Hey, my topic is impact of digital marketing on retail banking sector growth and I have collected data for my research and now I need to test it but I have no ideas as which test would be best for my case. I have 65 respondents forming 2 groups. I need to compare them and find the association between them. What test would be the best? Chi-square, T-Test or ANOVA?

I would suggest you to first identify the type of variable. Is it categorical, quantitative or nominal? you can only decide which test you can use like Wilcoxon, paired t-test, one sample t-test and chi-square.

I think you should use a T-test as your research methodology rather than using any other test. T-test will help you to compare whether two groups have different average value or not as your data is vast. You should avoid ANOVA because it is usually used to compare three or more variables and you have just two variables to compare.

I would suggest you to use Chi-square test to find a relationship between categorical variables and the t-test for the comparison.

There are so many information available online on statistics. Read from this link for information about such statistical problems.

http://www.phdstatistics.com/blog/

Also, take a look at this link: http://www.resourcesvalley.com/learn-inferential-statistics/

I think ANOVA is the best for comparison based study. I don’t remember completely but I think I also used ANOVA for the same kind of data. So, you can also use it. Also, tests are usually decided on the basis of a hypothesis, so you need to refer them before settling on the tests.