Hi Regina,
Hello,
because there is no obvious solution, I'll bring this to discussion here:
Example table
x y
-2 -4,84
-1 -1,74
0 0
1 2,38
2 3,82
3 7,17
4 9,28
gives for a linear regression the equitation (as shown in status bar)
y= 2.286 ∙ x − 6.847 for a line-diagram
y= 2.286 ∙ x + 0.01 for an XY-diagram
The wrong equitation in the line-diagram is due to the fact, that for
line diagrams not the real x-values but the values 1, 2, … are used.
The question is now, whether the regression curve should do so and it
is enough, if we tell it to the user. Or should the calculation use
the x-values of the data series, if they provide a datatyp to
calculate with?
The problem here is that there is this fundamental difference in line
charts and scatter charts. A line chart uses categories (which are
strings) and has equidistant data points. The "x-values" in this example
are names for categories for all data series of a line chart. If you
want them to be x-values, you have to chose scatter as chart-type.
The data series does not know any x-values in a line chart, so neither
does the regression curve. In addition your example works only because
the x-values are by chance equidistant. If they weren't, a line chart
would show the data points still equidistant. A regression curve using
the non-equidistant x-values would simply be wrong (the graphs would not
fit).
The only chance I see for this dilemma is to guide the user somehow that
he should use a scatter chart when the "categories" are numbers. In
Excel there is an automatism that uses scatter charts even if you select
a line chart type, when the categories are all numbers. However, I would
prefer to make this clear to the user.
Regards,
Bjoern
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