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Moderator analyses showed variation in results based on methodological-level (e.g. study design) and sample-level (e.g. gender) variables.
At the end of the research, it has been determined that there is meaningful difference between the reasons of absenteeism and class and gender variables.
The summary statistics also show that there are statistically significant differences between entrepreneurs and non-entrepreneurs in terms of income, age, and gender variables.
Attention is paid particularly to the caste and gender variables, due to the focus on such inequalities by national policies and development programmes.
This research applies a quantitative design where descriptive statistics are used for the student characteristics and design features data, t-tests for the age and gender variables to determine if they are significant in blended learning effectiveness and regression for predictors of blended learning effectiveness.
Data supplied included age and gender variables.
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According to finding, gender variable did not explain the differences in the compound variable "the number of formative e-tests".
Finding shows the practical importance of emotional management group training, while gender variable was not effective in that.
Demographic variables included the gender variable as well as age, race, employment and marital status.
The gender variable (GEND) was dichotomously coded (boys as 0 and girls as 1).
The size effect introduced by the gender variable (Cohen's d = .47; r = .23) can be seen as moderate but significant.
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CEO of Professional Science Editing for Scientists @ prosciediting.com