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Statistical computing field main motive is to provide you with the proper guidance and skills necessary for medium to high level manipulation of data and management in preparation for the analysis of statistical data which is generated in health and medical research in general. Specifically, you gain experience in manipulation of data and management by using the two important software of Statistical packages (Stata and R) also acquire fundamental programming skills for efficient use of each of these packages of software. So for more information read this blog till last let’s have a look on the given information.
Statistical Computing
Statistical computing provides you with the introduction to the use of statistical computing in the MINITAB, SAS, SPSSX and BMDP software packages, with a special emphasis on SAS and MINITAB. Graphics of Statistical capabilities of SAS GRAPH and MINITAB will also be included. It may be placed on the following points: Data entry; data editing;
Production of statistical summaries in the form of tables, graphs, charts and plots for report writing purposes; Management of Data methods for large scale survey data. Other points included: subset analysis, updating, and missing data methods. Topics of Statistics may also be noted such as correlation and regression analysis; Another two sample problems; and analysis of variance.
Let’s check out benefits of learning Statistical Computing
- With statistical computing you will Gain knowledge in data manipulation and management using the two leading statistical software packages (Stata and R).
- You will easily know the process of how to display and summarize data by using software of statistical.
- You can easily Familiarize yourself with cleaning and checking data properly.
- You will easily learn how you can link files with the help of unique and non-unique identifiers.
- You have to learn the process of fundamental programming skills
- Easily learn about the important principles of confidentiality and confidentiality in the storage of data and analysis of management.