To identify outliers in a data set, we typically use the Interquartile Range (IQR) method. Here are the steps:

1. First, we need to sort the data in ascending order: 495, 497, 500, 501, 502, 503, 504, 506, 506, 509, 510

2. Then, we find the median (Q2), which is the middle value. Since we have 11 data points, the median is the 6th value: 503

3. Next, we find the lower quartile (Q1), which is the median of the lower half of the data (not including Q2). In this case, it's the median of 495, 497, 500, 501, 502, which is 500.

4. We also find the upper quartile (Q3), which is the median of the upper half of the data (not including Q2). In this case, it's the median of 504, 506, 506, 509, 510, which is 506.

5. Now, we calculate the interquartile range (IQR), which is Q3 - Q1 = 506 - 500 = 6.

6. We then calculate the lower bound for outliers, which is Q1 - 1.5*IQR = 500 - 1.5*6 = 491.

7. We also calculate the upper bound for outliers, which is Q3 + 1.5*IQR = 506 + 1.5*6 = 515.

8. Finally, we identify any data points that are below the lower bound or above the upper bound. In this case, there are no data points below 491 or above 515.

So, there are no outliers in this data set.

Question

To identify outliers in a data set, we typically use the Interquartile Range (IQR) method. Here are the steps:

1. First, we need to sort the data in ascending order: 495, 497, 500, 501, 502, 503, 504, 506, 506, 509, 510

2. Then, we find the median (Q2), which is the middle value. Since we have 11 data points, the median is the 6th value: 503

3. Next, we find the lower quartile (Q1), which is the median of the lower half of the data (not including Q2). In this case, it's the median of 495, 497, 500, 501, 502, which is 500.

4. We also find the upper quartile (Q3), which is the median of the upper half of the data (not including Q2). In this case, it's the median of 504, 506, 506, 509, 510, which is 506.

5. Now, we calculate the interquartile range (IQR), which is Q3 - Q1 = 506 - 500 = 6.

6. We then calculate the lower bound for outliers, which is Q1 - 1.5*IQR = 500 - 1.5*6 = 491.

7. We also calculate the upper bound for outliers, which is Q3 + 1.5*IQR = 506 + 1.5*6 = 515.

8. Finally, we identify any data points that are below the lower bound or above the upper bound. In this case, there are no data points below 491 or above 515.

So, there are no outliers in this data set.

Knowee AI · Accepted Answer