The Difference Between Mean and Median — Which One Should You Use in Your Research?

One of the most common yet important questions in data analysis is:

“Should I use the mean or the median to summarize my data?”

Although both represent measures of central tendency, the choice between them depends on the nature of your data and the objective of your analysis. Selecting the wrong measure can lead to misinterpretation and potentially incorrect conclusions in your research.

The Difference Between Mean and Median

What Is the Mean?

The mean (or average) is calculated by summing all data values and dividing by the number of observations.

For example:

(10 + 12 + 14 + 15 + 16) ÷ 5 = 13.4

The mean provides an overall picture of your dataset and works well when data are normally distributed and free from outliers.

When to Use the Mean:

• Works best with normally distributed data

• Suitable for inferential statistical analyses such as t-tests, ANOVA, or regression

• When there are no extreme or outlier values in the dataset

Limitation:If the dataset contains extreme values (e.g., one value much higher than others), the mean can be skewed, failing to represent the true central trend of the data.

What Is the Median?

The median represents the middle value when data are arranged from smallest to largest.

For example:

Data: 10, 12, 14, 15, 100 → the median is 14

When to Use the Median:

• Not affected by outliers or extreme values

• Works well with skewed data distributions

• Ideal for variables such as income, price, satisfaction scores, or response times

• Represents a robust central trend even when outliers exist

Limitation:The median does not account for all data points in the dataset. Therefore, it may not be suitable for advanced statistical comparisons or equations that require continuous measurement precision.

Why You Should Use Data Investigator

Choosing the right statistical measure involves more than just formulas — it requires a deep understanding of data structure, distribution, and analytical purpose.

With over 15 years of experience in academic, business, and medical research, Data Investigator is your trusted partner in professional statistical analysis.

Our Expertise Includes:

• Professional data analysis using SPSS

• Checking data distribution and recommending whether to use mean or median

• Performing descriptive and inferential statistical analyses accurately

• Providing detailed explanations and interpretation of statistical results

• Issuing an official Certificate of Statistical Analysis

Whether you are a graduate student, medical researcher, or government agency,Data Investigator is your reliable partner for accurate, trustworthy, and professional data analysis at every step.

For more information, please contact:

E-mail: info@datainvestigatorth.com

Line: @datainvestigator