ABC Real Estate Company renovates and sells houses in different areas of Los Angeles. A sample of 50 houses was selected from their previous years final sales (Date File: CH2). Selling price, size, location (name, population, jobless rate), and type of the houses are included in the dataset. The company would like to use the sample data to determine the average house price in different regions, and whether or not area population and jobless rate play any role in the prices.

Use the methods of descriptive statistics to learn about the ABC Real Estate Companys activities. Include the following in your report.

1. Graphical and numerical summaries to display the scope of companys activities in terms of house sizes, prices, and locations (tables and histograms). Discuss what you learn about the company in terms of its variety of operations.

2. Summarize the frequency, selling price, size (ft2), and price per ft2 for different house types in different neighborhoods. Try to come up with valuable insights. For example, which neighborhood is more expensive; are detached houses on average larger than condominiums, any exceptions, etc. Is there any limitation in extracting insights?

3. Develop scatter diagrams to explore the relationship between the average price and areas characteristics (e.g. population and jobless rate). Use the vertical axis for price. Compute the sample correlation coefficients to support your observations.

4. Is there any linear relationship observable between house sizes and per-ft2 prices? Does it make sense?

Can someone answer in words please! Thank you!

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