NEW FROM QUALITY PROGRESS! Back to Basics: Sizing Up Samples, dives into the essentials of determining the ideal sample size when examining a population. If the population is heterogeneous and its total size is large but unknown, Cochran’s formula is a reliable method for estimating the sample size. Using the right sample size calculation method ensures statistical validity, avoiding the pitfalls of insufficient or excessively large samples. Get back to basics and enhance your analysis with this crucial read at: https://lnkd.in/gfSJbhXT #QualityProgress #Statistics #QualityTools #Measurement
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We need to talk about misconceptions in #statistics, namely p-values ... again. Part 2 of 5: Wasserstein, Schirm, Lazar (2019) Moving to a World Beyond "p < 0.05": There’s not much we can say here about the perils of p-values and significance testing that hasn’t been said already for decades (Ziliak and McCloskey 2008; Hubbard 2016). If you’re just arriving to the debate, here’s another sampling of what not to do.
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What sample size do you need to collect to conduct a meaningful analysis? A simple answer might be "more," but collecting data costs both money and time. In this blog post, I describe how to calculate the necessary sample size to achieve statistical significance using the Chernoff Bound.
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We need to talk about misconceptions in #statistics, namely p-values ... again. Part 3 of 5: Wasserstein, Schirm, Lazar (2019) Moving to a World Beyond "p < 0.05": There’s not much we can say here about the perils of p-values and significance testing that hasn’t been said already for decades (Ziliak and McCloskey 2008; Hubbard 2016). If you’re just arriving to the debate, here’s another sampling of what not to do.
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We need to talk about misconceptions in #statistics, namely p-values ... again. Part 5 of 5: Wasserstein, Schirm, Lazar (2019) Moving to a World Beyond "p < 0.05": There’s not much we can say here about the perils of p-values and significance testing that hasn’t been said already for decades (Ziliak and McCloskey 2008; Hubbard 2016). If you’re just arriving to the debate, here’s another sampling of what not to do.
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We need to talk about misconceptions in #statistics, namely p-values ... again. Part 1 of 5: Wasserstein, Schirm, Lazar (2019) Moving to a World Beyond "p < 0.05": There’s not much we can say here about the perils of p-values and significance testing that hasn’t been said already for decades (Ziliak and McCloskey 2008; Hubbard 2016). If you’re just arriving to the debate, here’s a sampling of what not to do:
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We need to talk about misconceptions in #statistics, namely p-values ... again. Part 4 of 5: Wasserstein, Schirm, Lazar (2019) Moving to a World Beyond "p < 0.05": There’s not much we can say here about the perils of p-values and significance testing that hasn’t been said already for decades (Ziliak and McCloskey 2008; Hubbard 2016). If you’re just arriving to the debate, here’s another sampling of what not to do.
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Systematic Literature Reviews and Meta-Analyses To learn how to implement #economic_evaluation_techniques (#CEA and #CUA) using decision analytic models, including #decision_trees and #Markov_models in a one-to-one setting: https://lnkd.in/dUcpjq6p.
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#OUTCOME MEASUREMENT IN #ECONOMIC_EVALUATION To learn how to implement #economic_evaluation_techniques (#CEA and #CUA) using decision analytic models, including #decision_trees and #Markov_models in a one-to-one setting: https://lnkd.in/dqTpcvTM.
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Randomized Controlled Trials #admin To learn how to implement #economic_evaluation_techniques (#CEA and #CUA) using decision analytic models, including #decision_trees and #Markov_models in a one-to-one setting: https://lnkd.in/dUcpjq6p.
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Requirements and Assessment of Laboratory Tests To learn how to implement #economic_evaluation_techniques (#CEA and #CUA) using decision analytic models, including #decision_trees and #Markov_models in a one-to-one setting: https://lnkd.in/dUcpjq6p.
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Very informative! Thank for the updates!