KANDA DATA

  • Home
  • About Us
  • Contact
  • Sitemap
  • Privacy Policy
  • Disclaimer
  • Bimbingan Online Kanda Data
Menu
  • Home
  • About Us
  • Contact
  • Sitemap
  • Privacy Policy
  • Disclaimer
  • Bimbingan Online Kanda Data
Home/Statistics/How to Distinguish Cross-Section Data, Time Series Data, and Panel Data

Blog

53,793 views

How to Distinguish Cross-Section Data, Time Series Data, and Panel Data

By Kanda Data / Date Jul 28.2023
Statistics

Based on the collection method, data can be divided into cross-section, time series, and panel data. A good understanding of the differences between the three types and how to collect the three types of data will lead to the right choice of analysis.

In testing the research hypothesis, we will carry out a series of data collection and analysis stages. Furthermore, based on the results of data collection and analysis, the results of statistical hypothesis testing from our study can be seen.

Cross-section, time series, and panel data differ in how the data is analyzed. Therefore, to choose the correct data analysis, we need to understand the different ways of collecting cross-sections, time series, and panel data.

Cross-Section Data (Definition and Example)

Cross-section data is collected from several observation units/individuals/subjects at one time period. This observation unit can include data on farmers, breeders, consumers, companies, and other data. As for one time period, namely data collected in one time period, for example, data collected in the last 1 year or data on current existing conditions.

An example is a researcher conducting research on the effect of fertilizer and seed inputs on rice production. The researcher then collected 250 farmers as a unit of observation. Data on the amount of fertilizer, seed, and rice production were collected based on data from the last harvest period. This researcher collects data called cross-section data.

This cross-section data is generally obtained from survey research activities in the field. In cross-sectional data, researchers can explore many variables that will be used according to research objectives.

In this case, the researcher limits the variables to be measured in the study. Thus, complete and detailed data can be obtained following the research objectives in cross-sectional data.

However, in carrying out data collection, researchers or enumerators need to have the same perception of the questionnaire instrument and have skills in conducting good interviewing techniques for respondents.

Pages: 1 2 3
Tags: 4 types of data in econometrics, cross-section data, econometrics, Kanda data, panel data, panel data differences from time series data, statistics, time series data

Related posts

Differences in Nominal, Ordinal, Interval, and Ratio Data Measurement Scales for Research

Date Jan 23.2026

Reasons Why the R-Squared Value in Time Series Data Is Higher Than in Cross-Section Data

Date Dec 24.2025

How to Create a Research Location Map in Excel: District, Province, and Country Maps

Date Oct 07.2025

Leave a Reply Cancel reply

You must be logged in to post a comment.

Categories

  • Article Publication
  • Assumptions of Linear Regression
  • Comparison Test
  • Correlation Test
  • Data Analysis in R
  • Econometrics
  • Excel Tutorial for Statistics
  • Multiple Linear Regression
  • Nonparametric Statistics
  • Profit Analysis
  • Regression Tutorial using Excel
  • Research Methodology
  • Simple Linear Regression
  • Statistics

Popular Post

January 2026
M T W T F S S
 1234
567891011
12131415161718
19202122232425
262728293031  
« Dec    
  • Differences in Nominal, Ordinal, Interval, and Ratio Data Measurement Scales for Research
  • Reasons Why the R-Squared Value in Time Series Data Is Higher Than in Cross-Section Data
  • How to Create a Research Location Map in Excel: District, Province, and Country Maps
  • How to Determine the Minimum Sample Size in Survey Research to Ensure Representativeness
  • Regression Analysis for Binary Categorical Dependent Variables
Copyright KANDA DATA 2026. All Rights Reserved