The variance is 13.5833
The variance is: 3.8
The variance is: 500.0
The variance is 10.
There are infinitely many sets. One possible set is {10,10,12,13,15}
In order to find the weighted mean of this set of the data, we need to know the weight for each data in the set, and this information is not given in your question.Definition: When each number ai is to have weight wi, the weighted mean is equal to(w1a1+w2a2 + ... + wnan)/(w1 + w2 + ... + wn).
The variance is: 3.8
- 4
For 12 10 9 7 7: var=4.5
The variance is: 500.0
The mean increases by 10.
mean = 5, variance = 5
To answer this question I will use an example. Data set: 10, 20, 30, 40, 50. First find the sum of all the numbers...so 10+20+30+40+50= 150. Then you take the sum (150) and divide it by the number of numbers in the data set. So 150 divided by 5 (the number of numbers in this data set) = 30. 30= the mean of the above data set. Finding the mean is pretty simple. :)
In any given set, the mean is the average, which is the total of the numbers divided by how many numbers there are. Ex. (10, 17, 20, 45, 68) 68 + 45 + 20 + 17 + 10 = 160 There are 5 numbers in this set. 160/5 = 32 The mean is 32.
The variance is 10.
No.The empirical rule is a good estimate of the spread of the data given the mean and standard deviation of a data set that follows the normal distribution.If you you have a data set with 10 values, perhaps all 10 the same, you clearly cannot use the empirical rule.
There are infinitely many sets. One possible set is {10,10,12,13,15}
In order to find the weighted mean of this set of the data, we need to know the weight for each data in the set, and this information is not given in your question.Definition: When each number ai is to have weight wi, the weighted mean is equal to(w1a1+w2a2 + ... + wnan)/(w1 + w2 + ... + wn).