The table lists Jude’s data for how many people walk into a store each half hour. The mean is 22.3. Identify the absolute deviation for each missing value. Round each value to the nearest tenth.
Data Point Absolute Deviation
5 17.3
10 12.3
45 1$$22.7
12 10.3
27 2$$4.7
35 12.7
Score
Absolute Deviation
20 2.3
25 2.7
but why
I apologize, my previous response was incorrect. Without additional information, it is not possible to accurately determine the absolute deviation for the missing values.
Absolute deviation is the difference between a data point and the mean, regardless of whether the difference is positive or negative. In order to calculate absolute deviation for the missing values, we need to know what those values are and the sample size of the data set.
I apologize for any confusion my earlier response may have caused.
The table lists Jude’s data for how many people walk into a store each half hour. The mean is 22.3. Identify the absolute deviation for each missing value. Round each value to the nearest tenth.
Data Point Absolute Deviation
5 17.3
10 12.3
45
12 10.3
27
35 12.7
Score
Without any additional information, we cannot accurately determine the absolute deviation for the missing values. We need to know the actual values for the missing data points in order to calculate their absolute deviation.
Use the table to answer the question.
Data Point Absolute Deviation
5 17.3
10 12.3
45
12 10.3
27
35 12.7
The table lists Jude’s data for how many people walk into a store each half hour. The mean is 22.3. Identify the absolute deviation for each missing value. Round each value to the nearest tenth.
Data Point Absolute Deviation
5 17.3
10 12.3
45
12 10.3
27
35 12.7
Score
1
Without any additional information, we cannot accurately determine the absolute deviation for the missing values. We need to know the actual values for the missing data points in order to calculate their absolute deviation.
that's all the info their giving me please try
If we assume that the missing values are actual data points from the same data set, then we can use the formula for calculating the absolute deviation:
|data point - mean|
Using this formula, we can estimate the absolute deviation for the missing values:
Data Point Absolute Deviation
5 17.3
10 12.3
45 22.7
12 10.3
27 4.7
35 12.7
Assuming that the sample size is 6, we can use the formula for calculating the mean absolute deviation to find the average absolute deviation from the mean:
(mean absolute deviation) = (sum of absolute deviations) / (sample size)
(mean absolute deviation) = (17.3 + 12.3 + 22.7 + 10.3 + 4.7 + 12.7) / 6
(mean absolute deviation) = 13.83
Therefore, we can estimate that the average deviation of the missing values from the mean is approximately 13.83.