Here at SurveyMonkey, our goal isn’t just to give you the results to your survey. We want to help you understand them, so that you can make better decisions based on those results.

Sometimes, just looking at a data table or a bar chart won’t reveal the whole story behind your data. The task gets even harder if you have a lot of answer options in your question, or if you’re trying to compare the results for one group of respondents against another.

That’s why we’re excited to announce our new **Basic Statistics** feature, which gives you a holistic understanding of your results in seconds.

**Basic Statistics**, which displays **mean**, **median**, **maximum**, **minimum**, and **standard deviation** alongside your results, is available on all multiple-choice questions including the Matrix/Rating Scale questions—and it’s also a great way to understand your Numerical Textbox results.

So let’s take a look at the numbers included in **Basic Statistics**, determine what those numbers mean, and learn how to display them alongside your survey responses.

#### Basic Statistics: Getting started

As an example, let’s say we’ve asked our audience about their satisfaction with our business using a Likert Scale**** question from the SurveyMonkey Question Bank. When we go to **Analyze**, the results look like this:

Though we can see that there were a lot of diverse responses, and we know the exact number of responses for each answer option, can we easily tell the overall answer to this question? Probably not.

This is where **Basic Statistics** can help. To turn on the **Basic Statistics** feature, use the standard customization features for your question. (Click the **Customize** button at the top right of the question.)

On the **Display Options** tab, you will find a set of checkboxes listed under **Show**, including a checkbox for **Basic Statistics**. By clicking the **Basic Statistics** checkbox and then clicking **Save**, you will see the new **Basic Statistics** table displayed under the response data table for your question.

In our example, our results with **Basic Statistics** showing look like this:

#### What’s in Basic Statistics?

The** Basic Statistics** table includes the **m****inimum**, **m****aximum**, **median**, **mean**, and **standard deviation** for this question. To help you understand the statistics, we assign a number to each answer option, and display those in parentheses next to the labels.

The **minimum** and **m****aximum** **show the lowest and highest number answer option that received at least one response**. (In the above example, the min and max of 1 and 7 show that there were 6 responses in the top answer—Extremely satisfied—and 2 responses in the bottom answer—Extremely dissatisfied.) This can be helpful to quickly see the range of your answers.

**Median** and **mean** give you a quick summary of your results. Using the numbers assigned to the answer options, the **mean gives the average of all responses**.

The **median represents the answer option in the middle of all your responses**, meaning there are an equal number of responses above and below that answer option.

In this case, a mean of 3.71 shows that overall your respondents came in somewhere between **Somewhat satisfied**, and the neutral **Neither satisfied nor dissatisfied**. However, there’s some nuance to the numbers when it comes to mean and median.

The median of 4 (higher than the 3.71 mean) shows that the answers are about evenly distributed between positive (more satisfied) and negative (less satisfied) responses. The difference between the mean and median shows that even though about equal number of respondents said they were overall satisfied and overall dissatisfied, there were more respondents who were extremely satisfied* *than respondents who were extremely dissatisfied*.*

Finally, the **standard deviation shows the spread or variation of your responses**. The higher your standard deviation, the greater your variance—meaning, the further your responses are from the mean (average) of your results.

In our example, we have a standard deviation of 1.71, which means that 68% of our responses are plus or minus 1.71 from the mean. With this information, we can expect 68% of our responses to be between 2 and 5.4.

Generally speaking, numbers within one standard deviation of the mean will encompass 68% of your respondents and numbers within two standard deviations of the mean will encompass 96% of your respondents. So, if you have a small standard deviation, more of your responses will be clustered around the mean. If you have a large standard deviation, your responses will be more spread out.

#### Basic Statistics + Compare = Awesome data analysis

As you can see, **Basic Statistics** gives you a full picture of your results pretty quickly. But the numbers become even more powerful if you are using **Compare** rules to compare results across different respondent groups.

For example, let’s say in our survey we asked respondents their gender. Now we can set up a **Compare** rule to see the differences in results for female vs. male respondents. When we turn on **Compare**, we will now see a **Basic Statistics** data table that looks like this:

In this example, the responses of men and women are not much different, but you can quickly see that:

- The maximum is different. None of your female respondents answered Extremely dissatisfied.
- While the median and mean are almost identical, the standard deviation is twice as high for the men. That means that, though overall the men and women felt the same way, the female responses were all bunched around the mean responses (neutral) while the male responses were spread more to the extremes of the answer options.

**Basic Statistics** is also very useful for understanding numerical responses. To see **Basic Statistics** for a numerical question, you need to use the **Multiple Textbox** question type when creating your survey, and check the checkbox for **Only Allow Numerical Data**.

For example, let’s say we wanted to know how many times our respondent had seen two movies (Star Wars and Twilight). Our results look like this:

Clearly, our respondents have seen Star Wars more than Twilight, but that’s about all we know.

However, if we turn on **Basic Statistics** for the question, we also get this data:

Now you can see that, though the mean is much higher for Star Wars than for Twilight, the median is the same (1). That means that the people who have seen Star Wars more than once have seen it more times than the people who have seen Twilight more than once.

Sure enough, when we look at the maximum for each movie, we can see that at least one person has seen Star Wars 50 times, while no one has seen Twilight more than 3 times.

If we compare the answers for men and women, we get even more detail:

Now we can see that the difference between Star Wars and Twilight came from our male respondents. (Our female respondents have all only seen Star Wars 0, 1, or 2 times.)

With the new **Basic Statistics** feature, you can understand your results faster and more fully. So sit back, relax, and let us do the math for you. You’ll have a more robust analysis to include in your reports—and you’ll be able to make even smarter decisions based on your data.

*How will you use Basic Statistics? Have any questions for us? Let us know in the Comments below!*