This chapter, "Data Collection, Verification, and Analysis," represents the cornerstone of the real estate valuation process, forming the scientific basis upon which the fair value of the property is estimated. Without accurate and reliable data, the valuation becomes mere speculation unsupported by evidence, thus losing its credibility and value.
The scientific importance of this chapter lies in its grounding in the principles and methodologies of scientific research. Data collection requires following systematic and objective methods to ensure the comprehensiveness of the information and its representation of reality. Data verification represents a practical application of the concept of scientific accuracy, where information is examined and its validity and reliability are confirmed before being used in the analysis. Data analysis is the core of the valuation process, where statistical and economic methods are used to extract indicators and relationships that affect the value of the property.
This chapter will cover the basic stages of the data collection process and the evaluation of its quality, starting with identifying the types of data required and their different sources, through the available data collection methods, and ending with techniques for verifying the validity and reliability of the data. It will also address the statistical and economic methods used in real estate data analysis, and how to use these analyses in estimating the value of the property.
The chapter aims to provide trainees with the knowledge and skills necessary to:
1. Identify the types of real estate data required, distinguishing between market data, physical data, legal data, and other types of data related to real estate valuation.
2. Identify reliable data sources, recognizing the official and unofficial sources of real estate data and evaluating the reliability of each source.
3. Apply different data collection methods, using questionnaires, interviews, field observations, databases, and other methods to collect real estate data.
4. Verify the validity and reliability of data by applying auditing and matching techniques, verifying sources, and comparing with historical data to ensure data accuracy.
5. Analyze real estate data using statistical and economic methods, using averages, standard deviations, regression, comparative analysis, and other methods to extract indicators and relationships that affect the value of the property.
6. Evaluate the quality of data and its impact on the valuation process, understanding the importance of data quality in obtaining an accurate and reliable valuation of the property, and identifying potential sources of errors in the data and their impact on the results.