# User Behaviour on Google Search Engine

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5 108 Figure 2. Links position - Quantitative Data Analysis We will do quantitative data analysis because the data collected will be numeric in form and we will use statistical techniques to draw conclusions about participant behaviour. The analysis will be made using correlation analysis with a Data Analysis Program in order to test the relationship between the percentage of PPC and Organic links visited, each group of Google search engine knowledge, and the average position of the websites visited on Organic searches from each group. The analysis of the data collected will be studied through Pearson Correlation and Linear Regression to determine how hard is the relation between variables. Results - Test Hypothesis 2 H2: Users with low Google search engine knowledge visit more Pay Per Click links on Google search engine in percentage than users with high knowledge.

8 111 Cross- products 1324, ,967 Covariance 11, ,420 N **. Correlation is significant at the 0,01 level (2-tailed). Based on Pearson Correlation at 95% confidence interval, the result of the test indicates a significant value of 0,000, which is less than 0,05 and it means that the null hypothesis should be rejected. The figure interprets that there is significant relationship between the result in the test and the average of Organic links visited. On the other hand, based on Pearson Correlation Coefficient, the relation between variable is strong and positive, because is: 0,706, like we can see on the table 3. We consider the relation medium-high, because from 0 to 1, we can say that 0,5 is medium and 0,75 high. Secondly, using linear regression with the same variables, we will be able to know how influenced are both variables, the table 4 show us how the influence of a 49,9%, on the average of the Organic links visited and the punctuation on the test about Google knowledge, which is a high result. Table 4. Hypothesis 3 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1,706 a,499,495,98869 a. Predictors: (Constant), Test Punctuation (0-40) - Test Hypothesis 1 H1: Users with different Google search engine knowledge are different when using it. This Hypothesis is like a summary of the second and third Hypothesis. The results we took from the Hypothesis 2 is that the correlation is significant (0,00 lower than 0,05) and the relation between variables is weak-medium (r=-0,358). On the other hand, from the Hypothesis 3, we got the results that the correlation is also significant (0,00 lower than 0,05) and the relation between variables is medium-high (r=0,706). So, we can conclude that the users with different Google search engine knowledge act differently when they are using it. Discussion H2 and H3 are not enough to disprove H1, because there are other aspects where users can act differently using the search engine. If the result would be negative for H2 and H3 We couldn t say that H1 is not true, but in my case both results are positive, and we can also prove H1. Saying that users act in a different way is not very difficult and complex. It is obvious that with different experience and knowledge about some application, program, website they will act different, because they know its performance better. In my case, it is easy to know that there are differences using the search engine, but it is difficult to prove it and the most important, to take advantage from these differences and to improve the SEO and SEM techniques.

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