 Transcribed

## Most Prominent Methods of How to Find Outliers in Statistics

MOST PROMINENT METHODS OF How to Find Outliers in Statistics What are outliers in statistics? A definition of outliers in statistics can be considered as a section of data, which is used to represent an extraordinary range from a piot to another point. Or we can say that it is the data that remains outside of the other given values with a set of data. Examples of outliers in statistics 5, 94, 95, 96, 99, 104, 105, 199 "5" is studied as an extremely low value whereas “199" is recognized as an extremely high value. \$220, \$245, \$20, \$230. Your average paycheck is considered as \$130. But the smaller paycheck (\$20) can be because that person went on holiday. 60, 9, 31, 18, 21, 28, 35, 13, 48, 2. One might guess that 2 is an outlier and possibly 60. But one predicts it as 60 is the outlier in the set of data. T 20 30 40 50 60 70 80 90 100 20 30 40 50 60 70 80 90 100 How to find outliers in statistics using the Interquartile Range (IQR)? An outlier is described as a data point that ranges above 1.5 IQRS, which is under the first quartile (Q1) or over the third quartile (Q3) within a set of data. Low = (Q1) – 1.5 IQR High = (Q3) + 1.5 IQR %3D Sample Problem: Find all of the outliers in statistics of the given data set: 10, 20, 30, 40, 50, 60, 70, 80, 90, 100. Step 1: Get the Interquartile Range, Q1(25th percentile) and Q3(75th percentile). IQR = 50 Q1 (25th percentile) = 30 Q2 (50th percentile) = 55 Q3 (75th percentile)= 80 Step 2: Multiply the calculated IQR with 1.5 that has been obtained in Step 1: IQR * 1.5 = 50* 1.5 = 75. Step 3: Add the number of Step 2 to Q3 [calculated in Step 1]: 75+ 80= 155. Step 4: Subtract the number which one has found in Step 2 from Q1 from Step 1: 30 – 50= -20. Step 5: Keep the values from the data set in order: 10, 20, 30, 40, 50, 60, 70, 80, 90, 100. Step 6: Include these low and high values to the given data set in order: -20, 10, 20, 30, 40, 50, 60, 7о, 80, 90, 100, 155. Step 7: Highlight a value above or below the values that one has put in Step 6: -20, 10, 20, 30, 40, 50, 60, 7о, 80, 90, 100, 155. How to find the outliers in statistics using the Tukey method? The Tukey method to discover the outliers in statistics applies the Interquartile Range to separate very small or very large numbers. The specifications are High outliers = Q3 + 1.5(Q3 – Q1) = Q3 + 1.5(IQR) Low outliers = Q1 – 1.5(Q3 – Q1) = Q1 – 1.5(IQR) Where: Q1 = first quartile Q2 = middle quartile Q3 = third quartile IQR = Interquartile range Sample Problem: Use Tukey's method to get the value of outliers of the fol- lowing data: 3,4,6,8,9,11,14,17,20,21,42. Step 1: Calculate the Interquartile range Q1 = 6 Q3 = 20 IQR = 14 Step 2: Measure the value of 1.5 * IQR: 1.5 * IQR = 1.5 * 14= 21 Step 3: Subtract the value of Q1 to obtain the lower fence: 6 - 21 = -15 Step 4: Sum the value to Q3 to obtain the upper fence: 20+ 21 = 41. Step 5: Add these fences to the given data to get the value of outliers: -15, 3, 4, 6, 8, 9, 11, 14, 17, 20, 21, 41, 42. www.statanalytica.com

# Most Prominent Methods of How to Find Outliers in Statistics

shared by statanalytica on Jun 26
0 views
0 shares
The efficient way to get all outliers is by utilizing the interquartile range (IQR). It includes the average bulk of the data, so outliers in statistics.

Category

Education
Did you work on this visual? Claim credit!

Get a Quote

### Embed Code

For hosted site:

Click the code to copy

For wordpress.com:

Click the code to copy
Customize size