* Descriptive statistics These tools are used to summarize and describe data, such as mean, median, mode, standard deviation, and variance.
* Inferential statistics These tools are used to make inferences about a population based on a sample, such as hypothesis testing and confidence intervals.
* Econometrics This is a branch of statistics that is used to analyze economic data, such as regression analysis, time series analysis, and panel data analysis.
* Machine learning This is a field of computer science that deals with the development of algorithms that can learn from data, such as artificial neural networks, support vector machines, and decision trees.
* Data mining This is a process of extracting useful information from large data sets, such as clustering analysis, association rule mining, and text mining.
The specific statistical tools that are used for financial research will depend on the research question being asked. For example, if the researcher is interested in describing the distribution of stock prices, then they might use descriptive statistics. If the researcher is interested in testing a hypothesis about the relationship between stock prices and interest rates, then they might use inferential statistics.
It is important to note that statistical tools are not always the best way to answer financial research questions. In some cases, it may be more appropriate to use qualitative research methods, such as interviews, surveys, and case studies.