Suggestions(1)
Exact(18)
Data from each question were organized in 3 × 5 contingency tables, for example, Gen Fac, Edu, Stu × a e (Chi-square tests, null hypotheses rejected at P ≤ 0.05).
This finding reflects the main strength of BWS, which is the information gain achieved by collecting additional information from each question.
Data from each question were organized in 2 × 5 contingency tables, for example, RWU biology majors, PC biology majors × A, B, C, D, E (Chi-square tests, null hypotheses rejected at P ≤ 0.05).
Data from each question were organized in 4 × 5 contingency tables, for example, Fac, Pub, Priv, Rel × A, B, C, D, or E (Chi-square tests, null hypotheses rejected at P ≤ 0.05).
The items were not mandatory and students had the option of abstaining from each question.
Hyperlinks are provided from each question to areas on the website that help to answer each question.
Similar(42)
To further explore the relationship between liking and reproducibility, we evaluated correlations between ratings for each question from each training condition, pre- and posttraining.
From the FACT-Br survey, 26 questions were asked and the mean and median scores for each question from all the respondents were tabulated.
35 The exact scores for each question from the substitute participant were imputed for the missing values for the participant of interest.
The scores for each question ranged from 1 to 7, thus the SOC value ranged from 13 to 91.
The response options for each question range from 1 (maximum impairment) to 7 (no impairment).
Write better and faster with AI suggestions while staying true to your unique style.
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