English language editing and statistical consulting services for scientists, students, and publishers worldwide
Many scientific fields rely on statistical concepts and analytical tools. But for many researchers, their training in the use of inferential statistics might not feel sufficient, or they are increasingly pressed for time to do them. This adds a second hurdle faced by non-native English speakers (ESL), who must also communicate their research internationally in the English language.
Here at Statistical Scientific Editing, the aim is provide you with friendly, professional and timely help in completing your research project and communicating it the best way possible. Both statistical consulting and related English-language editing services of your work are available, to help you succeed. Remember, conducting and reporting statistical analyses properly is an ethical responsibility when doing science. Writing good, clear English alone may not get your paper published if the statistics used are improperly done and reported. Don’t risk giving peer reviewers a further excuse to reject your paper.
Here at Statistical Scientific Editing, the aim is provide you with friendly, professional and timely help in completing your research project and communicating it the best way possible. Both statistical consulting and related English-language editing services of your work are available, to help you succeed. Remember, conducting and reporting statistical analyses properly is an ethical responsibility when doing science. Writing good, clear English alone may not get your paper published if the statistics used are improperly done and reported. Don’t risk giving peer reviewers a further excuse to reject your paper.
Improve your publication chances
Timing matters. Where is your research project at?
In academia, there is increasing pressure on established and career-minded younger researchers to publish not only in so-called 'high impact' journals but also to publish as many papers as quickly as possible. This is worrisome, since it favors quantity over quality in research, and fosters bad incentives that can promote unethical behavior and poor research methods. Making matters worse are "predatory journals", whose sole motive is profit and deceit. Clearly, such trends threaten scientific integrity and will corrupt science and its standing if not mitigated somehow.
One area that perhaps suffers the most is the proper use and reporting of statistical analyses in journal articles. This can take various forms, accidental or not, such as inflated statistical power (from pseudo-replication or inappropriate modeling), too small sample sizes, so-called "P hacking" practices (data-dredging, "fishing" for statistical significance), lack of randomization, applying incorrect statistical tests and models to sampling designs and data structures, failing to check their assumptions, insufficient transparency, and so on.
Collectively, these trends worsen an existing reproducibility problem in many scientific fields that rely upon statistical inference. It can lead to published results that have exaggerated support or are completely unfounded (i.e., false-positives). This misuse of statistics leads to unreliable and spurious factual claims that poison the scientific literature, waste limited resources, and further harms the public's trust in the scientific enterprise and the knowledge it provides.
One area that perhaps suffers the most is the proper use and reporting of statistical analyses in journal articles. This can take various forms, accidental or not, such as inflated statistical power (from pseudo-replication or inappropriate modeling), too small sample sizes, so-called "P hacking" practices (data-dredging, "fishing" for statistical significance), lack of randomization, applying incorrect statistical tests and models to sampling designs and data structures, failing to check their assumptions, insufficient transparency, and so on.
Collectively, these trends worsen an existing reproducibility problem in many scientific fields that rely upon statistical inference. It can lead to published results that have exaggerated support or are completely unfounded (i.e., false-positives). This misuse of statistics leads to unreliable and spurious factual claims that poison the scientific literature, waste limited resources, and further harms the public's trust in the scientific enterprise and the knowledge it provides.
Who can benefit from these services?
Researchers and publishers in academia, and other public and private entities:
- Professors facing time constraints and tight deadlines
- Post-doctoral scientists
- Graduate-level students (PhD or MSc)
- Staff scientists at NGO/NPO institutions or working in government
- Independent consultants in various fields (nature conservation, environmental assessments, etc.)
- All researchers whose native language is not English (ESL)
- Private sector clients who need their data and trends analyzed
- Publishing houses and journal editors who must safeguard the quality of their scientific publications
- Undergraduate and CEGEP students in Quebec