"In the realm of real estate, where comprehensive datasets serve as indispensable tools for unraveling market intricacies, the "realtor-data.csv" file stands out as a trove of information. This dataset meticulously documents over 700,000 real estate listings in the United States, encapsulating essential details in its ten discerning columns. From the current status and architectural specifics to geographical nuances like state, city, and zip code, the dataset provides a comprehensive view of each property. Crucial metrics such as bedrooms, bathrooms, acreage, and living space size lay the foundation for exploring trends within the real estate landscape. As we embark on this analysis, our focus narrows to three key variables bedrooms, state, and price. Through a meticulous examination of these factors, our objective is to unveil insights into how the number of bedrooms and the geographical location, represented by the state, influence housing prices. This study aims to contribute valuable findings for informed decision-making, shedding light on the intricate dynamics that govern the pricing dynamics in the dynamic real estate market."

Conduct the analysis by running data mining strategy that produce defendable and significant results (show step by step in excel): Regression analysis

Using the results of each of the analysis, select and produce at least one MS Excel visualizations that show the significance of the results. Make sure that:

• At least one visual is from Excel
• At least one visual is from Tableau Public

The analyses, the results, and the related visualizations are to be used to produce a persuasive argument in a report that will describe any recommended actions to fully address the problems described in the initial scenario.