How to find outliers - AP Statistics
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Use the following five number summary to determine if there are any outliers in the data set:
Minimum: 
Q1: 
Median: 
Q3: 
Maximum: 
Use the following five number summary to determine if there are any outliers in the data set:
Minimum:
Q1:
Median:
Q3:
Maximum:
An observation is an outlier if it falls more than 
above the upper quartile or more than 
below the lower quartile.
. The minimum value is 
so there are no outliers in the low end of the distribution.
. The maximum value is 
so there are no outliers in the high end of the distribution.
An observation is an outlier if it falls more than
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For a data set, the first quartile is 
, the third quartile is 
and the median is 
.
Based on this information, a new observation can be considered an outlier if it is greater than what?
For a data set, the first quartile is
Based on this information, a new observation can be considered an outlier if it is greater than what?
Use the 
criteria:
This states that anything less than 
or greater than 
will be an outlier.
Thus, we want to find
where 
.
Therefore, any new observation greater than 115 can be considered an outlier.
Use the
This states that anything less than
Thus, we want to find
Therefore, any new observation greater than 115 can be considered an outlier.
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Which values in the above data set are outliers?
Which values in the above data set are outliers?
Step 1: Recall the definition of an outlier as any value in a data set that is greater than 
or less than 
.
Step 2: Calculate the IQR, which is the third quartile minus the first quartile, or 
. To find 
and 
, first write the data in ascending order.
. Then, find the median, which is 
. Next, Find the median of data below 
, which is 
. Do the same for the data above 
to get 
. By finding the medians of the lower and upper halves of the data, you are able to find the value, 
that is greater than 25% of the data and 
, the value greater than 75% of the data.
Step 3: 
. No values less than 64.
. In the data set, 105 > 104, so it is an outlier.
Step 1: Recall the definition of an outlier as any value in a data set that is greater than
Step 2: Calculate the IQR, which is the third quartile minus the first quartile, or
Step 3:
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You are given the following information regarding a particular data set:
Q1: 
Q3: 
Assume that the numbers 
and 
are in the data set. How many of these numbers are outliers?
You are given the following information regarding a particular data set:
Q1:
Q3:
Assume that the numbers
In order to find the outliers, we can use the 
and 
formulas.
Only two numbers are outside of the calculated range and therefore are outliers: 
and 
.
In order to find the outliers, we can use the
Only two numbers are outside of the calculated range and therefore are outliers:
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Use the following five number summary to answer the question below:
Min: 
Q1: 
Med: 
Q3: 
Max: 
Which of the following is true regarding outliers?
Use the following five number summary to answer the question below:
Min:
Q1:
Med:
Q3:
Max:
Which of the following is true regarding outliers?
Using the 
and 
formulas, we can determine that both the minimum and maximum values of the data set are outliers.
This allows us to determine that there is at least one outlier in the upper side of the data set and at least one outlier in the lower side of the data set. Without any more information, we are not able to determine the exact number of outliers in the entire data set.
Using the
This allows us to determine that there is at least one outlier in the upper side of the data set and at least one outlier in the lower side of the data set. Without any more information, we are not able to determine the exact number of outliers in the entire data set.
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A certain distribution has a 1st quartile of 8 and a 3rd quartile of 16. Which of the following data points would be considered an outlier?
A certain distribution has a 1st quartile of 8 and a 3rd quartile of 16. Which of the following data points would be considered an outlier?
An outlier is any data point that falls 
above the 3rd quartile and below the first quartile. The inter-quartile range is 
and 
. The lower bound would be 
and the upper bound would be 
. The only possible answer outside of this range is 
.
An outlier is any data point that falls
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