Articles | Volume 19, issue 19
Atmos. Chem. Phys., 19, 12531–12543, 2019
https://doi.org/10.5194/acp-19-12531-2019
Atmos. Chem. Phys., 19, 12531–12543, 2019
https://doi.org/10.5194/acp-19-12531-2019

Technical note 09 Oct 2019

Technical note | 09 Oct 2019

Technical note: Effects of uncertainties and number of data points on line fitting – a case study on new particle formation

Santtu Mikkonen et al.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Wenzel on behalf of the Authors (25 Mar 2019)  Author's response
ED: Referee Nomination & Report Request started (26 Mar 2019) by Fangqun Yu
RR by Anonymous Referee #1 (23 Apr 2019)
ED: Reconsider after major revisions (24 Apr 2019) by Fangqun Yu
AR by Anna Wenzel on behalf of the Authors (06 Jun 2019)  Author's response
ED: Referee Nomination & Report Request started (10 Jun 2019) by Fangqun Yu
RR by Anonymous Referee #3 (17 Jul 2019)
ED: Reconsider after major revisions (17 Jul 2019) by Fangqun Yu
AR by Svenja Lange on behalf of the Authors (20 Aug 2019)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by editor) (02 Sep 2019) by Fangqun Yu
AR by Santtu Mikkonen on behalf of the Authors (05 Sep 2019)  Author's response    Manuscript
ED: Publish subject to technical corrections (09 Sep 2019) by Fangqun Yu
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Short summary
Atmospheric measurement data never come without measurement error. Too often, these errors are neglected when researchers make inferences from their data. We applied multiple line-fitting methods to simulated data mimicking two central variables in aerosol research. Our results show that an ordinary least squares fit, typically used to describe relationships, underestimates the slope of the fit and that methods taking the measurement uncertainty into account performed significantly better.
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