Introduction to Data Science Databases Paper
Description
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Data 1501: Introduction to Data Science
Midterm Project
Objective:
The purpose of this project is to assess your ability to apply the data science concepts and methods you have learned throughout the course using a real-world scenario. For the midterm project, you will only demonstrate your understanding and application of the concepts covered in the first half of the semester. These are:
- Understand the problem you are seeking to solve.
- Formulate a problem statement that is clear, concise, and measurable.
- Define the dependent and independent variables in the data.
- Assess, diagnose, and clean the data.
- Perform a univariate analysis on the quantitative variables.
- Perform a univariate analysis on the categorical variables.
- Assess the potential relationships between each independent variable and the dependent variable.
- Bivariate analysis with one categorical variable and one quantitative variable
- Bivariate analysis with two quantitative variables
- Identify the strongest potential relationships that you would like to investigate further.
- Brainstorm any new variables (or features) you could create using the original data.
Overview:
Imagine you are a data science consultant and you have just been hired by a real estate company to complete an analysis project. You walk in on the first day to get the run-down of why you have been hired. After sitting in on meeting after meeting, listening to the key stakeholders, and asking lots of questions, this is what you walk away with…
You are told by numerous people that they are having a hard time accurately pricing houses. Often, they price houses too low. While they sell quickly, they are not maximizing the profit for themselves and their clients. Other times, they price them too high. The downside in this situation is the house sits on the market for a while, which costs money, and they ultimately lower the prices or spend a lot of time negotiating with potential buyers. In either case, they are missing out on potential earnings.
Currently, they do not have a structured way to come up with a house price other than looking at comparable homes in the area using FMLS (the professional ‘Zillow’ for real estate agents), getting an inspection, and simply using their instincts and past experience to come up with what they feel is an accurate price. It would be very helpful if they could more accurately predict the listing price. In addition, they would love to know what the key features (or variables) are that increase the value of a home. With this information, they could better direct clients on what renovations they should do to increase the value of their home and earn more money.
Understanding what increases the value of a home and having the ability to accurately predict the selling price will allow the company to better serve their clients and increase their revenue.
Using the information above, your analysis, and the assigned data, come up with a solution to serve your client’s needs.
How to Approach the Completion of the Project:
- The Midterm Analysis should already have been attempted. You have been chipping away at it little by little with each homework and lab.
- That said, if you made mistakes on your lab and homework assignments, they need to be corrected in the midterm. Use your rubric feedback to ensure you are meeting all the criteria.
- If you did not complete a lab or homework assignment, it must be completed in the midterm for credit.
- If you have been staying on top of your work throughout the semester, all you have to do now is compile your analysis into a cohesive report that highlights what you did and what it means.
- Use the “Midterm Sample Report” as a guide for completing and assembling your report.
- Have fun and enjoy this learning opportunity!
Deliverables:
- A SINGLE complete excel workbook containing complete and corrected work from lab/homeworks (Understanding the Problem and the Data, Data Diagnosis and Cleaning, Univariate Exploratory Analysis, and Bivariate Exploratory Analysis)
- Organize a word document with the following section headings:
- Understand the Problem:
Write a brief synopsis of your understanding of the client’s problem.
- Problem Statement:
Provide your problem statement that is clear, concise, and measurable.
c. Assess the Data:
Include a picture of the formatted metadata table/data dictionary you created.
d. Diagnose the Data:
Include a picture of the diagnostics table you created.
- Clean the Data:
Provide a write-up of the decisions you made to clean the data.
- Univariate Quantitative Analysis:
Include pictures of the table and graphs you created for each univariate quantitative analysis. Include your brief write up of each variable below its respective graphs.
- Univariate Categorical Analysis:
Include pictures of the tables and graphs you created for each univariate categorical analysis. Include your brief write up of each variable below its respective tables and graphs.
- Bivariate Each Categorical and the Target Analysis:
Include pictures of the table and graph you created for your analysis. Include your brief write-up of each relationship below its respective table and graph.
- Bivariate Each Quantitative and the Target Analysis:
Include pictures of the matrix table and graphs you created for your analysis. Include your brief write up of each relationship below its respective graph.
- Bivariate Relationships:
Based on your analysis write a summary paragraph highlighting the relationships you suspect to be the strongest and why
- Variable (Feature) Creation:
Write a summary paragraph highlighting the possible variables that could be created with the original data.
- Your Word document must be neatly formatted with a title page and page numbers. It is expected that students will write in complete, well-structured sentences. It is important to proofread your work for spelling and grammatical errors before submitting it.
- Your Excel workbook must also be neatly formatted like the lecture workbook you created in class. It must be easy to find the information.
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