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|Data manipulation and cleaning||Time series analysis||Natural language processing||Statistical learning|
|Exploratory data analysis||Cluster analysis||Social network analysis||Decision trees|
|Regression analysis||Survival analysis||Dimensionality reduction||Random forests|
|Support vector machines||Neural networks||Model selection and evaluation||Web scrapping with SAS|
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Ans: SAS (Statistical Analysis System) is a popular software suite for data management, analytics, and business intelligence. It is widely used in a variety of industries, including healthcare, finance, and marketing, to help organizations make data-driven decisions.
Ans: Some advantages of using SAS include:
Flexibility: SAS can be used for a wide range of data analysis tasks, from simple data manipulation to complex statistical modeling and predictive analytics.
Scalability: SAS can handle large volumes of data and is suitable for both standalone and distributed computing environments.
Integration: SAS can be easily integrated with other software and databases, allowing users to work with data from multiple sources.
Support: SAS has a large and active user community, and offers extensive documentation, training, and support resources.
Ans: SAS programming assignments can be challenging for a number of reasons. Some common challenges include learning the SAS programming language, dealing with large and complex datasets, and understanding the output and results of your analysis. Additionally, SAS programming assignments often require a high level of attention to detail and careful planning, which can be difficult for some students.
Ans: To improve your SAS programming skills, you can practice by working on a variety of SAS programming assignments and projects. You can also read SAS documentation, tutorials, and books, and attend SAS training courses or workshops. Additionally, joining a SAS user group or forum can provide you with access to valuable resources and support from experienced SAS users.
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