1. Descriptive statistical analysis: This is the most basic analysis method, which is used to describe the basic characteristics of data sets, such as mean, median, mode and standard deviation. This method can help us understand the basic situation of the data set.
2. Exploratory data analysis: This method is mainly used to find patterns and trends in data sets. Commonly used exploratory data analysis methods include histogram, scatter plot and box plot.
3. Correlation analysis: This method is used to study the relationship between two or more variables. Commonly used correlation analysis methods include Pearson correlation coefficient and Spearman rank correlation coefficient.
4. Regression analysis: This method is used to predict the change of a variable according to other variables. The commonly used regression analysis methods include linear regression, multiple regression and logistic regression.
5. Cluster analysis: This method is used to divide the samples in the data set into several groups or "clusters", so that the similarity between samples in the same group is high, while the similarity between samples in different groups is low. Commonly used clustering analysis methods are K-means clustering and hierarchical clustering.
6. Principal component analysis: This method is used to reduce the dimension of the data set while retaining the main information of the data set. The commonly used principal component analysis method is PCA (Principal Component Analysis).
7. Factor analysis: This method is used to find out the * * * same factors that affect multiple variables in the data set. Commonly used factor analysis methods include maximum likelihood method, principal axis method and so on.
8. Time series analysis: This method is used to analyze data that changes with time. Commonly used time series analysis methods include autoregressive model, moving average model and so on.
9. Text mining: This method is used to extract valuable information from a large number of text data. Common text mining methods include word frequency statistics, TF-IDF (word frequency-inverse document frequency) and so on.
10. Network analysis: This method is used to analyze the relationships and patterns in the network structure. Common network analysis methods include node centrality and community discovery.