To perform a meaningful statistical analysis and examine research questions comprehensively and accurately, a statistical software program is necessary. Statistical programming is generally essential for this purpose. However, there is no universally applicable, one-size-fits-all statistical programming approach. Statistical programming varies depending on the statistical software program used, and—especially when it comes to troubleshooting—it often requires years of experience or specific, time-consuming training.
You, too, can benefit from professional statistical programming in SPSS, R, Stata, or SAS for your project. We have already successfully completed statistical projects for over 3,000 satisfied clients.
Experience, Expertise, and Quality
for your statistical programming.
NOVUSTAT supports you with statistical programming and analysis using established statistical software. Depending on your research question, your data, and the required methodology, we’ll guide you through working with SAS, MATLAB, R, Stata, and Python —from the initial conceptual framework to the structured implementation of your analysis.
We provide expert support when you're writing statistical programs in SAS as part of your analysis.
For more complex statistical analyses, MATLAB is the application of choice. Novustat also has expertise in the professional use and programming of this statistical software.
Our employees also achieve impressive results when performing statistical analyses using R.
With professional statistical programming, many steps can also be carried out in a clear and rigorous manner in Stata.
We'd be happy to assist you with your Python statistics projects by providing data analysis and programming support.
Our statisticians will review your requirements and recommend the appropriate statistical software and approach.
Customer reviews and reference projects demonstrate how NOVUSTAT supports projects in the field of statistical programming. For more than ten years, we have been providing expert, practical, and proven support.
Statistical programming at NOVUSTAT encompasses the development, customization, and automation of customized data analysis solutions. From program design and implementation to data transfer and data preparation, all the way to user-friendly applications and automated reports, we provide you with expert support at every stage of the project.
We are happy to assist you at every stage of statistical programming: from program design to implementation and subsequent test runs.
We'd be happy to search your program code for errors and fix them, further develop your program (or your predecessor's), and adapt it to new requirements. We'd also be happy to handle all statistical programming: You provide the data, and we'll deliver the results.
In addition, we can help you extract data from a database or perform a seamless data migration from one format to another on your behalf.
In addition, we also develop user-friendly interfaces for data entry, statistical analysis, graphical representations, and automated reporting. Once created, you can reuse them as often as you like; the results will then automatically adjust to reflect the current data.
No matter which tool or programming language you're using (SPSS programming, R data mining, SAS, MATLAB, or Stata), you can count on us! Every analysis described on our website can be automated.
All programming steps will be discussed with you in detail afterward, so that each step is clear and easy to follow. You don't need any programming knowledge!
Statistical data analysis can be automated and made repeatable with the help of statistical software. In principle, you can use any programming language for this, as they all support the reading of data from files (e.g. a csv file), basic arithmetic operations and repetitions. It is as unnecessary as it is time-consuming and error-prone to compile statistical evaluations from basic arithmetic operations and loops. For this purpose, there are programming languages such as R that have been specially developed for statistical evaluations.
This makes automating statistical procedures particularly easy. Numerous supplementary packages are available for every conceivable statistical method and industry. These programming languages allow you to implement standard statistical procedures with minimal effort and make it easy to adapt them to your specific needs. Statistical programming also enables you to import or export files created with other software—for example, importing SPSS files into R.
Most statistical tools also support statistical programming for repeatable scripts and analyses, such as business intelligence software, SPSS, MATLAB, Stata, or SAS.
Statistical programming makes it possible to import data in a structured manner, process it automatically, and output results flexibly. This allows both different data sources and custom output formats to be reliably integrated into the workflow.
A statistical program prefers to accept data from files as long as the data is separated by any separator (comma, semicolon, tab space, etc.).
By the way, you can obtain files in this format automatically using online survey tools; alternatively, you can create them by scanning a paper survey or manually entering the data into Excel.
It is crucial that your data be in a machine-readable format. That way, it is equally suitable as input for statistical programming and for other statistical tools.
You can of course also write a program in which you enter the data manually and then save it as a file. Statistical programming gives you every opportunity to design your work process!
You have complete freedom when it comes to creating output data.
You can write the results to a file that can be further processed by other tools (e.g. graphics tools) and allows the data to be output on the screen or in another human-readable form.
The statistical program can also take over the graphic display itself or generate entire reports including graphics in Excel, Word, html or pdf format.
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If you want to perform the same analysis repeatedly —for example, on data from different years or different samples—you can avoid having to manually repeat each step of the analysis by using a statistical program that automates this process, thereby increasing the efficiency of your work.
Even when similar data is to be analyzed by different employees in exactly the same way to achieve comparable results, it is worthwhile to use statistical software. This prevents different individuals from arriving at different results due to subjective assessments or differing approaches. With a statistical program, you can specify, implement, and repeat a standard procedure for data analysis as often as you like.
At the same time, it serves as a kind of log. Every step taken during the evaluation is clearly defined by the program. You can add source code comments to it and thus also document the reasoning behind your approach.
Large amounts of data (big data) and complex analyses generally cannot be handled without statistical programming!
