they are related, but one might not be causing the other
(10,10,30,30,30,50,50) (20,20,30,30,30,40,40) These two sets have the same mean, median and mode.
Correlation.
Correlation between two variables implies a linear relationship between them. The existence of correlation implies no causal relationship: the two could be causally related to a third variable. For example, my age is correlated with the number of TV sets in the UK but obviously there is no causal link between them - they are both linked to time.
If both sets are in agreement, it is a good indication each is accurate. If, on the other hand, there is great disparity between the two sets, we may conclude there is some significant error in our data gathering or sampling technique. The NASA GISS data (see link) include both a land/sea temperature index and temperature measurements from meteorological stations.
There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.
they are related, but one might not be causing the other.
They are related but one might not be causing the other
(10,10,30,30,30,50,50) (20,20,30,30,30,40,40) These two sets have the same mean, median and mode.
Comparing the relationship of two data sets is needed to see which of the two sets have more life distribution. Two data sets involve the use of simple plotting and contour plots.
The preposition "with" should follow the word "correlated." For example: "The data suggests that these two variables are strongly correlated with each other."
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.
If the skewness is different, then the data sets are different.Incidentally, there is one [largely obsolete] definition of skewness which is in terms of the mean and median. Under that definition, it would be impossible for two data sets to have equal means and equal medians but opposite skewness.
When comparing large data sets.
The line and the bar graph is used to describe a graph that compares two sets of data.
You can see where the data is clustered
To integrate has two separate meanings. It might mean simply that different sets of data are put together. It can also refer to a mathematical process which is part of the calculus.
mining two different data sets