Hi Hemant,
data_help <- data_help %>%
# Add a dummy index for each purchase to keep a memory of the purchase
since it will dissappear later on. You could also use row number
mutate(Purchase_ID = 1:n()) %>%
# For each purchase id
group_by(Purchase_ID) %>%
# Call the split_items function, which retu
Mathias,
If it's any comfort, I appreciated the example; 'expected' behaviour maybe, but
a very nice example for staff/student training!
S Ellison
> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Matthias
> Gondan
> Sent: 02 September 2017 18:22
> T
Sounds like a homework problem. This list has a no homework policy if it is.
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Sep 4, 2017 at 10:31
Dear S Ellison,
Thanks for the flowers! Indeed, I was actually considering to use it in my own
teaching material, as well. With rounded numbers, of course.
Though I am still slightly disturbed about this feature. I thought, now it is
the time to switch to Python, but that’s even worse, see here
>In the future, I’ll avoid dependencies between parameters.
You don't need to cut off your nose to spite your face... you are the one
writing the code that breaks the dependency, so you have the option to not
write your code that way (e.g. by using force() as Rui suggests).
--
Sent from my phon
I've recently come across the following results reported from the lm() function
when applied to a particular type of admittedly difficult data. When working
with
small data sets (for instance 3 points) with the same response for different
predicting variable, the resulting slope estimate is a r
> Do not the same considerations essentially apply to the well established
> /* */ convention used in C? Well maybe you simply *can't* get the "*/"
> string within a block of C code, but still
Yes, the same problem arises in C. And you _can_ get */ in valid code - as the
closing part of
Why does an unreliable fit have to provide "reasonable" results?
More specifically, p-values arise from observed distributions... if your slopes
are "in the noise" then the slope estimate's location within that distribution
could be anywhere relative to the center and spread of that very narrow
> On Sep 5, 2017, at 6:24 AM, Glover, Tim wrote:
>
> I've recently come across the following results reported from the lm()
> function when applied to a particular type of admittedly difficult data.
> When working with
> small data sets (for instance 3 points) with the same response for diffe
Tim,
I think what you're seeing is
https://en.wikipedia.org/wiki/Loss_of_significance.
Cheers,
Mark
From: "Glover, Tim"
To: "r-help@r-project.org"
Date: 09/05/2017 11:37 AM
Subject:[R] Interesting behavior of lm() with small, problematic
data sets
Sent by:"R-help"
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