Cross Section Statistics

I will cover the following points.

Cross section statistics. Then they would set up a longitudinal study to study cause and effect. Cross sectional analysis is a type of analysis where an investor analyst or portfolio manager compares a particular company to its industry peers. Cross sectional data are the result of a data collection carried out at a single point in time on a statistical unit.

These subjects are observed in the same time period and irrespective of any distinctions in the time. Cross sectional studies are often used in developmental psychology but this method is also used in many other areas including social science and education. Cross sectional data is a part of cross sectional study.

Data set with maximum temperature humidity wind speed of few cities on a single day is an example of a cross sectional data. Cross sectional vs longitudinal studies. Cross sectional analysis may focus on a single.

In cross sectional data there are several variables at the same point in time. Cross sectional studies can be done more quickly than longitudinal studies. The subjects include firms regions individuals as well as countries.

The analysis might also have no regard to differences in time. The opposite of a cross sectional study is a longitudinal study while cross sectional studies collect data from many subjects at a single point in time longitudinal studies collect data repeatedly from the same subjects over time often focusing on a smaller group of individuals that are connected by a common trait. A cross sectional study involves looking at data from a population at one specific point in time.

That s why researchers might start with a cross sectional study to first establish whether there are links or associations between certain variables. It is a cross section of a study population in econometrics and statistics. With cross sectional data we are not interested in the change of data over.