what are statistical tools for data analysis

Statistical modeling (linear regression, logistic regression, tree model, neural network, etc.).Statistical hypothesis testing (t test, analysis of variance, chi-square test, etc.).As far as our general data analysis or academic data analysis work is concerned, the things that R can do mainly include the following aspects. The functions of R cover almost any area where data is needed. Unlike Python, R, and other open source software, there is a charge for the genuine Excel.The built-in statistical analysis is too simple and has little practical value.

The Excel data file itself can hold only 1.08 million rows without the aid of other tools, and it’s not suitable for processing large-scale data sets.When the amount of data is large, there will be a situation of stuttering.To fully master Excel, you need to learn VBA, so the difficulty is still very high.It can help you understand the meaning of many operations before further learning other tools (such as Python and R).You can do a lot of things with Excel: modeling, visualization, reports, dynamic charts, etc.Production of charts for some business magazines and newspapers (data visualization).Combine Word and PowerPoint to create data analysis reports.Simple statistical analysis for students or teachers (such as analysis of variance, regression analysis, etc.).Data management and storage of small and medium-sized companies.Data processing work under general office requirements.

What are statistical tools for data analysis