Prices of statistical help
Prices of statistical help are related to the level of complexity of the project. Around 85% of the projects are very standardized, data are complete, and statistical methods are known. In these circumstances prizes are low, and the pace of the realization is high. This situation is very frequent in social sciences (e.g. quantitative methods, and experiments), and less frequent in life and health sciences (e.g. life endpoints, patient dropouts, measurement errors). The next 15% of the projects are related to high prices and long-term cooperation. These projects need high-end methods and cutting-edge thinking. In that situation, repeated consultations and testing of individual solutions are required to ensure a well-done work. Summarising, the average cost of standard (advanced) projects is around 350$ (1000$) and the boundaries are in between 250$ (400$) and 500$ (no limits).
The time of implementation of the statistical solution in projects is related to the elements mentioned above. The complexity of projects is the main factor that influences the time of work. Simple projects related to verifying a series of hypotheses, and simple or known modeling techniques (SEM, regressions) last two or three days. More complex e.g. text and data mining, machine learning, big data, random and fixed effects, and nuanced effects in structural equation modeling can take weeks and even months to complete.
We provide advanced statistical help for scientists and for Ph.D. students. We can help you long before the data will be collected. We are methodologists and statisticians with a very long practice. Our eyes see many projects, poor (and big) data, tears, great and weak solutions, methodology designs, measurements, and also good and bad people. Through 12 years of specialization, we gathered essential skills which help us to provide extraordinarily, but scientifically embedded, solutions and ideas for our clients and friends.
We provide quick statistical help for students (around 1-2 days) in their thesis. If your tutor is not very helpful or you have a problem with a methodology, research proposal or analysis development we can offer our statistical help. We have AI-based software that calculates the results of analyses, makes and describes figures and tables, and writes conclusions. In such student projects, we help quickly and painlessly. We understand your problems, which we will solve quickly and cheaply.
We ourselves go through or have gone through the hell of a Ph.D. thesis. We know everything about learned helplessness, depression, anxiety, and other Ph.D. student’s things. So, we will provide you substantive help, the best solutions for your projects, and, of course, hope with understanding. Our solutions, recommendations, and advice, as well as our embedding in current science, will make the statistical analyses resistant to criticism before and in the course of your defense.
If you apply for money from an institution, each element of your proposal will be carefully assessed. We can ensure that your methodology and analysis proposal will be well presented. We have extensive experience in this. The description must be not very detailed, but very understandable :) Let non-statisticians not be nervous :)))
No. We are experienced scientists with some the non-statistical expertise. Our team of science-related members does different things.
We know how to prepare meta-analyses in medicine.
How to prepare complex research methods that challenge (or limit) alternative explanations.
We know how to prepare measurement scales in psychology and management.
We know many methods of cause-and-effect reasoning.
We can program and automate analytical processes in business.
We know how to teach machines and statistically control decision-making processes at the industrial level.
Develop products and improve them.
Write, review, and evaluate scientific articles. Not only the analysis and results section but the whole meaning of written prose.
General science and science-based reasoning. As written before, we have long experience in different field related to statistics (social sciences, economics, health, and management) and, more generally, STEM fields (Science, Technology, Engineering, Mathematics).