INSTRUCTIONS:
- Definitions: Clarify the definition of “deforestation” used in the data (e.g., forest loss, tree cover loss, primary forest loss).
- Spatial Resolution: Consider the scale of analysis (national, regional, local) and the spatial resolution of the data.
- Time Period: Focus on data specifically from 2010 to 2022 for accurate analysis.
-
Research Question:
- This should be clear, focused, and directly address the relationship between deforestation and carbon emissions.
- Example: “To what extent does the rate of deforestation in India (measured by trees cut down per acre) correlate with carbon emission levels from 2010 to 2022?“
-
Introduction:
- Provide background information on deforestation and its impact on carbon emissions.
- Introduce India as a case study.
- Clearly state your research question and its significance.
-
Methodology:
- Explain your data collection process.
- Justify your choice of using Pearson’s Product Moment Correlation Coefficient.
- Outline the statistical analysis steps you will follow.
-
Data Collection and Analysis:
- Present your data in clear tables or graphs.
- Calculate Pearson’s correlation coefficient and interpret the results.
- Discuss any limitations or uncertainties in your data.
-
Evaluation and Conclusion:
- Evaluate the strength and direction of the correlation.
- Discuss the implications of your findings.
- Suggest potential future research directions.
-
Bibliography:
- List all sources used in your research.
Data Collection and Analysis
- Deforestation Rates:
- Obtain data on the number of trees cut down per acre from 2010 to 2022.
- Consider using data from the India State of Forest Reports (ISFR) or Global Forest Watch.
- Carbon Emission Levels:
- Collect data on India’s total carbon emissions from 2010 to 2022.
- Use reliable sources like the Global Carbon Project or the Indian government’s emissions reports.
- Pearson’s Correlation Coefficient:
- Calculate the correlation coefficient using statistical software (e.g., Excel, SPSS, or Python).
- Interpret the coefficient to determine the strength and direction of the relationship.
Key Considerations
- Data Quality: Ensure the accuracy and reliability of your data sources.
- Causation vs. Correlation: Remember that correlation does not imply causation. Other factors may influence both deforestation and carbon emissions.
- Limitations: Acknowledge the limitations of your study, such as data availability or potential biases.
- Clarity and Conciseness: Present your information clearly and concisely, using appropriate graphs and tables.
- Critical Thinking: Demonstrate your ability to analyze and interpret data, drawing meaningful conclusions.
SOURCES:
https://fsi.nic.in/forest-report-2021-details
https://www.globalforestwatch.org/dashboards/country/IND/
https://worldrainforests.com/deforestation/archive/India.htm
https://ourworldindata.org/deforestation
https://climate.nasa.gov/news/1001/landsat-data-yield-best-view-to-date-of-global-forest-losses-gains/#:~:text=Using%20Landsat%20imagery%20and%20cloud,as%20forest%20loss%20and%20gain.
https://www.statista.com/topics/8881/emissions-in-india/
https://www.iea.org/data-and-statistics/data-browser
https://climateactiontracker.org/countries/india/
FIND OTHER SOURCES BY YOURSELF AND USE THEM
ADD IN TEXT CITATIONS
I HAVE ATTACHED A SECOND EXAMPLE OF AN IA BELOW
Please use charts to demonstrate the correlation
Label each graph and each table; 1 GRAPH SHOWING THE CORRELATION WITH STANDARD DEDEVIATION ERROR BARS AND AN ANOVA TABLE AND ANOTHER TABLE SHOWING THE VALUES
USED FOR THE PEARSON CALCULATION
Use in text citations
Add a works cited page
Include your pearson correlation calculations AND ANOVA CALCULATIONS
THE WORKS CITED PAGE IS NOT INCLUDED IN THE WORD COUNT: THE DOCUMENT SHOULD BE NO MORE THAN 2200 WORDS WITHOUT THE WORKS CITED PAGE
THIS IS A TEMPLATE SHOWING THE STRUCTURE OF THE IA: https://www.clastify.com/blog/ess-ia-format-and-structure
THIS IS ALSO AN EXAMPLE OF A PAST IA: https://www.clastify.com/ia/ess/66030d1a60eb6cac1a32f2af
PLEASE MAKE SURE IT IS EXTREMELY DETAILED AND EVERYTHING IS LABELLED PROPERLY
ALSO IN YOUR CONCLUSION INCLUDE LIMITATIONS OF YOUR RESEARCH AND HOW IT COULD BE
IMPROVED AND SHOW HOW THE DATA HAS ALLOWED YOU TO COME TO YOUR CONCLUSION