Types of Data

Overview

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Exercises: min

Questions

Objectives

Cross-Sectional Data

It consists of variables, that are either quantitative or qualitative for a lot of different observations (usually called ‘cases’) and are taken from some defined population. All the cases are registered at a single point in time, or a reasonably short period of time. The techniques commonly used for this kind of data are ‘t-tests’ analysis of variance or regression depending on the kind and number of variables that are there in the data. It is noteworthy that each observation of a given variable or each set of variables are independent of every other observation in the dataset. The independence of the variables is a critical assumption when modelling cross-sectional data.

It is called cross-sectional data because we are measuring a cross-section of a defined population at a particular point in time or a very short period in time.

Time Series Data

If measurement on variables are taken over or through time. Every variable in a time series dataset is measured at equally spaced time intervals. Usually, the observations are not independent of each other in this case. Time series data can be classified into two types other thank the univariate and multivariate distinction and they are discussed in the time series chapter.

Key Points