Learn the difference between mean and median, how they are calculated, and when to use each for analyzing data in BlastPoint
When analyzing data in BlastPoint, you will encounter two key terms: mean and median. Both measures help find the central point in a set of numbers, but they are calculated differently and can provide different insights about your data.
Putting it All Together
- Understand the definition and calculation of mean
- Understand the definition and calculation of median
- Recognize the impact of outliers on mean and median
- Know when to use mean or median for your analysis
Step 1:
Definition: The mean is often called the "average."
Calculation: To find the mean, add up the numbers and divide by how many numbers there are.
Example: For the numbers 1, 2, 3, 4, and 100, the mean is (1+2+3+4+100) / 5 = 22.
Key Point: The mean can be greatly affected by very high or very low numbers (outliers).
Step 2:
Definition: The median is the middle number in a set of numbers when they are sorted from lowest to highest or highest to lowest.
Calculation: If there is an odd number of values, the median is the exact middle number. If there is an even number of values, the median is the average of the two middle numbers.
Example: For the numbers 1, 2, 3, 4, and 100, the median is 3 (the middle number when sorted).
Key Point: The median is less affected by very high or very low numbers (outliers).
Step 3:
Definition: Outliers are data points significantly different from most of the data.
Key Point: Outliers can drastically skew the mean, pulling it towards the extreme value. The median is less sensitive to outliers, considering only the middle value(s).
Step 4:
Use the mean when your data has no outliers and you want to know the average value.
Use the median when your data has very high or very low numbers that could skew the average, and you want a more accurate representation of the typical value.
Conclusion
The BlastPoint platform offers you a convenient way to toggle between these two very important statistics. Understanding the distinction between mean and median is crucial for accurately interpreting and communicating your findings.