<p><em>This is really more of a statistical question (except perhaps the bit about APA style). As such it probably belongs on <a href="https://stats.stackexchange.com/">stats.stackexchange.com</a> .</em></p>

<p>A binary variable does not have a "<a href="http://en.wikipedia.org/wiki/Normal_distribution" rel="nofollow noreferrer">normal distribution</a>". A normal distribution is bell shaped and is relevant to continuous data.</p>

<p>Your null hypothesis is that the population proportions for left and right handers are equal. Thus, if your chi-square value is sufficiently large, then you might reject the null hypothesis and conclude that the population proportions are unequal.</p>

<p>If $k$ is the number of categories (you have two categories), then 
degrees of freedom for the one sample chi-square test is $k-1$ (i.e., $2-1 = 1$).</p>

<p><a href="http://www.une.edu.au/WebStat/unit_materials/c6_common_statistical_tests/chi_square_ex_2.html" rel="nofollow noreferrer">To calculate chi-square check out the example here</a>.</p>

<p>The following formula in Excel should give you a p-value. For example if your chi-square value was 22, and your degrees of freedom was 3: </p>

<pre><code> =1-CHISQ.DIST(22, 3,TRUE)
</code></pre>

<ul>
<li>the first argument is the chi-square value</li>
<li>The second argument is the degrees of freedom</li>
<li>The third argument indicates that a cumulative distribution (CDF) is desired</li>
<li>Thus by taking 1 minus the value of the CDF you get the probability of getting a chi-square value as large or larger than the observed value.</li>
</ul>

<p>You can check your formula by looking at existing calculated tables. 
<a href="http://home.comcast.net/~sharov/PopEcol/tables/chisq.html" rel="nofollow noreferrer">http://home.comcast.net/~sharov/PopEcol/tables/chisq.html</a></p>

CC BY-SA 3.0
2013-03-11T11:30:11.993Z
2013-03-11T11:35:22.127Z
2017-04-13T12:44:18.443Z
Jeromy Anglim
<p>I am trying to understand the statistical test of the chi-square in Excel. I already made the test but I still don't know how to compute the χ² value and what it means, how to compute the degrees of freedom and how to write a propper APA approved result section. Can anyone help me and explain this in a simple way? </p>

<p>I have a population of n=76. 'Left' = 25 and 'Right' = 51. The hypothesis is you would expect a normal distribution ('Left' =38 and 'Right' = 38). So the question is 'is this distribution a coincidence?' The p &lt; .029. By seeing this outcome I thought there is that is no coincidence that there isn't a normal distribution and it must be due to a variable. </p>

<p>Is it true in this case the degress of freedom is just n-1? </p>

<methodology><statistics>
How to compute Chi-square value and degrees of freedom in Excel?
NinaM
# How to compute Chi-square value and degrees of freedom in Excel?

(Asked by: username_0 on 2013-03-11)

I am trying to understand the statistical test of the chi-square in Excel. I already made the test but I still don't know how to compute the χ² value and what it means, how to compute the degrees of freedom and how to write a propper APA approved result section. Can anyone help me and explain this in a simple way?

I have a population of n=76. 'Left' = 25 and 'Right' = 51. The hypothesis is you would expect a normal distribution ('Left' =38 and 'Right' = 38). So the question is 'is this distribution a coincidence?' The p < .029. By seeing this outcome I thought there is that is no coincidence that there isn't a normal distribution and it must be due to a variable.

Is it true in this case the degress of freedom is just n-1?

**Tags:** methodology, statistics


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## 1 answers

### Answer by username_1 on 2013-03-11. Score: 2 | Accepted answer

This is really more of a statistical question (except perhaps the bit about APA style). As such it probably belongs on stats.stackexchange.com .
A binary variable does not have a "normal distribution". A normal distribution is bell shaped and is relevant to continuous data.
Your null hypothesis is that the population proportions for left and right handers are equal. Thus, if your chi-square value is sufficiently large, then you might reject the null hypothesis and conclude that the population proportions are unequal.
If $k$ is the number of categories (you have two categories), then 
degrees of freedom for the one sample chi-square test is $k-1$ (i.e., $2-1 = 1$).
To calculate chi-square check out the example here.
The following formula in Excel should give you a p-value. For example if your chi-square value was 22, and your degrees of freedom was 3: 
 =1-CHISQ.DIST(22, 3,TRUE)


the first argument is the chi-square value
The second argument is the degrees of freedom
The third argument indicates that a cumulative distribution (CDF) is desired
Thus by taking 1 minus the value of the CDF you get the probability of getting a chi-square value as large or larger than the observed value.

You can check your formula by looking at existing calculated tables. 
http://home.comcast.net/~sharov/PopEcol/tables/chisq.html


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