The Statistical Crisis in Science

The Statistical Crisis in Science

4/1/2015

link

http://www.americanscientist.org/issues/feature/2014/6/the-statistical-crisis-in-science/99999

summary

This article discusses the statistical crisis in science, focusing on the issues of reproducibility and reliability of scientific research. It highlights the prevalence of publication bias, where positive results are more likely to be published, while negative or inconclusive results often go unpublished. The article also delves into the misuse and misinterpretation of statistical methods, leading to false conclusions and a lack of robustness in scientific findings. It emphasizes the need for better statistical training for researchers and the importance of open data sharing and replication studies to address this crisis. Overall, the article sheds light on the challenges faced by the scientific community in maintaining the integrity and credibility of research.

tags

scientific research ꞏ statistical analysis ꞏ reproducibility crisis ꞏ scientific methodology ꞏ data integrity ꞏ research quality ꞏ statistical methods ꞏ data analysis ꞏ scientific experiments ꞏ scientific publishing ꞏ scientific rigor ꞏ scientific accuracy ꞏ data interpretation ꞏ research ethics ꞏ scientific validation ꞏ research transparency ꞏ research bias ꞏ research misconduct ꞏ p-value ꞏ hypothesis testing ꞏ data manipulation ꞏ research credibility ꞏ scientific community ꞏ data-driven decision making ꞏ data reliability ꞏ research standards ꞏ research integrity ꞏ data reproducibility ꞏ data falsification ꞏ scientific knowledge ꞏ scientific objectivity ꞏ scientific evidence ꞏ research validity ꞏ research reliability ꞏ statistical significance ꞏ research design ꞏ data collection ꞏ data processing ꞏ research honesty ꞏ research reproducibility ꞏ scientific inquiry ꞏ scientific discovery ꞏ scientific progress