Statistical evaluations are the bridge between your theory and practice

You have a specific topic, but you do not know how to check it on the basis of practice or how a statistical evaluation works? Then you are exactly right with our team. Basically, there are two ways to work empirically: qualitative and quantitative research. Statistical evaluations are an instrument used by quantitative research. We will find the right methodology for you and make your topic measurable.

Data collection method:

How do I get data?

In addition to the methods of statistical evaluation for the later calculation of the data, there are also so-called methods or methods of data collection. Regardless of scientific discipline (eg economics, medicine or psychology), there are three different procedures: observation, interviewing and content analysis. Survey is the most commonly chosen method, but it does not necessarily have to be the right one. There can be distortions that occur automatically when the subjects are allowed to classify certain things themselves. Observations or content analysis can be more objective or a good complement to match survey results. Either way, it is data collection procedures that must first be established before a statistical evaluation can take place.

What should a data record look like for statistical evaluation?

You have conducted a survey yourself or collected data (eg from a stock portal, state statistics or medical-clinical studies) and have now reached the point where you need support as part of your empirical part? If possible, your data should already comply with the standard statistical standard reading standard to facilitate statistical evaluation for our ghostwriter. The basic principle is: per file column (eg Excel or CSV) = one variable and one cell per cell below it. In the end, your ghostwriter only needs to know which record’s content belongs to which hypothesis or research question. The statistical evaluation is now nothing in the way.

Fundamentals of statistical evaluation in scientific papers

Statistics is a tool that either structures data (descriptive statistics) or tests hypotheses (inferential statistics). While descriptive statistics (such as averages or frequencies) are still relatively easy to use for statistical evaluations even by non-stained users, this is already moderately more complicated in inferential statistical methods that use different assumptions of probability theory. So you have to first choose which method fits the review of your research hypothesis or question and is then faced with the task of understanding the statistical method as well as to apply for the statistical evaluation. For example, when examining the applicability of a statistical method, there are a multitude of hurdles (eg normal distribution of data or regression diagnoses). If requirements are not met, it must be assessed whether a procedure is nevertheless applicable or whether a suitable alternative can be used.

Statistical evaluation for the bachelor thesis, master thesis or dissertation

Just as the academic degrees to be obtained later differ in their value, ghostwriting also has to differ in its claim depending on the research project. For each project, which aims at a statistical evaluation, an author is used, who knows the statistical requirements of the respective working level knows and to apply, even if it is nowhere explicitly written in your records. An example of this is the testing of quality criteria for measured facts, which must be more intensive and more demanding in a dissertation than, for example, in a bachelor thesis. Another example is that the supplementation of α- and β-errors in a very differentiated view usually only starts from a statistical evaluation at the master’s level and is required by the students. We consider such and other comparable contents for you by consulting you individually from the beginning.

Types of hypotheses

You have probably heard the term hypothesis more often. We also use it in this section. However, there are two fundamental differences in the meaning of the term hypothesis, which we would like to break down here for the sake of clarity. In your scientific work, for example, with the goal of a statistical evaluation formulate a hypothesis that you intend to review. This hypothesis is usually a research hypothesis or at least a first thesis. Simplifiedly, research hypotheses can be differentiated into so-called contextual hypotheses (eg, the more online targeting a company operates, the more successful the company is) or differentiation hypotheses (eg, men are more empowered in their profession than women). In order to test a research hypothesis by means of statistical evaluation, a statistical procedure is needed whose statistical hypothesis fits the research hypothesis. A statistical hypothesis is the smallest form of the hypothesis. There are zero (i.in. no effect) and alternative hypotheses (i.in., an effect) of a particular test procedure and these must be analyzed in advance to be able to test the research hypothesis with a method.

Different data

For the sake of simplicity, data that you or we collected via one of the data collection methods is referred to as measurement data for statistical evaluation.

However, in order to select the right statistical method for evaluating measurement data, it is first necessary to be aware of which data is to be evaluated.

A professional statistics program is half the rent

Hardly anyone writing a thesis is a graduate in statistics, but most students or graduates are statistical users. This means that one has to understand how the calculation concept of an applied procedure acts in order to be able to interpret the results of the statistical evaluation and make them usable for one’s own work. It is against this background that very powerful software applications exist that implement the various statistical methods needed. Obtaining a software will not be as economical for one-time authoring as a costly training in a program.

Our website provides analysis based on a variety of statistical software applications (eg MatLab, Pathos, Python, R, R-Studio, SAS, SPSS and STATA and other programs for statistical evaluation) and authors who master these programs and who are responsible for Your research project can make appropriate analyzes.

Conclusion

Regardless of which scientific discipline you are from, you are in the right place with us. Before embarking on literature for weeks, it may be useful to hire a specialist expert from our website to work on your project efficiently and effectively.

The author who realizes your project has at least a master’s degree in a scientific discipline that suits you and supports you in the statistical evaluation – or more.

The price is always based on the effort that arises. Of course, if you want to outsource all the work, the overhead is higher than if you only needed point support and made good preparations.