Hey guys, I urgently need help with a Rstudio project that is getting impossible. I am not very familiar with the software as this is unrelated to my studies, but as it is an important one-time project I thought to get extra help from the community itself.

Using the European Value Study data-set (EVS_UK_full), I am measuring two variables:

- Dependent variable: attitudes towards immigration (are immigrants good or bad for the development of the country?) with answers going from 1 to 5, where 1 is very bad and 5 very good.
- Independent variable: income of respondents per year (household) with answers going from 1 to 10, with 1 representing respondents with less than 11,619£ a year and 10 with more than 64,070£ a year.

I have done all the basic measurements to calculate the central tendency, the causal relationship. However, I don't seem to be familiar with testing the hypothesis that: a low level of income is linked with a negative attitude towards immigrants, while a high level of income generates a positive attitude towards immigrants. Apparently, to do so, I will need to go through the right statistical test, the bivariate hypothesis testing (tabular analysis - chi-square, difference of means - t-test, correlation coefficient, linear regression, or logistic regression, depending on the type of variable). After that, I will need to do the actual regression analysis and the multivariate regression analysis, which I really am not familiar with. I am just seeking for help in terms of the steps I have to take, theoretically speaking. For instance, given the variables stated above, what steps are best to measure the hypothesis given all the types of test to be done, what kind of variables are the two stated above? categorical, ordinal or interval?

Please let me know! Hope it is all clear and looking forward for this project to reach an end! As someone absolutely not familiar with coding, it really does get frustrating.