Compare the Difference Between Similar Terms

Difference Between Time Series and Cross Sectional Data

The key difference between time series and cross sectional data is that the time series data focuses on the same variable over a period of time while the cross sectional data focuses on several variables at the same point of time. Furthermore, the time series data consist of observations of a single subject at multiple time intervals whereas, the cross sectional data consist of observations of many subjects at the same point in time.

Fields such as Statistics, Econometrics gathers data and analyze them. Data is a vital aspect of activities such as for research, predictions and proving theories. There are various types of data. Two of them are time series and cross sectional data.

CONTENTS

1. Overview and Key Difference
2. What is Time Series Data
3. What is Cross Sectional Data
4. Side by Side Comparison – Time Series vs Cross Sectional Data in Tabular Form
5. Summary

What is Time Series Data?

Time series data focuses on observations of a single individual at different times usually at uniform intervals. It is the data of the same variable over a period of time such as months, quarters, years etc. The time series data takes the form of Xt. The t represents the time. Below is an example of the profit of an organization over a period of 5 years’ time. Profit is the variable that changes each year.

Usually, time series data is useful in business applications. Time measurement can be months, quarters or years but it can also be any time interval. Generally, the time has uniform intervals.

What is Cross Sectional Data?

In cross sectional data, there are several variables at the same point in time. Data set with maximum temperature, humidity, wind speed of few cities on a single day is an example of a cross sectional data.

Another example is the sales revenue, sales volume, number of customers and expenses of an organization in the past month. Cross sectional data takes the form of Xi. Expanding the data from several months will convert the cross sectional data to time series data.

What is the Difference Between Time Series and Cross Sectional Data?

Time series data consist of observations of a single subject at multiple time intervals. Cross sectional data consist of observations of many subjects at the same point in time. Time series data focuses on the same variable over a period of time. On the other hand, cross sectional data focuses on several variables at the same point in time. This is the main difference between time series and cross sectional data.

Profit of an organization over a period of 5 years’ time is an example for a time series data while maximum temperature of several cities on a single day is an example for a cross sectional data.

Summary – Time Series vs Cross Sectional Data

The difference between time series and cross sectional data is that time series data focuses on the same variable over a period of time while cross sectional data focuses on several variables at the same point of time. Different data types use different analyzing methods. Therefore, it is important to identify the correct type of the data.

Reference:

1.“Cross-Sectional Data.” Wikipedia, Wikimedia Foundation, 26 May 2018. Available here