Identify the outlier for the given data 34,23,43,28,56,125,52,40,26,24,37,25

Outliers are stragglers — extremely high or extremely low values— in a data set that can throw off your stats. For example, if you were measuring children’s nose length, your average value might be thrown off if Pinocchio was in the class. Contents (Click to skip to the section): • • • Watch the video for the definition and how to find outliers with the IQR and Tukey’s method: An outlier is a piece of data that is an abnormal distance from other points. In other words, it’s data that lies outside the other values in the set. If you had Pinocchio in a class of children, the length of his nose compared to the other children would be an outlier. In this set of random numbers, 1 and 201 are outliers: 1, 99, 100, 101, 103, 109, 110, 201 “1” is an extremely low value and “201” is an extremely high value. Outliers aren’t always that obvious. Let’s say you received the following paychecks last month: $225, $250, $25, $235. Your average paycheck is $135. But that small paycheck ($25) might be because you went on vacation, so a weekly paycheck average of $135 isn’t a true reflection of how much you earned. Your average is actually closer to $237 if you take the outlier ($25) out of the set. Of course, trying to find outliers isn’t always that simple. Your data set may look like this: 61, 10, 32, 19, 22, 29, 36, 14, 49, 3. You could take a guess that 3 might be an outlier and perhaps 61. But you’d be wrong: 61 is the only outlier in this data set. A The outlier on this boxplot is out...

A commonly used rule says that a data point is an outlier if it is more than 1.5 ⋅ IQR 1.5\cdot \text Q 3 ​ + 1 . 5 ⋅ IQR start text, Q, end text, start subscript, 3, end subscript, plus, 1, point, 5, dot, start text, I, Q, R, end text . • Your answer should be • an integer, like 6 6 6 6 • a simplified proper fraction, like 3 / 5 3/5 3 / 5 3, slash, 5 • a simplified improper fraction, like 7 / 4 7/4 7 / 4 7, slash, 4 • a mixed number, like 1 3 / 4 1\ 3/4 1 3 / 4 1, space, 3, slash, 4 • an exact decimal, like 0.75 0.75 0 . 7 5 0, point, 75 • a multiple of pi, like 12 pi 12\ \text 2 / 3 pi 2, slash, 3, space, start text, p, i, end text Check Explain Yes, absolutely. For example, let's consider -19, -1, (0), 5, 7, (9), 12, 12, (12), 13, 13 Low threshold Q1-1.5*(Q3-Q1) = 0 - 1.5*12 = -18. Our min value -19 is less than -18, so it is an outlier. Now, let's shift our numbers in such a way, that there's no more negative numbers: 0, 18, (19), 24, 26, (28), 31, 31, (31), 32, 32 - the same sequence, but with numbers shifted to be positive. Low threshold = Q1 - 1.5*(Q3-Q1) = 19 - 1.5*(31-19) = 19-1.5*12 = 19-18 = 1. Our difference is the same here, -19 - (-18) = 0 - 1 = -1, therefore, negative numbers can be used in our data sets as well as positive. If you think about it, there's no difference in negative or positive numbers as no difference between coordinates on the (x, y) plane. For example, you can get distance between 2 points, doesn't matter where those 2 points lie. This is n...

An online outlier calculator helps you to detect an outlier that exists far beyond the data set at a specific range. Here, you can adopt various methods to figure out the outliers if they exist. But we have made it easy for you to perform the outlier check. For better understanding, just jump down! What Is An Outlier? In statistical analysis, “A specific entry or number that is totally different from all other entries in the data set is known as an outlier” Statistical Outlier Test: The outliers usually occur by chance and can cause serious problems in data sorting. You can use our online outlier calculator to determine an outlier absolutely for free. But, you must know the five number summary as well which is explained below: (1) Maximum: In a data set, the greatest value is always considered a maximum value. For example: Let us consider the following data set: 1, 5, 32, 854, 4 In this data set, the maximum is 854 because it is the greatest among all. (2) Minimum: The smallest value that exist in a data set is known as minimum. For example: Consider the same data set as mentioned above: 1, 5, 32, 854, 4 For this data set, the minimum is the 1 as it is the smallest value. (3) Median: The middle term in a data set is called median. Rules For Median: It must be kept in mind that you have two rules defined if you want to find median. Even Numbers: If the number of values in your data set are even, then the median is considered as the average of two middle terms. $$ median = \...

Some observations within a set of data may fall outside the general scope of the other observations. Such observations are called outliers. In We can use the IQR method of identifying outliers to set up a “fence” outside of Q1 and Q3. Any values that fall outside of this fence are considered outliers. To build this fence we take 1.5 times the IQR and then subtract this value from Q1 and add this value to Q3. This gives us the minimum and maximum fence posts that we compare each observation to. Any observations that are more than 1.5 IQR below Q1 or more than 1.5 IQR above Q3 are considered outliers. This is the method that Minitab uses to identify outliers by default. A teacher wants to examine students’ test scores. Their scores are: 74, 88, 78, 90, 94, 90, 84, 90, 98, and 80. Five number summary: 74, 80, 89, 90, 98. \(IQR = 90 - 80 = 10\) The interquartile range is 10. \(1.5 IQR = 1.5 (10) = 15\) 1.5 times the interquartile range is 15. Our fences will be 15 points below Q1 and 15 points above Q3. Lower fence: \(80 - 15 = 65\) Upper fence: \(90 + 15 = 105\) Any scores that are less than 65 or greater than 105 are outliers. In this case, there are no outliers. A survey was given to a random sample of 20 sophomore college students. They were asked, “how many textbooks do you own?” Their responses, were: 0, 0, 2, 5, 8, 8, 8, 9, 9, 10, 10, 10, 11, 12, 12, 12, 14, 15, 20, and 25. The observations are in order from smallest to largest, we can now compute the IQR by finding the...

• Home • Statistics Calculators • Mean, Median, and Mode Calculator • Range, Standard Deviation, and Variance Calculator • Z-Score Calculator • Raw Score Calculator • Chebyshev’s Theorem Calculator • Empirical Rule Calculator • Percentile Rank Calculator • Percentile Formula Calculator • 5 Number Summary Calculator / IQR Calculator • Binomial Probability Calculator • Binomial Distribution Calculator • Normal CDF Calculator • Inverse Normal Distribution Calculator • Inverse T Distribution Calculator • Poisson Probability Calculator • Poisson Distribution Calculator • Standard Deviation Calculator with Step by Step Solution • Outlier Calculator with Easy Step-by-Step Solution • Descriptive Statistics • What is a Z-Score? Why We Use Them and What They Mean • How to Find a Z-Score with the Z-Score Formula • What is the Empirical Rule? • Chebyshev’s Theorem Explained • How to Find the Mean Median and Mode • Probability • How To Use the Z-Table to Find Area and Z-Scores • Math T-Shirts and Gear Answer: Interquartile range: 86 Outlier(s): 66, 185 Potential outlier(s): 859 See the outliers and potential outliers highlighted in the sorted data set here: 66, 185, 559, 567, 571, 572, 572, 587, 593, 606, 625, 639, 645, 645, 657, 659, 670, 670, 859 Solution: The interquartile range, IQR, is the difference between Q3 and Q1. In this data set, Q3 is 657 and Q1 is 571. Subtract Q1, 571, from Q3, 657. $$ IQR = 657 - 571 = 86 $$ You can use the 5 number summary calculator to learn steps on ...