Construct a data set of 8 items that has a mean absolute deviation of 0.5 and for which average 8
well, the set 7.5, 7.5, 8.5, 8.5 fits the bill for 4 numbers. See whether you can expand that to 8 values.
Idek
To construct a data set of 8 items with a mean absolute deviation of 0.5 and an average of 8, we can follow these steps:
Step 1: Start with the assumption that the data set is sorted in ascending order.
Step 2: Since the mean absolute deviation (MAD) is the average distance between each data point and the mean, we can calculate the sum of the absolute differences between each data point and the mean. In this case, we want the MAD to be 0.5, so the sum of the absolute differences will be 0.5 * 8 = 4.
Step 3: Divide the sum of the absolute differences (4) by the number of data points (8) to find the mean difference, which is 4 / 8 = 0.5.
Step 4: Begin by filling in the data set with the average value (8) for all 8 items.
Step 5: Distribute the remaining difference of 4 across the data set, ensuring that the given MAD of 0.5 is maintained. To do this, place the differences symmetrically around the mean.
To illustrate this step-by-step, let's assume the average is 8 and the ordered data set is as follows:
8, 8, 8, 8, 8, 8, 8, 8
Step 6: Calculate the differences between each data point and the mean, and sum their absolute values. In this case, the sum of the differences is 0.
Absolute Differences: 0, 0, 0, 0, 0, 0, 0, 0
Sum of Absolute Differences: 0
Step 7: Adjust the data set by adding/subtracting differences symmetrically around the mean until the sum of the absolute differences equals 4.
One approach to distribute the differences symmetrically is by adding 0.5 to one item and subtracting 0.5 from another. We adjust the first and last items in the sorted data set.
Adjusted Data Set (final result):
7.5, 8, 8, 8, 8, 8, 8, 8.5
Step 8: Calculate the mean of the adjusted data set. The sum of the data points is 63 and there are 8 items, so the mean is calculated as 63 / 8 = 7.875.
The adjusted data set has an average of approximately 7.875 and a mean absolute deviation of 0.5.
To construct a data set with a mean absolute deviation of 0.5 and an average of 8, we can use the following steps:
Step 1: Start with a set of 8 numbers with a mean of 8. We can choose any numbers as long as their sum is 8 multiplied by 8, which is 64. For simplicity, we can start with all 8 numbers as 8.
[8, 8, 8, 8, 8, 8, 8, 8]
Step 2: Calculate the mean of this initial set of numbers.
Mean = (8 + 8 + 8 + 8 + 8 + 8 + 8 + 8) / 8 = 8
The current mean is already 8, as desired.
Step 3: Adjust the numbers to achieve the desired mean absolute deviation (MAD) of 0.5. To do this, we need to slightly increase or decrease the values of some numbers while keeping the sum unchanged.
In this case, to increase or decrease the numbers in a controlled manner, we will add or subtract a fixed number to each number. The fixed number we will use is half of the mean absolute deviation (0.5/2 = 0.25).
Updated set: [8 + 0.25, 8 - 0.25, 8 + 0.25, 8 - 0.25, 8 + 0.25, 8 - 0.25, 8 + 0.25, 8 - 0.25]
Simplified set: [8.25, 7.75, 8.25, 7.75, 8.25, 7.75, 8.25, 7.75]
Step 4: Calculate the mean of the updated set.
Mean = (8.25 + 7.75 + 8.25 + 7.75 + 8.25 + 7.75 + 8.25 + 7.75) / 8 = 8
The mean is still 8, and we have achieved the desired mean.
Step 5: Calculate the mean absolute deviation (MAD) of the updated set to confirm it is 0.5.
MAD = (|8.25-8| + |7.75-8| + |8.25-8| + |7.75-8| + |8.25-8| + |7.75-8| + |8.25-8| + |7.75-8|) / 8
MAD = (0.25 + 0.25 + 0.25 + 0.25 + 0.25 + 0.25 + 0.25 + 0.25) / 8
MAD = 2 / 8 = 0.25
The calculated mean absolute deviation is 0.25, which does not match the desired MAD of 0.5 in our data set.
To rectify this, we can adjust the fixed number used in Step 3 from 0.25 to 0.5. Repeat steps 3 to 5 using the adjusted fixed number until the MAD is 0.5.
By following these steps, you can create a data set of 8 items with a mean absolute deviation of 0.5 and an average of 8.