Learning outcomes

In this chapter, you will learn how to

• contrast time series, cross-sectional and panel data;

• calculate measures of central tendency, of dispersion, of skewness and of kurtosis for a given series;

• calculate measures of association between series;

• test hypotheses about the mean of a series by calculating test statistics and forming confidence intervals;

• interpret p-values; and

• discuss the most common pitfalls that can occur in the analysis of real estate data.

Types of data for quantitative real estate analysis

There are broadly three types of data that can be employed in quantitative analysis of real estate problems: time series data, cross-sectional data and panel data. Each of these types of data is now described, with examples of how and why they might be used.

Time series data

Time series data, as the name suggests, are data that have been collected over a period of time on one or more variables. Time series data have associated with them a particular frequency of observation or collection of data points. The frequency is simply a measure of the interval over, or the regularity with which, the data are collected or recorded. Box 3.1 shows some examples of time series data.

It is also generally a requirement that all data used in a model be of the same frequency of observation.