In my thesis I calculated two of this method correlation and regression. But I can't understand which is better for data analysis.
It really depends on the question. Linear regression usually contribute more information about the relationship. Have a look at this publication and see if it provides the information you require.
Article Statistics review 7: Correlation and Regression
If your goal is to understand the relationship between two variables, correlation is the ideal test. However, if your goal is to identify the significant predictors of a dependent variable, regression is the test you need to opt for. It ultimately depends on what your goal is.
Impossible to give any sensible answer without knowing what are your data, your experimental design and your research question.
Application of both statistical tools depends on the context of your thesis and the problem statement and related hypothesis being addressed in your research.
Correlation is for evaluating and plotting relationship between data in general and variables within a data to be specific.
Regression brings out the nature of the relationship between data./ variables and is also used to make a predictive plot of this relationship.
The research objective, problem statement and hypothesis should direct the application of both these statistical tools.
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