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Thus, we have tried to determine whether there is a correlation between the views and the number of edits of each student category and for the whole sample. The result obtained and interpreted according to Colton (1974) is (DruganTigan, 2005): 1. In the group that had an average of less than 15 views/ month, we calculated the Bavaris- Pearson correlation coefficient and we obtained r=0.17
200 Correlation View/Page Edits 150 View 100 50 0 y = 4.752x + 106.1 R² = 0.465 0 2 4 6 8 Page Edits Figure 7 The Regression Line The regression line that approximates the tendency of the dot cloud is based on the equation y = 4.752x + 106, 1 and the coefficient of determination R2 = 0.465. The trust level of this equation is good, with a coefficient of determination of 0.465, which means that there is a correlation between the two activities for 4 users in 10 for this group. 3. Within the group with a rich activity, namely more than 30 views/ month, the value of the Pearson coefficient was r=0.14
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