Learning Goal: I’m working on a other case study and need the explanation and answer to help me learn.
This project is an opportunity for you to apply the skills you’ve learned in the course Introduction to Data Science Programming. For this project, you will choose a dataset of your choice from and conduct a comprehensive analysis of the data. Your analysis should include data engineering, statistical modeling, and insights on the dataset’s potential applications.
To complete this project, you should first choose a dataset that interests you and has enough information to support your analysis. Once you have chosen your dataset, you should conduct data cleaning and engineering to prepare the data for analysis. After that, you should apply statistical modeling techniques to gain insights and draw conclusions about the data.
In your final report, you should include a detailed description of the dataset, an explanation of the data engineering process, and a discussion of the statistical modeling techniques you used. You should also include your findings and insights, as well as any potential areas for future research.
Overall, this project is an opportunity for you to showcase your data science skills and demonstrate your ability to apply data-driven decision-making to real-world problems. By completing this project, you will gain valuable experience in data engineering, statistical modeling, and data analysis, which will prepare you for future data science projects and career opportunities.
- Project Proposal: Exploring a Dataset
Choose a dataset of your choice from and write a report on how it can be used to make data-driven decisions. In your report, include an overview of the dataset, its sources, and its potential applications. Describe the data engineering and data cleaning processes required to prepare the data for analysis. Identify any statistical modeling techniques that can be applied to the dataset and explain how they can be used to gain insights. Finally, summarize your findings and suggest any possible areas for future research.
- a .Dataset Overview (2 marks)
- b.Data Engineering and Cleaning (3 marks)
- c.Statistical Modeling Techniques (3 marks)
- d.Findings and Insights (1 marks)
- e.Future Research (1 marks)
a.In this section, you should provide a brief description of the dataset you have chosen. Explain the sources of the dataset, its size, format, and any relevant metadata. Discuss why you chose this dataset and what potential applications it has. For example, if you chose a dataset on housing prices, you could discuss how this data could be used to inform real estate investments or policy decisions.
b.In this section, describe the steps you took to prepare the dataset for analysis. Explain how you handled missing data, duplicates, and outliers. Describe any data transformations or feature engineering you performed and why. For example, if you noticed that the dataset had missing values, you could explain how you imputed those values, or if you noticed outliers, you could explain why you removed them.
c.In this section, identify and explain any statistical modeling techniques that can be applied to the dataset. This may include regression analysis, hypothesis testing, clustering, or other methods. Explain how each technique can be used to gain insights into the data and support data-driven decision-making. For example, if you are working with a dataset on customer behavior, you could explain how clustering can be used to group customers with similar characteristics and how this information can be used to develop targeted marketing campaigns.
d.In this section, summarize your findings and insights from your analysis of the dataset. Include any key observations or trends that you discovered and how they relate to the dataset’s potential applications. For example, if you are working with a dataset on public health, you could discuss how your analysis revealed certain risk factors or how certain interventions could be more effective than others.
e.In this section, suggest possible areas for future research based on your analysis of the dataset. Explain why these areas are important and how they could benefit from further analysis. For example, if you are working with a dataset on climate change, you could discuss how future research could focus on predicting the impact of different policy interventions on greenhouse gas emissions.
The dataset we choose I uploaded
you can use excel when cleaning and engineering data put pictures to show and explain what you do in project report
Dont forget the references and no plagirsime