Standard Deviation in Excel: STDEV.S vs STDEV.P Explained Simply

When I’m checking sales data to choose the right person for my next project, I don’t look only at the average.

Many times, I see two people with the same average sales.

On paper, they look equally good.

But when I look a little deeper at their monthly numbers, I notice something important.

One person’s sales are steady and consistent every month.

The other person’s sales are very high one month and very low the next.

Even though the average is the same, their performance is clearly different.

So the real question becomes:

• Who is more reliable?
• Who performs more consistently over time?

This is exactly where standard deviation in Excel using STDEV.S and STDEV.P functions becomes powerful.

It helps you measure how far numbers move away from the average and shows whether performance is steady or jumping up and down — something the AVERAGE function alone cannot reveal.

That’s why understanding STDEV.S vs STDEV.P is important when you work with sales, performance, salaries, or any real-life reports.

Let’s break it down – what standard deviation really means in very simple words.

What Is Standard Deviation?

Standard deviation tells you how much your numbers change from the average.

Think of it like this:

• Low standard deviation → numbers stay close to the average
• High standard deviation → numbers move far away from the average

In short:

It tells you if your results are steady or fluctuating.

• If the value is small, your data is stable.
• If the value is big, the numbers are moving a lot.

While the average shows the center, standard deviation shows how tightly or loosely numbers are grouped around it.

If extreme values are disturbing your center point, you might also want to understand how the median works, because it finds the true middle without being affected by big highs or lows.

STDEV.S vs STDEV.P – What’s the Difference?

Excel gives us two standard deviation functions because data is not always complete.

Sometimes you work with part of the data.

Other times you have everything.

Because of this difference, Excel uses two slightly different formulas to calculate standard deviation more accurately.

That’s why we have STDEV.S and STDEV.P.

STDEV.S – Sample Standard Deviation:

Use STDEV.S when your data is a sample.

This means you are working with only a portion, not the entire dataset.

And honestly, this is what happens in most real-life situations.

You usually don’t have every number. You work with what is available and try to understand the bigger picture.

 What “sample” means?

• Some values are missing
• Collecting all data is difficult
• Or You are analyzing a subset

 Common examples of sample data:

• Sales from one branch
• Feedback from some customers
• Marks of a few students
• Performance for limited months

Here, you are estimating trends, not measuring everything.

STDEV.S adjusts the formula to give a better estimate when data is incomplete.

That’s why:

STDEV.S is the most commonly used standard deviation function in Excel.

If you are confused about which one to pick, choose STDEV.S. It is usually the correct choice.

Easy Memory Trick:

S in STDEV.S = Sample

If your data is only a part of something bigger, use STDEV.S.

STDEV.P – Population Standard Deviation

Use STDEV.P when you have all the data, when your list includes every value and nothing is missing.

This means:

• You have all the data
• Nothing is missing
• Every value that exists is included in your calculation

In this case, Excel does not need to estimate anything, because you are measuring the full picture.

Real-life meaning of “population”:

A population means:

• Every value is included
• No estimation is needed
• Excel measures exact variation

You already know everything, so Excel can calculate standard deviation directly.

Common real-life examples of population data:

• Salaries of all employees in a company
• Marks of all students in a class
• Full-year production numbers of a factory
• Daily sales data for every day of the year
• Attendance data for every employee

In these situations, you are not trying to estimate trends —

you are measuring actual variation in the complete dataset.

STDEV.P gives a slightly lower value than STDEV.S because it assumes there is no missing data and no uncertainty.

Simple Way to Remember:

P in STDEV.P = Population

If your data includes everything, use STDEV.P.

Why the Results Are Different:

• STDEV.S assumes the data is incomplete, so it adjusts the calculation.
• STDEV.P assumes the data is complete, so it does not adjust.

So:

• STDEV.S usually returns a slightly higher value
• STDEV.P returns a slightly lower value

Both are correct — they are just used in different situations.

Syntax:

 STDEV.S

=STDEV.S(range)

 STDEV.P

=STDEV.P(range)

You can use:

• cell ranges
• individual numbers
• multiple ranges

Example: Daily Sales Data

Day	Sales
1	100
2	105
3	98
4	102
5	101

Range: B2:B6

Example 1: Using STDEV.S

=STDEV.S(B2:B6)

 Result: 2.588 – A small number

Meaning:

• Sales are very close to each other.
• Performance is stable and consistent.

Example 2: Using STDEV.P:

=STDEV.P(B2:B6)

 Result: 2.315 – Slightly lower than STDEV.S

Why?

• STDEV.P assumes the dataset is complete, so Excel calculates variation without adjustment.
• Easy Comparison: High vs Low Deviation (Made Simple)

Let’s look at two small sets of numbers.

Stable Data (Low Deviation):

100, 101, 99, 102, 98

In this set:

• All values are very close to each other
• The numbers stay near the average
• There are no big jumps or drops

➡ Low standard deviation

➡ Performance is predictable and consistent

This kind of data is common when:

• Sales are steady every month
• Employees perform at a similar level
• Costs remain under control

Unstable Data (High Deviation):

50, 150, 90, 160, 40

In this set:

• Numbers are far apart
• Some values are very high, others very low
• The data jumps up and down a lot

• High standard deviation

• Performance is unpredictable and risky

This often happens when:

•  Sales fluctuate heavily
•  Results depend on chance
•  Performance is inconsistent

What This Tells Us:

Even if both datasets had a similar average, their behavior is very different.

• The average might look fine.

• Standard deviation shows what is really happening.

That’s why standard deviation is so powerful when you want to make smarter decisions based on real data.

If instead you wanted to find the top performer, you might use MAX and MIN.

If you wanted the 2nd or 3rd highest result, then LARGE and SMALL would help.

And if you wanted to assign positions like 1st, 2nd, 3rd, you would use ranking functions in Excel.

But when it comes to consistency, standard deviation is the hero.

Important Things to Know:

• Text and blank cells are ignored
• Only numeric values are used
• Dates are treated as numbers
• A single value returns an error

STDEV.S vs STDEV.P – Quick Table:

Feature	STDEV.S	STDEV.P
Data type	Sample	Full population
Most used	Yes	Less common
Result	Slightly higher	Slightly lower
Best for	Real-world analysis	Complete datasets

In Simple Words:

• Sample → STDEV.S
• Full data → STDEV.P
• Small result → stable
• Big result → fluctuating

Standard deviation helps you judge consistency, not just totals.

And this is why professionals use it for decision-making.

Quick Decision Rule:

Ask yourself:

“Do I have all the data?”

 Yes → STDEV.P

 No or unsure → STDEV.S

Most of the time → it will be STDEV.S.