# 2x3 weird design

My experiment tests how frequently people in two different countries use different types of computers. Assume, that there are only three types of computers (desktop, laptop and tablet) . I am interested to see the difference of usage between types (within each country) as well as between two countries (for each type). I conducted the survey in which participants ranked how frequently they use each type (1 - low frequency, 10 - high frequency). I got the following avrage results (error bars are SEM):

For desktop there is almost no difference between countries, but there is quite a large one-side difference for laptops and desktops. But given that there are only three types of computers, how it can be that higher frequency for two types in country 1 is not compensated by higher values for other type for country 2? Am I right with my concern or there is a flow in my logic?

To resolve the issue, for each participant I calculated relative frequency by dividing the frequency value of each type by sum of frequencies. So, now the previous problem was solved (see the graph below). But: a) the applied normalization altered the relationship, so now the biggest difference between countries is for desktops; and b) how I can run now 2-way ANOVA for these data given that the values are not independent (in each country they summed up to 100).

What is the correct way to tackle my problem?