<p>It sounds like you've basically eyeballed the groups to decide they're similar.  A more advanced way of eyeballing would be to plot the distribution of each characteristic to see how similar they look.</p>

<p>In order to move beyond eyeballing, though, you'd need recourse to statistics.  One common method--that comes up frequently in two-group studies--is to do a statistical test to verify that the groups are similar.</p>

<p>Broadly speaking, you'd look at each characteristic, say height, and assert your hypothesis: average height is the same in both groups.  Then you could do a hypothesis test to see if the average height is actually the same or if it's different.  The specific statistical test you'd use depends on the data in your possession.</p>

<p>For example, see the <a href="https://en.wikipedia.org/wiki/Student%27s_t-test" rel="nofollow">t-test</a> or the <a href="https://en.wikipedia.org/wiki/Chi-squared_test" rel="nofollow">chi-squared</a> test for a difference in means (or just search for "difference in means test").</p>

<p>You'd run the test (statistical software generally has a feature like this) to determine if it shows a significant difference.  If so, you might be comfortable saying the groups are not similar inasmuch as that characteristic (height) is concerned.</p>

<p>Then you'd repeat the procedure for weight and each of the other characteristics.</p>

<p>At the end, many researchers make a little table that shows the $p$-values (which you get from running the test) for each of the characteristics.  This gives your readers the ability to see and decide for themselves whether the groups are similar.</p>

CC BY-SA 3.0
2015-07-21T00:46:08.650Z
In addition to pairwise t-tests I have also seen researchers present a joint F-test of the hypothesis that all the means are the same.
BKay
CC BY-SA 3.0
2015-07-21T08:32:33.643Z
Hi Pat,

This is what I ended up doing in the end. I used Bartlett's test to determine that there was equal variance of each mean per group, and then used a basic two-tailed t-test. It seems to have worked.

Thank you.
Groupsimilarity
CC BY-SA 3.0
2015-07-20T22:37:32.917Z
2015-07-20T22:55:49.020Z
2015-07-20T22:55:49.020Z
Pat W.
<p>I am trying to show that 2 groups of individuals are intrinsically the same. I have various characteristics to measure for both group A and group B, such as height, weight, age, etc. I have taken the averages of both groups, and by inference I can see that they are similar - is there a more robust way of doing this?</p>

CC BY-SA 3.0
2015-07-20T21:05:10.280Z
are you talking about statistically testing a difference in means?
Pat W.
CC BY-SA 3.0
2015-07-20T21:44:11.253Z
I wouldn't say that necessarily.

I literally just want to show that these two groups are similar in terms of all the afore mentioned characteristics.
Groupsimilarity
<microeconomics><econometrics><statistics>
Comparing two groups of individuals
Groupsimilarity
# Comparing two groups of individuals

(Asked by: username_0 on 2015-07-20)

I am trying to show that 2 groups of individuals are intrinsically the same. I have various characteristics to measure for both group A and group B, such as height, weight, age, etc. I have taken the averages of both groups, and by inference I can see that they are similar - is there a more robust way of doing this?

**Tags:** microeconomics, econometrics, statistics
> **Comments:**
> **username_1**: are you talking about statistically testing a difference in means?  
> **username_0**: I wouldn't say that necessarily.  I literally just want to show that these two groups are similar in terms of all the afore mentioned characteristics.  

---

## 1 answers

### Answer by username_1 on 2015-07-20. Score: 2

It sounds like you've basically eyeballed the groups to decide they're similar. A more advanced way of eyeballing would be to plot the distribution of each characteristic to see how similar they look.

In order to move beyond eyeballing, though, you'd need recourse to statistics. One common method--that comes up frequently in two-group studies--is to do a statistical test to verify that the groups are similar.

Broadly speaking, you'd look at each characteristic, say height, and assert your hypothesis: average height is the same in both groups. Then you could do a hypothesis test to see if the average height is actually the same or if it's different. The specific statistical test you'd use depends on the data in your possession.

For example, see the [t-test](https://en.wikipedia.org/wiki/Student%27s_t-test) or the [chi-squared](https://en.wikipedia.org/wiki/Chi-squared_test) test for a difference in means (or just search for "difference in means test").

You'd run the test (statistical software generally has a feature like this) to determine if it shows a significant difference. If so, you might be comfortable saying the groups are not similar inasmuch as that characteristic (height) is concerned.

Then you'd repeat the procedure for weight and each of the other characteristics.

At the end, many researchers make a little table that shows the $p$-values (which you get from running the test) for each of the characteristics. This gives your readers the ability to see and decide for themselves whether the groups are similar.

> **Comments:**
> **username_2**: In addition to pairwise t-tests I have also seen researchers present a joint F-test of the hypothesis that all the means are the same.  
> **username_0**: Hi Pat,  This is what I ended up doing in the end. I used Bartlett's test to determine that there was equal variance of each mean per group, and then used a basic two-tailed t-test. It seems to have worked.  Thank you.  

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