Mrs. Keegan wrote down her student's quiz grades from Unit 2. Their results included: 58, 72, 88, 100, 65, 93, 81. Which number, if added to the dataset, would represent an outlier in the data? options 53 99 35 69

Question

Mrs. Keegan wrote down her student's quiz grades from Unit 2. Their results included: 58, 72, 88, 100, 65, 93, 81. Which number, if added to the dataset, would represent an outlier in the data? options 53 99 35 69

Answer 1

To determine if a number is an outlier in the data set, we can use the criteria of being more than 1.5 times the interquartile range (IQR) away from the first quartile (Q1) or third quartile (Q3).

First, we need to find the IQR:
1. Arrange the numbers in ascending order: 58, 65, 72, 81, 88, 93, 100.
2. Find Q1: This is the median of the lower half of the dataset. In this case, it is the median of 58, 65, and 72, which is 65.
3. Find Q3: This is the median of the upper half of the dataset. In this case, it is the median of 81, 88, and 93, which is 88.
4. Calculate the IQR: Q3 - Q1 = 88 - 65 = 23.

Now we can check each option:
1. 53: This number is less than Q1, so it is not a potential outlier.
2. 99: This number is greater than Q3 but not by more than 1.5 times the IQR, so it is not a potential outlier.
3. 35: This number is less than Q1, so it is not a potential outlier.
4. 69: This number is between Q1 and Q3, so it is not a potential outlier.

None of the given options would represent an outlier in the data set.

Answer 2

are you sure

Answer 3

I apologize for the incorrect information in my previous response. Let's go through the steps to find the potential outlier again.

1. Arrange the numbers in ascending order: 58, 65, 72, 81, 88, 93, 100.
2. Find Q1: This is the median of the lower half of the dataset. In this case, it is the median of 58, 65, and 72, which is 65.
3. Find Q3: This is the median of the upper half of the dataset. In this case, it is the median of 81, 88, and 93, which is 88.
4. Calculate the IQR: Q3 - Q1 = 88 - 65 = 23.

Now, let's check each option again:
1. 53: This number is less than Q1, so it is not a potential outlier.
2. 99: This number is greater than Q3 but not by more than 1.5 times the IQR (23 * 1.5 = 34.5), so it is not a potential outlier.
3. 35: This number is less than Q1, so it is not a potential outlier.
4. 69: This number is between Q1 and Q3, so it is not a potential outlier.

After reassessment, it appears that none of the given options would represent an outlier in the data set.

Answer 4

choose 1 guggy

Answer 5

I apologize for the confusion. If I have to choose one option from the given options, I would choose 99 as the potential outlier. While it does not meet the criteria to be considered an outlier based on the 1.5 times IQR rule, it is the highest value in the dataset and is relatively farther away from the other values. Again, it is important to note that without further information or a clear definition of what constitutes an outlier in this context, it might not be appropriate to identify any value in the dataset as an outlier.