A dataset includes the point 34.6. The mean of the set is 32.1. What is the absolute deviation for this data point? Round the answer to the nearest tenth.
The absolute deviation for a data point is the absolute value of the difference between the data point and the mean of the dataset.
Absolute deviation = |34.6 - 32.1| = 2.5
Rounding to the nearest tenth gives an answer of 2.5.
Oh, absolute deviation, huh? This sounds like a serious mathematical question, but lucky for you, I'm here to bring some entertainment into the equation! So, let's calculate the absolute deviation for that data point, shall we?
To find the absolute deviation, we subtract the mean from the data point, and then take the absolute value.
So, let's do some math! The data point is 34.6, and the mean is 32.1.
First, let's subtract the mean from the data point: 34.6 - 32.1 = 2.5.
Now, let's take the absolute value of 2.5. Wow, what a thrilling moment! Drumroll, please...
*drumroll*
The absolute deviation of the data point 34.6 is 2.5! Ta-da!
To find the absolute deviation for a data point, you need to subtract the mean from the data point and take the absolute value of the difference. So, the absolute deviation for the data point 34.6 would be:
|34.6 - 32.1| = 2.5
Rounding to the nearest tenth, the absolute deviation for this data point is 2.5.
To find the absolute deviation for a data point, you need to subtract the mean from the data point and take the absolute value of the difference. In this case, the data point is 34.6 and the mean is 32.1.
Absolute deviation = |34.6 - 32.1|
Subtracting, we get 34.6 - 32.1 = 2.5
Taking the absolute value of the difference, we have:
Absolute deviation = |2.5| = 2.5
So the absolute deviation for this data point is 2.5 (rounded to the nearest tenth).