To find outliers in data, we can use some helpful measures. These include range, interquartile range (IQR), and standard deviation. Let’s break them down:
Range: This shows the difference between the highest and lowest numbers. If the range is really big, there might be outliers!
Interquartile Range (IQR): This is the range of the middle 50% of the data.
To find it, subtract the first quartile (Q1) from the third quartile (Q3):
IQR = Q3 - Q1.
If a data point is below Q1 - 1.5 × IQR or above Q3 + 1.5 × IQR, it might be an outlier.
Standard Deviation: This shows how spread out the numbers are. If a number is more than 2 standard deviations away from the average (mean), it could be an outlier.
Using these tools can help us better understand our data!
To find outliers in data, we can use some helpful measures. These include range, interquartile range (IQR), and standard deviation. Let’s break them down:
Range: This shows the difference between the highest and lowest numbers. If the range is really big, there might be outliers!
Interquartile Range (IQR): This is the range of the middle 50% of the data.
To find it, subtract the first quartile (Q1) from the third quartile (Q3):
IQR = Q3 - Q1.
If a data point is below Q1 - 1.5 × IQR or above Q3 + 1.5 × IQR, it might be an outlier.
Standard Deviation: This shows how spread out the numbers are. If a number is more than 2 standard deviations away from the average (mean), it could be an outlier.
Using these tools can help us better understand our data!