Academic research covers so many problems and techniques. The data collection methods and types are also different for different research problems. Suppose, you have to deal with statistical research problems. In this task, they have to use different software that can give you the best end results. Before using any software, it is necessary to understand the purpose and features of all relevant software. As per the importance of software use, this article aims to discuss about some statistical software, including R and Stata.
What software do students use in academic research for quantitative analysis?
Quantitative analysis deals with bundles of numeric data. Researchers use different software in academic research to have the best end results from qualitative data. In the list of best software for quantitative analysis, you can find SPSS, STATA and R. Starting from SPSS, its acronym is Statistical Package for Social Sciences, and is used to analyse and interpret conclusions based on its results. On the other hand, Stata is a software that works very quickly on large data and does not demand for experience of the researcher.
Apart from SPSS and Stata, R is an advanced technique to deal with quantitative data in academic research. The use of Stata and R is increasing with respect to time because of their amazing features. Most of online dissertation help providers suggest students to use Stata at the start of their research career. This suggestion does not mean R is not good, but it is somehow complex to deal for fresh researchers.
Is It Better To Learn Stata Or R?
Stata and R both are used to handle data. Both of these work well to represent data in a graphical form. Each of them has a particular way of representing the data. Some of the researchers take Stata as the best software for their academic research. On the other hand, some of the researchers take R as a good one. The selection of software and language can vary based on the purpose of the research. Let’s discuss which software is better to learn for academic research.
Data Type in Stata
Stata gives you a complete control over imports and exports. Also, you can use different features of Stata for working on Unicode in academic research. In Stata, you can handle all data types. These data types are mentioned below:
- Multilevel data
- Discrete data
- Multiple-imputation data
- Time-series data
- Panel data
Graphical Representation of Data
Another best thing about Stata is its graphical representation. Here, you can make quality graphs that can represent your data in a well-mannered way. In other software, you can find a problem related to the export of graphs. In the case of Stata, you can export the graph in the the following forms:
Other than export, you can change the format of graphs as per your own choice. You can amend the text, line, title, and other stuff easily.
In academic research, the evolution in technology cause many differences. You have to understand the importance of old research and its frequent use in future. You can say that the old research works as a foundation for new work. Many times you have to understand the old work so that you can better work on its advanced aspects. In Stata, you can see new features with evolution in technology, but the interesting thing is that it always facilitates you to read old versions of data. In the same way, Stata will facilitate in future also.
In R, you can find different varieties of techniques related to statistics. It includes linear as well as non-linear modelling. Furthermore, you can get clustering and time-series analysis by using R. Similarly, you can enjoy different techniques related to graphical representation as well.
In academic research, the use of R works well to generate a well-designed graph. You get the quality plots of the graph through R. Here, you can add mathematical symbols as well as equations that are relevant to your graph. At the time of designing a graph, you are supposed to be conscious of every little change.
R is free software that facilitates in many aspects of academic research. In this software, you can analyse as well as calculate the available data in a good way. Researchers take R as an easy and productive language for academic research.
Is R Easier To Learn Than Stata?
If you compare Stata and R, it is easy to learn Stata. For Stata, you just have to develop basic skills to use different features of the software. On the other hand, R requires proper training for its language. Researchers take it difficult to learn a language as compared to the features of the software. Most of the tasks are very simple to analyse on Stata. Still, it is easy to learn Stata as compared to R. In R, you are supposed to learn all of its basic skills.
Do Economists Use R?
Economists do not work on a single language, but they require a different set of languages. It includes Matlab and Python. Another language that is used very frequently is R. The reason why most of the researchers prefer R is its open sources.
Stata is statistical software. By using Stata, you can better represent your data and its result in graphical form. Also, it is easy to analyse data on Stata. It is very important to understand the purpose of using Stata software. The researchers use Stata to identify the pattern of data in academic research. On the other hand, R is a software which works for language and environment. The purpose of using R is to handle statistical data and then represent it in the form of graphs.