claim is your concise statement summarizing your central argument or conclusion. It's what you're trying to prove or support. A strong claim is specific, measurable, achievable, relevant, and time-bound (SMART).

Example: "Tiger shark populations in the Great Barrier Reef are declining due to increased human activity."

2. Evidence:

Evidence consists of the data or observations that support your claim. This could include quantitative data (numbers, measurements), qualitative data (observations, descriptions), or a combination of both. The evidence must be relevant, reliable, and sufficient to support your claim.

Example: "Analysis of tiger shark tagging data from 2010-2020 shows a 25% decrease in the number of tagged sharks. Furthermore, anecdotal reports from local fishermen indicate a significant reduction in tiger shark sightings."

3. Reasoning:

Reasoning explains the connection between your evidence and your claim. It's the logical explanation of why the evidence supports your claim. This involves interpreting the data, explaining patterns, and drawing inferences. Strong reasoning uses scientific principles, established theories, and logical connections.

Example: "The decrease in tagged sharks, coupled with anecdotal evidence from fishermen, strongly suggests a decline in the tiger shark population. This decline is likely linked to increased human activity in the Great Barrier Reef, including fishing, habitat destruction, and pollution, which negatively impact shark survival and reproduction."

Analyzing Tiger Shark Data: A Case Study

Let's consider a hypothetical scenario involving tiger shark data analysis. We'll construct a CER argument based on this data.

Scenario: Scientists are studying the diet of tiger sharks in a specific region. They collect data on the stomach contents of 20 tiger sharks, recording the weight (in grams) of different prey items found.

Hypothetical Data:

Shark ID	Seal (g)	Turtle (g)	Fish (g)
1	500	0	200
2	800	100	150
3	0	300	500
4	700	0	300
5	600	200	100
6	900	0	0
7	400	150	250
8	1000	0	50
9	550	100	200
10	750	0	250
11	0	400	300
12	600	150	100
13	850	0	150
14	300	200	400
15	100	350	250
16	950	50	0
17	700	100	200
18	500	250	150
19	0	500	0
20	800	0	100

Constructing the CER Argument:

1. Claim: Seals constitute the primary prey item in the diet of tiger sharks in this region.

2. Evidence:

Calculate the total weight of each prey item consumed across all 20 sharks.
Determine the percentage contribution of each prey item to the total prey weight.
Present the data in a clear and concise manner, possibly using a bar graph or table showing the total weight and percentage for each prey type. For example, if the total weight of seals consumed is significantly higher than turtles or fish, this serves as strong evidence.

3. Reasoning:

Explain how the calculated percentages support the claim. For instance, if seals make up 60% of the total prey weight, this indicates they are the dominant prey item.
Discuss any limitations of the study. The sample size (20 sharks) is relatively small, and the study is limited to a single region. Acknowledge these limitations and their potential impact on the conclusion.
Relate the findings to established knowledge about tiger shark diets. Do these findings align with previous research? Are there any potential ecological explanations for the observed prey preference?

Common Pitfalls in CER Analysis

Avoid these mistakes to strengthen your arguments:

Weak Claims: Vague or unspecific claims make your argument ineffective. Ensure your claim is clear, concise, and directly addresses the question at hand.
Insufficient Evidence: Don't rely on a single piece of evidence. Provide multiple, diverse pieces of evidence to bolster your argument.
Irrelevant Evidence: Ensure your evidence directly supports your claim. Avoid including data that is not pertinent to your argument.
Logical Fallacies: Avoid flawed reasoning. Ensure your reasoning is logically sound and based on established principles.
Ignoring Limitations: Acknowledge the limitations of your data and analysis. This demonstrates critical thinking and strengthens the credibility of your argument.

Improving CER Skills: Tips and Strategies

Practice: The more you practice constructing CER arguments, the better you'll become. Work through various examples and receive feedback on your work.
Seek Feedback: Ask peers or instructors to review your CER arguments and provide constructive criticism.
Read Scientific Literature: Study how scientists construct arguments in published research papers. Pay close attention to their use of evidence and reasoning.
Use Visual Aids: Graphs, charts, and tables can effectively communicate your data and enhance your arguments.
Clearly Define Terms: Ensure that all terms and concepts are clearly defined to prevent ambiguity.

Conclusion

CER analysis is an invaluable tool for analyzing data and constructing scientifically sound arguments. By mastering the CER framework and avoiding common pitfalls, you can significantly improve your data interpretation skills and communicate your findings effectively. This comprehensive guide, focusing on tiger shark data as an example, provides a solid foundation for understanding and applying CER analysis in diverse scientific contexts. Remember that meticulous data collection and analysis are paramount to building robust and credible CER arguments. Further research and exploration of specific tiger shark populations will undoubtedly yield more nuanced and detailed understandings of their ecological roles and the threats they face. The application of the CER framework will continue to be essential in interpreting these findings and informing conservation strategies.