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Ayush Tamang

4 years agoPosted 4 years ago. Direct link to Ayush Tamang's post “I still don't get how to ...”

I still don't get how to find the MAD, can anyone pls help me

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(27 votes)

Siddharth Ranjan

4 years agoPosted 4 years ago. Direct link to Siddharth Ranjan's post “find the MAD by 1. find...”

find the MAD by

1. finding the mean(average) of the set of numbers

2. find the distance of all the numbers from the mean.

3. Find the mean of those numbers.(101 votes)

Sneha123

(Video) Mean absolute deviation | Data and statistics | 6th grade | Khan Academy4 years agoPosted 4 years ago. Direct link to Sneha123's post “Wait, so we have to find ...”

Wait, so we have to find the mean and then the absolute value right?

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(23 votes)

Rohit

3 years agoPosted 3 years ago. Direct link to Rohit's post “Is there an easier way to...”

Is there an easier way to calculate MAD? So much writing!

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(7 votes)

Dr. Smartie

4 months agoPosted 4 months ago. Direct link to Dr. Smartie's post “Well, we can solve the wr...”

Well, we can solve the writing problem by doing mental math, but we can't solve the easy way part.

(0 votes)

adavis

4 years agoPosted 4 years ago. Direct link to adavis's post “but how do you do these t...”

but how do you do these things and not get them wrong:{

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(1 vote)

(Video) Mean absolute deviation example | Data and statistics | 6th grade | Khan AcademyJerry Nilsson

4 years agoPosted 4 years ago. Direct link to Jerry Nilsson's post “There are a lot of calcul...”

There are a lot of calculations and it's easy to get one wrong.

Be patient, take your time, and never assume you got it right on your first try.(19 votes)

ansel.edison

4 years agoPosted 4 years ago. Direct link to ansel.edison's post “Is this different from st...”

Is this different from standard deviation? I find that I get different answers from both, but they seem like the same concept. Can you please explain the difference and purpose of each?

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(9 votes)

Insatiable

3 years agoPosted 3 years ago. Direct link to Insatiable's post “There was a distinction m...”

There was a distinction made between a sample variance/standard deviation and a population variance/standard deviation. The population variance is calculated by taking the sum of the squared deviations from each data point to the population mean, and then dividing by the number of data points in the population. On the other hand, the sample variance goes through the same process as above, except it's with respect to the sample mean, and you should also divide by one less than the number of data points in your sample, to correct the bias (Bessel's Correction). I'm wondering if a similar notion exists for the Mean Absolute Deviation (MAD)? In other words, whether it's a sample or population we're dealing with, is there any significant difference in the way that the MAD is calculated for either of them?

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(6 votes)

joshua

9 months agoPosted 9 months ago. Direct link to joshua's post “what how to do it”

(Video) Mean Absolute Deviation (MAD) | Math with Mr. Jwhat how to do it

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(2 votes)

Neal

9 months agoPosted 9 months ago. Direct link to Neal's post “Mean Absolute Deviation (...”

Mean Absolute Deviation (MAD) is a way to measure how spread out a set of data is.

The first step is to calculate the mean (average) of the set of data. If we have the set of data [-1,2,3,7,9,12,17], the mean would be [-1+2+3+7+9+12+17] / 7, so 7 is the mean.

The second step is to measure how far each point of data is from the mean, so [7-(-1)] + [7-2] + [7-3] + [7-7] + [7-9] + [7-12] + [7-17]. If we have a number that is bigger than the mean, like 9,12, and 17 in this case, we take the absolute value, so usually 7-9 = -2 (but with absolute value) 2.

The third step is to add all the values above, and divide them by

the number of data points, so 7. Eventually, we get : 34/7, or [4 6/7]

Hope this helps.(8 votes)

Monika

7 years agoPosted 7 years ago. Direct link to Monika's post “I still don't under stand...”

I still don't under stand how you come up with the two different data sets do I split my data in half?

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(0 votes)

Mr. Mitchell

7 years agoPosted 7 years ago. Direct link to Mr. Mitchell's post “Sal uses two completely d...”

Sal uses two completely different data sets to show how MAD describes the variability of a single data set.

2,2,4,4 - number of donuts I ate each of the last four days

1,1,6,4 - number of times I scored in my last four soccer games

Both data sets have a mean of 3. On average, I eat 3 donuts a day, and score 3 goals per game [I wish].

The MAD of the donut data is 1, showing that I am pretty consistent on eating donuts. The average day is 2 to 4 donuts (1 donut more or less than 3).

However, The MAD of the soccer data is 2, showing that there is more variability in my goal scoring. An average game is 1 to 5 goals (2 goals more or less than 3).(13 votes)

(Video) Mean Absolute Deviation ( MAD )

Dojo Cat

8 months agoPosted 8 months ago. Direct link to Dojo Cat's post “Ummm. Do the numbers in a...”

Ummm. Do the numbers in a data set need to be ordered? Thanks...................

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(3 votes)

David Severin

8 months agoPosted 8 months ago. Direct link to David Severin's post “It is not necessary in th...”

It is not necessary in this case, the statistic that is easiest to do by ordering is the median (middle number). To find the mean, order does not matter because addition is commutative, and order may help to find the mode (number with the most results), but it does not matter for MAD either. On the other hand, it never hurts to order the data for convenience and possibly easier calculations.

(3 votes)

Sandy670803

4 years agoPosted 4 years ago. Direct link to Sandy670803's post “what does the ratio diffe...”

what does the ratio difference in means/mean absolute deviation tell you about how much visual overlap there is between two distributions with similar variations?

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(3 votes)

## Video transcript

- [Voiceover] Let's say that I've got two different data sets. The first data set, I have two, another two, a four, and a four. And then, in the otherdata set, I have a one. We'll do this on theright side of the screen. A one, a one, a six, and a four. Now, the first thing Iwanna think about is, "Well, how do I ... "Is there a number that can give me "a measure of center ofeach of these data sets?" And one of the ways thatwe know how to do that is by finding the mean. So let's figure out the meanof each of these data sets. This first data set, the mean ... Well, we just need to sumup all of the numbers. That's gonna be two plus two plus four plus four. And then we're gonna divide by the number of numbers that we have. So we have one, two, three, four numbers. That's that four right over there. And this is going to be,two plus two is four, plus four is eight, plus four is 12. This is gonna be 12 over four, which is equal to three. Actually, let's see ifwe can visualize this a little bit on a number line. Actually I'll do kind of a ... I'll do a little bit of a dot plot here so we can see all of the values. If this is zero, one, two, three, four, and five. We have two twos. Why don't I just do ... So for each of these twos ... Actually, I'll just do it in yellow. So I have one two, thenI have another two. I'm just gonna do a dot plot here. Then I have two fours. So, one four and anotherfour, right over there. And we calculated that the mean is three. The mean is three. A measure of centraltendency, it is three. So I'll just put three right over here. I'll just mark it with that dotted line. That's where the mean is. All right. Well, we'vevisualized that a little bit. That does look like it's the center. It's a pretty ... It makes sense. So now let's look at thisother data set right over here. The mean, the mean over here is going to be equal to one plus one plus six plus four, all of that over, we stillhave four data points. And this is two plus six is eight, plus four is 12, 12 divided by four ... This is also three. So this also has the same mean. We have different numbers, but we have the same mean. But there's something about this data set that feels a little bitdifferent about this. And let's visualize it, to see if we can see a difference. Let's see if we can visualize it. I have to go all the way up to six. Let's say this is zero, one, two, three, four, five, six, and I'll go one more, seven. So we have a one. We have a one, we have another one. We have a six. And then we have a four. And we calculated that the mean is three. So we calculated that the mean is three. So the mean is three. When we measure it by the mean, the central point, ormeasure of that central point which we use as the mean, well, it looks the same, butthe data sets look different. How do they look different? Well, we've talked about notions of variability or variation. And it looks like this dataset is more spread out. It looks like the datapoints are on average further away from the mean than these data points are. That's an interesting question that we ask ourselves in statistics. We just don't want a measureof center, like the mean. We might also want ameasure of variability. And one of the more straightforward ways to think about variability is, well, on average, how farare each of the data points from the mean? That might sound a little complicated, but we're gonna figure out what that means in a second, (chortles) notto overuse the word "mean." So we wanna figure out, on average, how far each of thesedata points from the mean. And what we're about to calculate, this is called Mean Absolute Deviation. Absolute Deviation. Mean Absolute Deviation, or if you just use the acronym, MAD, mad, for Mean Absolute Deviation. And all we're talking about, we're gonna figure out howmuch do each of these points, their distance, so absolute deviation. How much do the deviate from the mean, but the absolute of it? So each of these points at two, they are one away from the mean. Doesn't matter if they're less or more. They're one away from the mean. And then we find the meanof all of the deviations. So what does that mean? (chuckles) I'm using the word "mean," using it a little bit too much. So let's figure out theMean Absolute Deviation of this first data set. We've been able to figureout what the mean is. The mean is three. So we take each of the data points and we figure out, what's its absolutedeviation from the mean? So we take the first two. So we say, two minus the mean. Two minus the mean, and wetake the absolute value. So that's its absolute deviation. Then we have another two, so we find that absolutedeviation from three. Remember, if we're justtaking two minus three, taking the absolute value, that's just saying its absolute deviation. How far is it from three? It's fairly easy tocalculate in this case. Then we have a four and another four. Let me write that. Then we have the absolute deviation of four from three, from the mean. Then plus, we have another four. We have this other four right up here. Four minus three. We take the absolute value, because once again,it's absolute deviation. And then we divide it, and then we divide it by thenumber of data points we have. So what is this going to be? Two minus three is negative one, but we take the absolute value. It's just going to be one. Two minus three is negative one. We take the absolute value. It's just gonna be one. And you see that here visually. This point is just one away. It's just one away from three. This point is just one away from three. Four minus three is one. Absolute value of that is one. This point is just one away from three. Four minus three, absolute value. That's another one. So you see in this case, every data point was exactly one away from the mean. And we took the absolute value so that we don't have negative ones here. We just care how far itis in absolute terms. So you have four data points. Each of their absolutedeviations is four away. So the mean of the absolute deviations are one plus one plus one plus one, which is four, over four. So it's equal to one. One way to think about it is saying, on average, the mean of thedistances of these points away from the actual mean is one. And that makes sense because all of these are exactly one away from the mean. Now, let's see how, what results we get for thisdata set right over here. And I'll do it ... Let me actually get some space over here. At any point, if you get inspired, I encourage you to calculate the Mean Absolute Deviation on your own. So let's calculate it. The Mean Absolute Deviation here, I'll write MAD, is going to be equal to ... Well, let's figure outthe absolute deviation of each of these points from the mean. It's the absolute valueof one minus three, that's this first one, plus the absolute deviation, so one minus three, that's the second one, then plus the absolutevalue of six minus three, that's the six, then we have the four, plus the absolute valueof four minus three. Then we have four points. So one minus three is negative two. Absolute value is two. And we see that here. This is two away from three. We just care about absolute deviation. We don't care if it's tothe left or to the right. Then we have another oneminus three is negative two. It's absolute value, so this is two. That's this. This istwo away from the mean. Then we have six minus three. Absolute value of thatis going to be three. And that's this right over here. We see this six is three to the right of the mean. We don't care whether it'sto the right or the left. And then four minus three. Four minus three is one,absolute value is one. And we see that. It is one to the right of three. And so what do we have? We have two plus two is four, plus three is seven, plus one is eight, over four, which is equal to two. So the Mean Absolute Deviation ... Let me write it down. It fell off over here. Here, for this data set, the Mean AbsoluteDeviation is equal to two, while for this data set, the Mean AbsoluteDeviation is equal to one. And that makes sense. They have the exact same means. They both have a mean of three. But this one is more spread out. The one on the right is more spread out because, on average, each of these points are two away from three, while on average, each of these points are one away from three. The means of the absolutedeviations on this one is one. The means of the absolutedeviations on this one is two. So the green one is morespread out from the mean.

## FAQs

### How do you find the mean absolute deviation MAD? ›

Step 1: Calculate the mean. Step 2: Calculate how far away each data point is from the mean using positive distances. These are called absolute deviations. Step 3: Add those deviations together.

**How do you find median absolute deviation and MAD? ›**

**To use the formula and find the MAD, take the following steps.**

- Order the numbers in the data set and find the median.
- Subtract the median from each number in the data set.
- Take the absolute value of each difference.
- Add up all of the positive differences.
- Divide this sum by the number of data points in the set.

**What is the mean absolute deviation quizlet? ›**

Terms in this set (7)

**the DIFFERENCE between one set of values and some fixed value, usually the mean of the set**. mean absolute deviation. one measure of variability; the average of how much the individual scores of a data set differ from the mean of the set. - abbreviation: MAD.

**What is mean absolute deviation 7th grade math? ›**

Mean absolute deviation (MAD) of a data set is **the average distance between each data value and the mean**. Mean absolute deviation is a way to describe variation in a data set. Mean absolute deviation helps us get a sense of how "spread out" the values in a data set are.

**How to calculate mean deviation? ›**

Mean deviation from mean : σ=√∑fd2∑f−(∑fd∑f)2×i=√35450−(2450)2×10=√35450−5762500×10=√6.85×10=26.17MDσ=∑f|d|N=998.450=19.968.

**What is the difference between standard deviation and mean absolute deviation? ›**

While both measures rely on the deviations from the mean (x - \bar{x}), **the MAD uses the absolute values of the deviations and the standard deviation uses the squares of the deviations**. Both methods result in non-negative differences. The MAD is simply the mean of these nonnegative (absolute) deviations.

**What is an example of mean absolute deviation? ›**

Example: Mean Absolute Deviation About the Mean

Now we start with a different data set: 1, 1, 4, 5, 5, 5, 5, 7, 7, 10. Just like the previous data set, the mean of this data set is 5. Thus the mean absolute deviation about the mean is **18/10 = 1.8**.

**What is a good mean absolute deviation? ›**

A small mean absolute deviation tells us that most of the data values are very close to the mean (since the expected distance from each data value to the mean is small). **A high mean absolute deviation tells us that many of the data values are spread out further from the mean**.

**Can the mean absolute deviation be negative? ›**

Absolute deviation-The absolute deviation of a data value from the mean is the distance that the data value is away from the mean of the data set. Because it is a distance, **absolute deviation cannot be negative**. You find it by taking the absolute value of the deviation of the data value.

**What is the relationship between MAD and standard deviation? ›**

The Mean Absolute Deviation (MAD) and Standard Deviation (STD) are both ways to measure the dispersion in a set of data. The MAD describes what the expected deviation is whereas the STD is a bit more abstract.

### What is mean absolute deviation around median? ›

The Mean Absolute Deviation Around the Median is **a measure of dispersion of a set of data points**. It is used in place of the Median Absolute Deviation (Around the Median) as it returns a smoother curve.

**What is median absolute deviation MAD in Matlab? ›**

Description. **y = mad( X ) returns the mean absolute deviation of the values in X** . If X is a vector, then mad returns the mean or median absolute deviation of the values in X . If X is a matrix, then mad returns a row vector containing the mean or median absolute deviation of each column of X .

**How do you find the MAD step by step? ›**

Take each number in the data set, subtract the mean, and take the absolute value. Then take the sum of the absolute values. Now compute the mean absolute deviation by dividing the sum above by the total number of values in the data set. Finally, round to the nearest tenth.

**What is the easiest way to find the mean? ›**

It's obtained by simply **dividing the sum of all values in a data set by the number of values**.

**How do you find the absolute value? ›**

To find the absolute value of any real number, first locate the number on the real line. **The absolute value of the number is defined as its distance from the origin**. For example, to find the absolute value of 7, locate 7 on the real line and then find its distance from the origin.

**What is the use of the mean absolute deviation MAD quizlet? ›**

The mean absolute deviation is designed to **provide a measure of overall forecast error for the model**. It does this by taking the sum of the absolute values of the individual forecast errors and dividing by the number of data periods.

**What is the definition of the mean absolute deviation Quizizz? ›**

The absolute value of the mean. **The variation of data values around the mode**. **The rage distance between the data values and the mean**. Q.

**What is the primary purpose of the mean absolute deviation? ›**

The main purpose of the mean absolute deviation is **to measure the accuracy of the forecast**. By averaging the deviation, the probability of an accurate forecast is increased.

**What is mean absolute deviation for kids? ›**

mean absolute deviation. • **the average of how much the individual scores of a data set**. **differ from the mean of the set**.

**What is the mean absolute deviation of the data set 7 10 14 and 20? ›**

And the answer for this is **12.75**.

### What grade level is mean absolute deviation? ›

Math, **Grade 6**, Distributions and Variability, An Introduction To Mean Absolute Deviation (MAD) | OER Commons.

**What is mean deviation with example? ›**

We know that the procedure to calculate the mean deviation. Therefore, the mean value is 6. Now, the obtained data set is 1, 3, 1, 2, 2, 3. Hence, the mean deviation for 5, 3,7, 8, 4, 9 is 2.

**What is the first step when calculating the mean absolute deviation? ›**

To find the mean absolute deviation of the data, start by finding the mean of the data set. Find the sum of the data values, and divide the sum by the number of data values. Find the absolute value of the difference between each data value and the mean: |data value – mean|.

**How do you find the deviation between two values? ›**

**To calculate the standard deviation of those numbers:**

- Work out the Mean (the simple average of the numbers)
- Then for each number: subtract the Mean and square the result.
- Then work out the mean of those squared differences.
- Take the square root of that and we are done!

**Should I use standard deviation or mean absolute deviation? ›**

**The mean average, or mean absolute deviation, is considered the closest alternative to standard deviation**. It is also used to gauge volatility in markets and financial instruments, but it is used less frequently than standard deviation.

**Is mean absolute deviation variance? ›**

The absolute deviation, variance and standard deviation are such measures. **The absolute and mean absolute deviation show the amount of deviation (variation) that occurs around the mean score**. To find the total variability in our group of data, we simply add up the deviation of each score from the mean.

**What is the difference between mean absolute deviation MAD and mean squared error MSE )? ›**

Answer and Explanation: Thus, **MAD gives all errors equal weightage (i.e linear) while MSE weights error according to their squares**. Thus if there are periods which have large errors, these will get magnified in MSE.

**Is mean absolute deviation a measure of dispersion? ›**

**The mean absolute deviation was used as a measure of dispersion in the past, but then fell into disuse**. It has the disadvantage that, unlike the standard deviation (σ), it cannot be readily 'plugged' into the normal distribution formulae.

**Do you want a lower or higher mean absolute deviation? ›**

The larger the MAD, the greater variability there is in the data (the data is more spread out). The MAD helps determine whether the set's mean is a useful indicator of the values within the set. **The larger the MAD, the less relevant is the mean as an indicator of the values within the set**.

**What does the MAD tell you about a data set? ›**

Mean absolute deviation (MAD) is a measure of the average absolute distance between each data value and the mean of a data set. Similar to standard deviation, MAD is a parameter or statistic that measures the spread, or variation, in your data.

### What is a good deviation value? ›

Statisticians have determined that values **no greater than plus or minus 2 SD** represent measurements that are are closer to the true value than those that fall in the area greater than ± 2SD. Thus, most QC programs require that corrective action be initiated for data points routinely outside of the ±2SD range.

**Is mean absolute deviation a measure of accuracy? ›**

Mean Absolute Deviation (MAD) **measures the accuracy of the prediction** by averaging the alleged error (the absolute value of each error). MAD is useful when measuring prediction errors in the same unit as the original series[5][6].

**Is mean absolute deviation affected by outliers? ›**

Photo by Randy Fath on Unsplash. Median absolute deviation is a robust way to identify outliers. It replaces standard deviation or variance with median deviation and the mean with the median. The result is a method that **isn't as affected by outliers** as using the mean and standard deviation.

**Is mean absolute deviation resistant to outliers? ›**

**The MAD is resistant to outliers**. The presence of outliers does not change the value of the MAD. In this respect, it is similar to the interquartile range. In contrast, the SD is very sensitive to the presence of outliers.

**How do you find the mean deviation? ›**

Mean deviation from mean : **σ=√∑fd2∑f−(∑fd∑f)2×i**=√35450−(2450)2×10=√35450−5762500×10=√6.85×10=26.17MDσ=∑f|d|N=998.450=19.968.

**How does the mean absolute deviation MAD of the data in set 2? ›**

How does the mean absolute deviation (MAD) of the data in set 2 compare to the mean absolute deviation of the data in set 1? The MAD of set 2 is **13.35 more than the MAD of set 1**.

**What is mean deviation answer? ›**

The mean deviation is defined as **a statistical measure that is used to calculate the average deviation from the mean value of the given data set**.

**What is the difference between mean absolute deviation and standard deviation? ›**

While both measures rely on the deviations from the mean (x - \bar{x}), **the MAD uses the absolute values of the deviations and the standard deviation uses the squares of the deviations**. Both methods result in non-negative differences. The MAD is simply the mean of these nonnegative (absolute) deviations.

**What are the three steps for finding the mean absolute deviation? ›**

**The process for finding the mean absolute deviation involves the following three steps.**

- Calculate the sample average by summing all observations and dividing by the sample size.
- Find the absolute deviation of all data points from the mean. ...
- Calculate the average of the absolute deviations.

**How do you find the mean absolute deviation from a frequency table? ›**

**Mean deviation and frequency distribution**

- Formula: - ∑ f | X-X| / ∑ f.
- where, f is the value of frequency.
- x is the mean, calculated as (sum of all the values/number of values) = ∑ f x / ∑ f.
- mid points are calculated as (lower limit + upper limit) / 2.