Intuition for Variance












1












$begingroup$


Say $X$ is a random variable with a binomial distribution where $n = 3$ and $p = 0.5$, eg. the number of heads we get when we flip a coin three times.



So this distribution has the values -




  • $0$ with probability $frac{1}{8}$

  • $1$ with probability $frac{3}{8}$

  • $2$ with probability $frac{3}{8}$

  • $3$ with probability $frac{1}{8}$


The mean is $1.5$.



Now if I calculate the second moment, ie. the variance, $E[X^2]$ I get the value $3$. This seems to say that the distribution 'spreads' from $0$ to $3$.



Now if I calculate the variance about the mean, $E[(X - E[X])^2]$ I get the value $0.75$. What does this figure of $0.75$ mean? Intuitively I would have expected this value to be $1.5$, as in the distribution spreads from the mean value of $1.5$ to $0$, and to $3$, ie. it spreads out $1.5$ in each direction about the mean...so how do I interpret this seemingly arbitrary value of $0.75$?










share|cite|improve this question









$endgroup$












  • $begingroup$
    The second moment is not the same thing as the variance. The variance is the central second moment, which is, as you write, $Eleft[(X-E[X])^{2}right]$. The "uncentered" second moment $Eleft[ X^2right]$ is something else.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:51










  • $begingroup$
    How does this sound to you: en.wikipedia.org/wiki/…
    $endgroup$
    – Hoda
    Jan 31 '14 at 19:53










  • $begingroup$
    @Unwisdom What does the uncentered second moment mean? How do I interpret the value of $3$ that I get for it?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 19:53








  • 1




    $begingroup$
    You are right that the variance is a measure of how much the distribution spreads out. The range is another such measure. The two quantities (range and variance) don't tell you the same thing, but they are at least a little bit similar. It's a bit like the mean and the median. They aren't the same thing, but they measure aspects of a distribution that are somewhat related. I mention the range because of your comment "This seems to say that the distribution 'spreads' from 0 to 3." In fact, the range of this distribution is 3, and that is the thing telling you that it spreads from 0 to 3.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:56






  • 1




    $begingroup$
    The uncentered second moment is just the usual second moment: $Eleft[X^{2}right]$. Subtracting the mean from a random variable is sometimes called centering: the resulting variable has a mean of 0. The centered second moment is the (uncentered) second moment of $X-E[X]$.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:58
















1












$begingroup$


Say $X$ is a random variable with a binomial distribution where $n = 3$ and $p = 0.5$, eg. the number of heads we get when we flip a coin three times.



So this distribution has the values -




  • $0$ with probability $frac{1}{8}$

  • $1$ with probability $frac{3}{8}$

  • $2$ with probability $frac{3}{8}$

  • $3$ with probability $frac{1}{8}$


The mean is $1.5$.



Now if I calculate the second moment, ie. the variance, $E[X^2]$ I get the value $3$. This seems to say that the distribution 'spreads' from $0$ to $3$.



Now if I calculate the variance about the mean, $E[(X - E[X])^2]$ I get the value $0.75$. What does this figure of $0.75$ mean? Intuitively I would have expected this value to be $1.5$, as in the distribution spreads from the mean value of $1.5$ to $0$, and to $3$, ie. it spreads out $1.5$ in each direction about the mean...so how do I interpret this seemingly arbitrary value of $0.75$?










share|cite|improve this question









$endgroup$












  • $begingroup$
    The second moment is not the same thing as the variance. The variance is the central second moment, which is, as you write, $Eleft[(X-E[X])^{2}right]$. The "uncentered" second moment $Eleft[ X^2right]$ is something else.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:51










  • $begingroup$
    How does this sound to you: en.wikipedia.org/wiki/…
    $endgroup$
    – Hoda
    Jan 31 '14 at 19:53










  • $begingroup$
    @Unwisdom What does the uncentered second moment mean? How do I interpret the value of $3$ that I get for it?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 19:53








  • 1




    $begingroup$
    You are right that the variance is a measure of how much the distribution spreads out. The range is another such measure. The two quantities (range and variance) don't tell you the same thing, but they are at least a little bit similar. It's a bit like the mean and the median. They aren't the same thing, but they measure aspects of a distribution that are somewhat related. I mention the range because of your comment "This seems to say that the distribution 'spreads' from 0 to 3." In fact, the range of this distribution is 3, and that is the thing telling you that it spreads from 0 to 3.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:56






  • 1




    $begingroup$
    The uncentered second moment is just the usual second moment: $Eleft[X^{2}right]$. Subtracting the mean from a random variable is sometimes called centering: the resulting variable has a mean of 0. The centered second moment is the (uncentered) second moment of $X-E[X]$.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:58














1












1








1


2



$begingroup$


Say $X$ is a random variable with a binomial distribution where $n = 3$ and $p = 0.5$, eg. the number of heads we get when we flip a coin three times.



So this distribution has the values -




  • $0$ with probability $frac{1}{8}$

  • $1$ with probability $frac{3}{8}$

  • $2$ with probability $frac{3}{8}$

  • $3$ with probability $frac{1}{8}$


The mean is $1.5$.



Now if I calculate the second moment, ie. the variance, $E[X^2]$ I get the value $3$. This seems to say that the distribution 'spreads' from $0$ to $3$.



Now if I calculate the variance about the mean, $E[(X - E[X])^2]$ I get the value $0.75$. What does this figure of $0.75$ mean? Intuitively I would have expected this value to be $1.5$, as in the distribution spreads from the mean value of $1.5$ to $0$, and to $3$, ie. it spreads out $1.5$ in each direction about the mean...so how do I interpret this seemingly arbitrary value of $0.75$?










share|cite|improve this question









$endgroup$




Say $X$ is a random variable with a binomial distribution where $n = 3$ and $p = 0.5$, eg. the number of heads we get when we flip a coin three times.



So this distribution has the values -




  • $0$ with probability $frac{1}{8}$

  • $1$ with probability $frac{3}{8}$

  • $2$ with probability $frac{3}{8}$

  • $3$ with probability $frac{1}{8}$


The mean is $1.5$.



Now if I calculate the second moment, ie. the variance, $E[X^2]$ I get the value $3$. This seems to say that the distribution 'spreads' from $0$ to $3$.



Now if I calculate the variance about the mean, $E[(X - E[X])^2]$ I get the value $0.75$. What does this figure of $0.75$ mean? Intuitively I would have expected this value to be $1.5$, as in the distribution spreads from the mean value of $1.5$ to $0$, and to $3$, ie. it spreads out $1.5$ in each direction about the mean...so how do I interpret this seemingly arbitrary value of $0.75$?







probability statistics probability-distributions






share|cite|improve this question













share|cite|improve this question











share|cite|improve this question




share|cite|improve this question










asked Jan 31 '14 at 19:47









sonicboomsonicboom

3,69582853




3,69582853












  • $begingroup$
    The second moment is not the same thing as the variance. The variance is the central second moment, which is, as you write, $Eleft[(X-E[X])^{2}right]$. The "uncentered" second moment $Eleft[ X^2right]$ is something else.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:51










  • $begingroup$
    How does this sound to you: en.wikipedia.org/wiki/…
    $endgroup$
    – Hoda
    Jan 31 '14 at 19:53










  • $begingroup$
    @Unwisdom What does the uncentered second moment mean? How do I interpret the value of $3$ that I get for it?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 19:53








  • 1




    $begingroup$
    You are right that the variance is a measure of how much the distribution spreads out. The range is another such measure. The two quantities (range and variance) don't tell you the same thing, but they are at least a little bit similar. It's a bit like the mean and the median. They aren't the same thing, but they measure aspects of a distribution that are somewhat related. I mention the range because of your comment "This seems to say that the distribution 'spreads' from 0 to 3." In fact, the range of this distribution is 3, and that is the thing telling you that it spreads from 0 to 3.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:56






  • 1




    $begingroup$
    The uncentered second moment is just the usual second moment: $Eleft[X^{2}right]$. Subtracting the mean from a random variable is sometimes called centering: the resulting variable has a mean of 0. The centered second moment is the (uncentered) second moment of $X-E[X]$.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:58


















  • $begingroup$
    The second moment is not the same thing as the variance. The variance is the central second moment, which is, as you write, $Eleft[(X-E[X])^{2}right]$. The "uncentered" second moment $Eleft[ X^2right]$ is something else.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:51










  • $begingroup$
    How does this sound to you: en.wikipedia.org/wiki/…
    $endgroup$
    – Hoda
    Jan 31 '14 at 19:53










  • $begingroup$
    @Unwisdom What does the uncentered second moment mean? How do I interpret the value of $3$ that I get for it?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 19:53








  • 1




    $begingroup$
    You are right that the variance is a measure of how much the distribution spreads out. The range is another such measure. The two quantities (range and variance) don't tell you the same thing, but they are at least a little bit similar. It's a bit like the mean and the median. They aren't the same thing, but they measure aspects of a distribution that are somewhat related. I mention the range because of your comment "This seems to say that the distribution 'spreads' from 0 to 3." In fact, the range of this distribution is 3, and that is the thing telling you that it spreads from 0 to 3.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:56






  • 1




    $begingroup$
    The uncentered second moment is just the usual second moment: $Eleft[X^{2}right]$. Subtracting the mean from a random variable is sometimes called centering: the resulting variable has a mean of 0. The centered second moment is the (uncentered) second moment of $X-E[X]$.
    $endgroup$
    – Unwisdom
    Jan 31 '14 at 19:58
















$begingroup$
The second moment is not the same thing as the variance. The variance is the central second moment, which is, as you write, $Eleft[(X-E[X])^{2}right]$. The "uncentered" second moment $Eleft[ X^2right]$ is something else.
$endgroup$
– Unwisdom
Jan 31 '14 at 19:51




$begingroup$
The second moment is not the same thing as the variance. The variance is the central second moment, which is, as you write, $Eleft[(X-E[X])^{2}right]$. The "uncentered" second moment $Eleft[ X^2right]$ is something else.
$endgroup$
– Unwisdom
Jan 31 '14 at 19:51












$begingroup$
How does this sound to you: en.wikipedia.org/wiki/…
$endgroup$
– Hoda
Jan 31 '14 at 19:53




$begingroup$
How does this sound to you: en.wikipedia.org/wiki/…
$endgroup$
– Hoda
Jan 31 '14 at 19:53












$begingroup$
@Unwisdom What does the uncentered second moment mean? How do I interpret the value of $3$ that I get for it?
$endgroup$
– sonicboom
Jan 31 '14 at 19:53






$begingroup$
@Unwisdom What does the uncentered second moment mean? How do I interpret the value of $3$ that I get for it?
$endgroup$
– sonicboom
Jan 31 '14 at 19:53






1




1




$begingroup$
You are right that the variance is a measure of how much the distribution spreads out. The range is another such measure. The two quantities (range and variance) don't tell you the same thing, but they are at least a little bit similar. It's a bit like the mean and the median. They aren't the same thing, but they measure aspects of a distribution that are somewhat related. I mention the range because of your comment "This seems to say that the distribution 'spreads' from 0 to 3." In fact, the range of this distribution is 3, and that is the thing telling you that it spreads from 0 to 3.
$endgroup$
– Unwisdom
Jan 31 '14 at 19:56




$begingroup$
You are right that the variance is a measure of how much the distribution spreads out. The range is another such measure. The two quantities (range and variance) don't tell you the same thing, but they are at least a little bit similar. It's a bit like the mean and the median. They aren't the same thing, but they measure aspects of a distribution that are somewhat related. I mention the range because of your comment "This seems to say that the distribution 'spreads' from 0 to 3." In fact, the range of this distribution is 3, and that is the thing telling you that it spreads from 0 to 3.
$endgroup$
– Unwisdom
Jan 31 '14 at 19:56




1




1




$begingroup$
The uncentered second moment is just the usual second moment: $Eleft[X^{2}right]$. Subtracting the mean from a random variable is sometimes called centering: the resulting variable has a mean of 0. The centered second moment is the (uncentered) second moment of $X-E[X]$.
$endgroup$
– Unwisdom
Jan 31 '14 at 19:58




$begingroup$
The uncentered second moment is just the usual second moment: $Eleft[X^{2}right]$. Subtracting the mean from a random variable is sometimes called centering: the resulting variable has a mean of 0. The centered second moment is the (uncentered) second moment of $X-E[X]$.
$endgroup$
– Unwisdom
Jan 31 '14 at 19:58










1 Answer
1






active

oldest

votes


















0












$begingroup$

I find the variance easier to understand in terms of the standard deviation. The variance is basically "the average squared distance between the observations and the mean", but that is not a very intuitive measure of variation in the observations. If you take the square root of the variance, you will get the standard deviation, which is therefore "the average distance between the observations and the mean".



So the value of 0.75 is easier to interpret in terms of the std. deviation $sqrt{0.75}approx 0.87$. This number tells you that on average the observations are $0.87$ units away from the mean.






share|cite|improve this answer









$endgroup$









  • 3




    $begingroup$
    "The average distance between observarion and mean" would be mean absolute deviation (or $0$ if you consider sign), not standard deviation
    $endgroup$
    – Luis Mendo
    Jan 31 '14 at 20:24












  • $begingroup$
    I thought a standard deviation of $0.87$ would mean that 68% of the observations were within a distance of $0.87$ from the mean?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 20:33










  • $begingroup$
    Luis: Checking your link, you seem to be right -- perhaps "a typical distance bewteen the observations and the mean" would have been a better description.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:45










  • $begingroup$
    Sonicboom: Only if the distribution is normal. It won't necessarily be true for arbitrary distributions.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:46











Your Answer





StackExchange.ifUsing("editor", function () {
return StackExchange.using("mathjaxEditing", function () {
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
});
});
}, "mathjax-editing");

StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "69"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);

StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});

function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
noCode: true, onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});


}
});














draft saved

draft discarded


















StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f658828%2fintuition-for-variance%23new-answer', 'question_page');
}
);

Post as a guest















Required, but never shown

























1 Answer
1






active

oldest

votes








1 Answer
1






active

oldest

votes









active

oldest

votes






active

oldest

votes









0












$begingroup$

I find the variance easier to understand in terms of the standard deviation. The variance is basically "the average squared distance between the observations and the mean", but that is not a very intuitive measure of variation in the observations. If you take the square root of the variance, you will get the standard deviation, which is therefore "the average distance between the observations and the mean".



So the value of 0.75 is easier to interpret in terms of the std. deviation $sqrt{0.75}approx 0.87$. This number tells you that on average the observations are $0.87$ units away from the mean.






share|cite|improve this answer









$endgroup$









  • 3




    $begingroup$
    "The average distance between observarion and mean" would be mean absolute deviation (or $0$ if you consider sign), not standard deviation
    $endgroup$
    – Luis Mendo
    Jan 31 '14 at 20:24












  • $begingroup$
    I thought a standard deviation of $0.87$ would mean that 68% of the observations were within a distance of $0.87$ from the mean?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 20:33










  • $begingroup$
    Luis: Checking your link, you seem to be right -- perhaps "a typical distance bewteen the observations and the mean" would have been a better description.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:45










  • $begingroup$
    Sonicboom: Only if the distribution is normal. It won't necessarily be true for arbitrary distributions.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:46
















0












$begingroup$

I find the variance easier to understand in terms of the standard deviation. The variance is basically "the average squared distance between the observations and the mean", but that is not a very intuitive measure of variation in the observations. If you take the square root of the variance, you will get the standard deviation, which is therefore "the average distance between the observations and the mean".



So the value of 0.75 is easier to interpret in terms of the std. deviation $sqrt{0.75}approx 0.87$. This number tells you that on average the observations are $0.87$ units away from the mean.






share|cite|improve this answer









$endgroup$









  • 3




    $begingroup$
    "The average distance between observarion and mean" would be mean absolute deviation (or $0$ if you consider sign), not standard deviation
    $endgroup$
    – Luis Mendo
    Jan 31 '14 at 20:24












  • $begingroup$
    I thought a standard deviation of $0.87$ would mean that 68% of the observations were within a distance of $0.87$ from the mean?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 20:33










  • $begingroup$
    Luis: Checking your link, you seem to be right -- perhaps "a typical distance bewteen the observations and the mean" would have been a better description.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:45










  • $begingroup$
    Sonicboom: Only if the distribution is normal. It won't necessarily be true for arbitrary distributions.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:46














0












0








0





$begingroup$

I find the variance easier to understand in terms of the standard deviation. The variance is basically "the average squared distance between the observations and the mean", but that is not a very intuitive measure of variation in the observations. If you take the square root of the variance, you will get the standard deviation, which is therefore "the average distance between the observations and the mean".



So the value of 0.75 is easier to interpret in terms of the std. deviation $sqrt{0.75}approx 0.87$. This number tells you that on average the observations are $0.87$ units away from the mean.






share|cite|improve this answer









$endgroup$



I find the variance easier to understand in terms of the standard deviation. The variance is basically "the average squared distance between the observations and the mean", but that is not a very intuitive measure of variation in the observations. If you take the square root of the variance, you will get the standard deviation, which is therefore "the average distance between the observations and the mean".



So the value of 0.75 is easier to interpret in terms of the std. deviation $sqrt{0.75}approx 0.87$. This number tells you that on average the observations are $0.87$ units away from the mean.







share|cite|improve this answer












share|cite|improve this answer



share|cite|improve this answer










answered Jan 31 '14 at 20:17









René B. ChristensenRené B. Christensen

47049




47049








  • 3




    $begingroup$
    "The average distance between observarion and mean" would be mean absolute deviation (or $0$ if you consider sign), not standard deviation
    $endgroup$
    – Luis Mendo
    Jan 31 '14 at 20:24












  • $begingroup$
    I thought a standard deviation of $0.87$ would mean that 68% of the observations were within a distance of $0.87$ from the mean?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 20:33










  • $begingroup$
    Luis: Checking your link, you seem to be right -- perhaps "a typical distance bewteen the observations and the mean" would have been a better description.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:45










  • $begingroup$
    Sonicboom: Only if the distribution is normal. It won't necessarily be true for arbitrary distributions.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:46














  • 3




    $begingroup$
    "The average distance between observarion and mean" would be mean absolute deviation (or $0$ if you consider sign), not standard deviation
    $endgroup$
    – Luis Mendo
    Jan 31 '14 at 20:24












  • $begingroup$
    I thought a standard deviation of $0.87$ would mean that 68% of the observations were within a distance of $0.87$ from the mean?
    $endgroup$
    – sonicboom
    Jan 31 '14 at 20:33










  • $begingroup$
    Luis: Checking your link, you seem to be right -- perhaps "a typical distance bewteen the observations and the mean" would have been a better description.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:45










  • $begingroup$
    Sonicboom: Only if the distribution is normal. It won't necessarily be true for arbitrary distributions.
    $endgroup$
    – René B. Christensen
    Jan 31 '14 at 20:46








3




3




$begingroup$
"The average distance between observarion and mean" would be mean absolute deviation (or $0$ if you consider sign), not standard deviation
$endgroup$
– Luis Mendo
Jan 31 '14 at 20:24






$begingroup$
"The average distance between observarion and mean" would be mean absolute deviation (or $0$ if you consider sign), not standard deviation
$endgroup$
– Luis Mendo
Jan 31 '14 at 20:24














$begingroup$
I thought a standard deviation of $0.87$ would mean that 68% of the observations were within a distance of $0.87$ from the mean?
$endgroup$
– sonicboom
Jan 31 '14 at 20:33




$begingroup$
I thought a standard deviation of $0.87$ would mean that 68% of the observations were within a distance of $0.87$ from the mean?
$endgroup$
– sonicboom
Jan 31 '14 at 20:33












$begingroup$
Luis: Checking your link, you seem to be right -- perhaps "a typical distance bewteen the observations and the mean" would have been a better description.
$endgroup$
– René B. Christensen
Jan 31 '14 at 20:45




$begingroup$
Luis: Checking your link, you seem to be right -- perhaps "a typical distance bewteen the observations and the mean" would have been a better description.
$endgroup$
– René B. Christensen
Jan 31 '14 at 20:45












$begingroup$
Sonicboom: Only if the distribution is normal. It won't necessarily be true for arbitrary distributions.
$endgroup$
– René B. Christensen
Jan 31 '14 at 20:46




$begingroup$
Sonicboom: Only if the distribution is normal. It won't necessarily be true for arbitrary distributions.
$endgroup$
– René B. Christensen
Jan 31 '14 at 20:46


















draft saved

draft discarded




















































Thanks for contributing an answer to Mathematics Stack Exchange!


  • Please be sure to answer the question. Provide details and share your research!

But avoid



  • Asking for help, clarification, or responding to other answers.

  • Making statements based on opinion; back them up with references or personal experience.


Use MathJax to format equations. MathJax reference.


To learn more, see our tips on writing great answers.




draft saved


draft discarded














StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f658828%2fintuition-for-variance%23new-answer', 'question_page');
}
);

Post as a guest















Required, but never shown





















































Required, but never shown














Required, but never shown












Required, but never shown







Required, but never shown

































Required, but never shown














Required, but never shown












Required, but never shown







Required, but never shown







Popular posts from this blog

android studio warns about leanback feature tag usage required on manifest while using Unity exported app?

SQL update select statement

'app-layout' is not a known element: how to share Component with different Modules