Ensuring statistics have power: sample sizes, effect sizes and confidence intervals (and how to use them)
Ensuring statistics have power: sample sizes, effect sizes and confidence intervals (and how to use them)
There is ongoing confusion in empirical energy efficiency and energy demand evaluation studies over the meaning, value and use of statistical significance and statistical power. This is compounded by confusion over how these concepts should be used both in designing studies and in deciding what can be inferred from them. As a consequence, sample sizes in most energy efficiency studies may be too low to provide adequate statistical power and so statistically robust conclusions cannot be drawn at conventional thresholds . In this paper we explore this problem via the design of a study focused on winter evening heat pump demand to demonstrate how sample sizes, effect sizes and confidence intervals matter.
Anderson, Ben
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Rushby, Tom
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Bahaj, Abubakr
a64074cc-2b6e-43df-adac-a8437e7f1b37
James, Patrick
da0be14a-aa63-46a7-8646-a37f9a02a71b
16 March 2021
Anderson, Ben
01e98bbd-b402-48b0-b83e-142341a39b2d
Rushby, Tom
bdb7715f-0331-491c-a9dd-5835f30b0bf8
Bahaj, Abubakr
a64074cc-2b6e-43df-adac-a8437e7f1b37
James, Patrick
da0be14a-aa63-46a7-8646-a37f9a02a71b
Anderson, Ben, Rushby, Tom, Bahaj, Abubakr and James, Patrick
(2021)
Ensuring statistics have power: sample sizes, effect sizes and confidence intervals (and how to use them).
Energy Evaluation Europe: 2021 Europe Conference: Accelerating the energy transition for all: Evaluation's role in effective policy making, Online.
10 - 16 Mar 2021.
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Conference or Workshop Item
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Abstract
There is ongoing confusion in empirical energy efficiency and energy demand evaluation studies over the meaning, value and use of statistical significance and statistical power. This is compounded by confusion over how these concepts should be used both in designing studies and in deciding what can be inferred from them. As a consequence, sample sizes in most energy efficiency studies may be too low to provide adequate statistical power and so statistically robust conclusions cannot be drawn at conventional thresholds . In this paper we explore this problem via the design of a study focused on winter evening heat pump demand to demonstrate how sample sizes, effect sizes and confidence intervals matter.
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Published date: 16 March 2021
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Energy Evaluation Europe: 2021 Europe Conference: Accelerating the energy transition for all: Evaluation's role in effective policy making, Online, 2021-03-10 - 2021-03-16
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Local EPrints ID: 447573
URI: http://eprints.soton.ac.uk/id/eprint/447573
PURE UUID: e4a5507d-d51a-433d-9d4c-9a6198077b71
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Date deposited: 16 Mar 2021 17:34
Last modified: 17 Mar 2024 02:39
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Author:
Tom Rushby
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