Our client Flatiron Insurance Agency, offers a wide variety of property insurance solutions giving a hommeowner the best coverage needed at a discounted premium. Flatiron Insurance Agency is currently dominating the East coast insurance market and wants to make a statement when entering the West Coast market.

In order to meet our clients' expectations, which is to provide the best coverage at a competitive premium. DEE Analytics will conduct an inferential analysis on variables such as bedrooms, bathrooms, sqft_living, floors and/or added features to the house that have a higher correlation to house sale value or price ,than any other house sale predictors.

Questions to consider:

• What are the business's pain points related to this project?
• How did you pick the data analysis question(s) that you did?
• Why are these questions important from a business perspective?

We were provided with a dataset from kc_house_data.csv used for data analysis and modeling. kc_house_data.csv set has 21 columns and ~21,597 entries. As the team explored these entries, we came to the conclussion that not all columns will be useful for our business problem, so we adjusted the Dataset by dropping eight columns that were incomplete or had no significannce for use. We used the remaining columns congruent to our Stakeholder. Describe the data being used for this project.

Questions to consider:

• Where did the data come from, and how do they relate to the data analysis questions?
• What do the data represent? Who is in the sample and what variables are included?
• What is the target variable?
• What are the properties of the variables you intend to use?

One of the first methods used was to looking for any correlation.

Questions to consider:

• How did you prepare, analyze or model the data?
• Why is this approach appropriate given the data and the business problem?

Present your key results. For Phase 1, this will be findings from your descriptive analysis.

Questions to consider:

• How do you interpret the results?
• How confident are you that your results would generalize beyond the data you have?

Here is an example of how to embed images from your sub-folder:

Provide your conclusions about the work you've done, including any limitations or next steps.

Questions to consider:

• What would you recommend the business do as a result of this work?
• What are some reasons why your analysis might not fully solve the business problem?
• What else could you do in the future to improve this project?

Please review our full analysis in our Jupyter Notebook or our presentation.

For any additional questions, please contact name & email, name & email

Describe the structure of your repository and its contents, for example:

├── README.md                           <- The top-level README for reviewers of this project
├── dsc-phase1-project-template.ipynb   <- Narrative documentation of analysis in Jupyter notebook
├── DS_Project_Presentation.pdf         <- PDF version of project presentation
├── data                                <- Both sourced externally and generated from code
└── images                              <- Both sourced externally and generated from code