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Fig. 2 Gesture used in the variability condition.
Parameters for the no criterial variability condition were: a = .35, SSF = SSP = .5, csim = csu = .07.07
Parameter for the criterial variability condition were the same except that csim = csu ~ N(μ = .07, =.75 * μ).
This difference between the Centrality and Variability condition was statistically significant (Χ 2 (1, N = 100) = 4.59, p = 0.032).
The survey software (Qualtrics, 2017) randomly assigned students to one of two gesture conditions: the Centrality condition (n = 47) or the Variability condition (n = 53).
In the Variability condition we saw a different pattern, with twice as many students saying they would need more information as saying they were fairly certain of an effect.
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Continued high browsing pressure is one of many factors contributing to the restructuring of northern Great Lakes forests away from historical variability conditions towards a novel and more homogeneous forested landscape.
These models can describe uncertainty arising from stochastic disturbances, variability conditions and risk consideration.
The distribution of responses in the Centrality and Variability conditions were not significantly different from Study 1 (Χ 2 (1, N = 162) = 5.45, p = 0.07).
Our goal was then to ensure that our RTT estimator is able to adjust to high variability conditions and yield accurate RTT estimates.
When asked in question 2 which additional pieces of information would be helpful in determining if there was an effect, students in the Centrality and Variability conditions showed a similar pattern of responses.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com