This project aims to explore the integration of economic theory and data analytics practices. By combining concepts learned in economics classes with practical data analysis skills acquired through the Google Data Analytics Advanced Course, this project will provide insights into economic phenomena using statistical methods and data-driven approaches.
- Combine Economic Theory and Data Analytics: Leverage economic principles to analyze real-world data, enhancing understanding of both fields.
- Apply Statistical Techniques: Utilize statistics, probability, and other analytical methods to interpret data effectively.
- Conduct Exercises: Implement exercises from the Google Data Analytics course to reinforce learning and apply theoretical knowledge.
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Economic Theory Application:
- Explore key economic concepts such as supply and demand, market structures, and consumer behavior.
- Analyze how these theories can be applied to current economic data.
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Data Analytics Techniques:
- Use statistical analysis to uncover trends and patterns in economic data.
- Implement various data visualization techniques to present findings clearly.
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Statistical Methods:
- Apply descriptive and inferential statistics to interpret data.
- Conduct probability analysis to assess risks and uncertainties in economic scenarios.
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Exercises from Google Data Analytics Course:
- Incorporate practical exercises that enhance analytical skills, including data cleaning, exploratory data analysis (EDA), and predictive modeling.
- Programming Languages: Python or R for data manipulation and analysis.
- Data Visualization Tools: Matplotlib, Seaborn, Tableau for presenting insights.