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Stata is a statistical software with great potential that can be employed to organize, analyse, and create visual representation of data. The word Stata is a combination of the words ‘statistics’ and ‘data.’ It is an intuitive software that has a Graphical User Interface as well as a command line, making the interaction more convenient for the user. Stata is used largely by researchers in different fields including economics, political science, biomedicine, and so on. Some of the features which makes it popular among data scientists are its ability to store data in memory making it super-fast in operation, and its command-driven nature. Along with the command box, there is a menu and a dialogue box which give the users access to the built-in commands.
Beginners need to know a few facts before they can start using the Stata: firstly, they can go through the Stata manuals which are designed to be directional to make Stata easy for users. They impart knowledge about the commands, procedures, and possibilities that Stata offers, along with detailed examples of commands for beginners to learn from. Users have access to several statistical techniques when they use Stata, and the manuals guide the ways in which they can be used or interpreted. The Reference Manuals and User Guide are useful for these purposes.
Secondly, Stata has on-line help facilities which is a store of all their manuals, and when faced with any confusion, users can simply type “help
Thirdly, the four principle boxes one needs to be familiar with are the ‘results,’ ‘command,’ ‘variables,’ and ‘review’ boxes. The result box is meant to display the user’s input and corresponding output, and the procedure used for arriving at the output. In case of lengthy outputs which the user does not desire to be displayed, they can simply type in the word ‘quietly’ in front of their command. The command box is the one where the commands are typed in by users. The intuitive aspect of Stata allows it to understand commands and variables in abbreviated forms if the same abbreviation is not used for more than one factor. The Variables box reduce work for users by listing the variables which are present in a given data-set (which are stored in the memory); a user can click on a variable to include it in their data. The review box lists all the commands that have been used by the user and clicking on any of these commands would add them to the present command box.
Fourthly, beginners are advocated to use log-files which maintain a record of a user’s past sessions on Stata. This would help the user to track what they did immediately before but also something they did perhaps a month ago. The user decides the time from which they desire to begin or ‘save’ the log-files and when they want to end or ‘close’ the files.
Lastly, Do-files are largely useful for beginners trying to work on scientific projects because it saves time by easily repeating commands. Instead of having to type the command line by file, the do-files help to apply a command to the entire batch by entering them in a text file first.
Stata is used in research and students often need to use Stata in their coursework for organizing, interpreting, or visualizing data. Most universities have their license for Stata which can be collectively used by students from the university library or lab. However, if the University does not provide access to Stata, students can still use the software on their own. Stata offers a free use period of 7 days to students which benefits anyone who needs to use the software for a single project. However, if a student needs to use the software for more than 7 days, they can purchase a student’s license at discounted price from Stata’s official website.
Both SPSS and Stata are used in statistical analysis but there are a number of differences between them. Our experts provide excellent solution for Stata as well as SPSS. Given below are seven key differences between SPSS vs Stata:
We can help you with your Statistics, SPSS & Stata homework as well as R programming homework. Some key differences between Stata & R are as listed below:
Linear regression analysis, also called bivariate regression analysis, is used to generate the value of a dependant variable based on the value of an independent variable. Stata fits linear regression models under the head least-squares and once that is done, Stata can calculate predictions, standardized residuals, errors in forecasts or predictions or residuals, specification tests, variance-inflation factors, and so on. Factor variables are used in the process. Linear Regression analysis using Stata is based on seven chief assumptions, which are as follows:
When the assumptions are satisfied, two variables should be created, and scores related to each must be entered into the Data Editor spreadsheet in two different columns. Analysis can be performed with the use of code or Stata’s GUI. Results can then be interpreted and reported using Stata. Multiple regression can be performed in the same manner using Stata, however, there the variables would have to meet an additional assumption of multicollinearity, which is a case where two or more independent variables exhibit high level of correlation between themselves. In Stata, this can be verified with the help of correlation coefficients and Tolerance or VIF values.
At the time of writing this article, Stata 16 is the latest version of the software which was launched in June 2019. This updated version introduced several new features and tools, some significant ones are listed below:
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