What is the outlier in the data set 42.7, 42.8, 43.1, 43.3, 43.5, 43.8?
The outlier in the data set is 42.7.
The following bivariate data set contains an outlier.
x y
43.3 -159.6
60.8 1530.9
15.6 1070.3
24.5 466.6
51.4 1104.5
26.6 -540.7
31.1 -175.9
23.9 695.6
44 195.4
25.4 -501.1
50.7 -621.7
25.9 -403.3
326 7988.7
38.8 74.7
93.2 -212.5
This data can be downloaded as a *.csv file with this link: Download CSV
¿What is the correlation coefficient with the outlier?
rw =
¿What is the correlation coefficient without the outlier?
rwo =
Outlier values may or may not be valid, but either way it does affect the calculations. You will need to calculate the correlation coefficient TWO times: once with all of the data (including the outlier) and again with the outlier excluded. Note that excluding the outlier reduces the sample size by 1.
The following bivariate data set contains an outlier.
x y
67.8 -1624
65.9 4363.9
83.4 -735.3
53.4 3586.8
73.3 3004
247 -33436.9
101.8 -1663.1
62.5 -5086.3
86.3 622.3
86.1 -1404.6
86.4 1197.7
70.1 815.7
89.5 1433.6
89 1678
78.7 1773.1
This data can be downloaded as a *.csv file with this link: Download CSV
¿What is the correlation coefficient with the outlier?
rw =
¿What is the correlation coefficient without the outlier?
rwo =
To determine the outlier in a data set, you need to calculate the interquartile range (IQR) and identify any data points that fall outside a certain range. The IQR is the range between the first quartile (Q1) and the third quartile (Q3).
To find the outlier in the given data set [42.7, 42.8, 43.1, 43.3, 43.5, 43.8], you can follow these steps:
1. Sort the data set in ascending order: [42.7, 42.8, 43.1, 43.3, 43.5, 43.8]
2. Calculate Q1, which is the median of the lower half of the data set. In this case, Q1 = (42.8 + 43.1) / 2 = 43.0.
3. Calculate Q3, which is the median of the upper half of the data set. In this case, Q3 = (43.3 + 43.5) / 2 = 43.4.
4. Calculate the IQR, which is the difference between Q3 and Q1. In this case, IQR = 43.4 - 43.0 = 0.4.
5. Determine the lower bound by subtracting 1.5 times the IQR from Q1. Lower bound = Q1 - (1.5 * IQR) = 43.0 - (1.5 * 0.4) = 42.4.
6. Determine the upper bound by adding 1.5 times the IQR to Q3. Upper bound = Q3 + (1.5 * IQR) = 43.4 + (1.5 * 0.4) = 43.9.
7. Any data point below the lower bound or above the upper bound is considered an outlier.
In the given data set, none of the values fall outside the range from 42.4 to 43.9. So, there is no outlier.