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b) Independent variables: Gender
To test the relationship between gender and the usage of internet, we use the independent sample t-test for this section. We use gender(general question) as the grouping variable and the gender(independent variable) as tested variable.
Table 1
Table 2
From the table 1 above, t, We found that the mean for the 'male' group is higher than that of the 'female' group. That is, male on average are more frequently using of the internet compare to female. There is a significant difference between the two groups because the significance level are less than 0.05.Therefore, we can say that there is a significant difference between the female and the usage of internet. Thus, male had significantly frequent in using the internet compare to female.
(c) Predictors: (constant), Importance of Internet services
Coefficients (a)
From the table above, we can find that the R= 0.524. This means that the there is a positive relationship between independent variables and dependent variables and the relationship are quite strong. The R square value, 0.403 means that all items in gender explain 40.3% of the factors increase the usage of internet. For the standardized coefficient, if the importance of internet services towards usage of internet increase by one unit, the usage of internet will increase by 0.557 units.
For a alternative hypothesis to be accepted, the significant level must less (<) than 0.05. The significant level of usage of E-Learning variable is 0.000, which is less than 0.05 and thus the alternative hypothesis, there is a relationship between the importance of internet services and the usage of internet are accepted.
Table 2.1
Table 2.2
Table 2.3
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