elements
Yes
Yes it is. If all the observations have the same non-zero value then the coefficient of variation will be zero.
It is possible for two sets of data - not ALL of which are the same - to have the same measures of central tendency. However, if the two sets do have a mode, then that number must appear in both sets ... several times.
In database there are number of issues to be handled ,like redundant data, inconsistent data, unorganized data etc. Redundancy of data is the repetitive data that is taking the storage unnecessarily . So the redundant data must be removed or at least reduced.
The general shape of the line indicates whether the relationship is linear, quadratic, polynomial, power, inverse etc. It will also help determine whether the relationship remains the same over the whole domain or changes. The scatter of the observations about a line gives a measure of the variation in the observations about the values that might be expected from the line graph.
It can't * * * * * Yes it can. When there are an even number of observations and the middle two numbers are not the same.
Yes
Yes
Quartiles are values that divide a sample of data into four groups containing the same number of observations. You will find details in the related link.
No, it is not true.
You don't GET class intervals. The person analysing the data chooses what class interval gives the best summary of the data. Ideally you are looking for class intervals that havea reasonable number of observations in each class (5 or more),a reasonable number of classes,(sometimes) observations within the same class are as similar to one another as possible while observations between classes are as different as possible (maximum discrimination),a nice round numbers as their midpoints.The first three are important for some kinds of statistical analyses. The last is to make calculations simpler and interpretation of the results easier.
-- Multiply the first averages by the number of observation for each set of these. -- Add up the sets of averages. -- Divide the sum by the total number of observations (Add cardinaility of each set). -- The result is the average of the averages. If you say have 4 "average" value and just add these, and divide by 4, the result is "unfair" because average may be of 3 observations, while another of 1000. So, to "compensate" and make every observation just as valuable, you re-generate the "sum of sums" and then divide by the total number of observations. If all sets are the same you can divide by number of observations.
First, we compute the variance by taking the sum of squares and divide that by N which is the number of data points in the same. It is average squared deviation of each number from its mean. The point is a squared number is always positive and N is always positive so the variance must always be non-negative. ( It can be 0). The variance is a measure of the dispersion of a set of data points around their mean value. It would not make sense for it to be negative.
Yes.But only if the mode exists.If all the values in the dataset appear the same number of times there is no mode.
Yes it is. If all the observations have the same non-zero value then the coefficient of variation will be zero.
Yes, unless all the data are the same number.
Elements within a group always have the same number of valence electrons.