Statistical collection, modeling, and analysis are critical exercises when conducting scientific research. The importance of statistics in research is difficult to overstate because every advancement in computing technology, medical science, and other scientific endeavors occurred because of accurate statistics. In fact, author H.G. Wells once said, “Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write.” Let’s look at the uses of statistics in research and determine if Wells is right.
A December 2018 report in Medical NewsToday detailed the importance of statistics in pharmaceutical research. In particular, pharmaceutical researchers use randomized control trials to determine the effectiveness of new drugs and treatments. Participants in a drug trial are given treatments, with half receiving the actual treatment and half receiving a non-active version of the treatment. Researchers observe participant reactions to the treatments through interviews and physical exams.
By placing each participant into random groups, researchers can get close to determining the genuine impacts of the trial treatment. In statistical terms, researchers calculate a p-value for each study to determine if the results are significant or occurred by chance. Academic programs like Michigan Technological University’s online Masters in Applied Statistics train professionals on how to conduct similar research projects.
Exploring the Cosmos
Studying far-away planets, stars, and stellar phenomena is not simply looking into a telescope. The limitations of technology mean that astronomers use statistics when filling in the blanks of satellite and telescopic images. Professors James Long and Rafael De Souza detailed the different uses of statistics in research for scientists studying places beyond Earth in a 2017 paper.
Long and De Souza wrote that algorithms and statistical modeling allow astronomers to evaluate the distances of stars from Earth based on image brightness. This article pointed to time series statistics that can determine brightness, distance, and potential relations to other bodies in space. Astronomers also use Bayesian computational models to estimate the growth of the galaxy and the evolution of individual bodies in space over time. Statistical analysis, in short, allows scientists to make educated guesses about the development of our universe.
Automotive Safety Testing
Motorists are able to assume the safety and security of their vehicles, thanks to the importance of statistics in research to automakers. Vehicle manufacturers in the United States not only use statistics to improve safety to protect their customers but also to comply with federal regulations. The National Highway Traffic Safety Administration (NHTSA) maintains a trove of safety statistics acquired over years of testing.
Statistical analysis is used in the automotive industry to create safety tests and evaluate their outcomes. NHTSA has worked for years to create safety tests that account for overlap and oblique crashes that fall outside of head-on collisions. The increased use of computers in passenger vehicles has led to data collection on cybersecurity threats to vehicle safety. The federal agency also reviews performance data from individual vehicle parts to identify defects that require recalls. Statistical analysts and engineers engage their curiosity to find new frontiers in data that can reduce vehicle crashes.
Athletic Performance Analytics
Sports science has become a global phenomenon with projected global revenues of $4.5 billion by 2024. Professional clubs around the world look to statistical analysis to improve on-field performance, off-field recovery, and financial performance.
A 2014 study in the International Journal of Sports Science & Coaching used statistics from German football to determine what actions are most connected to team results. This study concluded that goal efficiency exceeded all other measures by a statistically significant amount.
Mark Gellard’s study of the 2018 Australian Open for Tennis View Magazine found that a tennis player has a greater advantage when serving if points last four shots or less. Sports analytics show that the answer to, “How can statistics be used in a scientific study?”, can combine recreation with data analysis.
Integrating Statistics into your Organization
After learning about the myriad uses of statistics in scientific research, a natural question is how these processes can be incorporated into an organization. Michigan Tech trains future applied statistical analysts for careers in the public and private sectors. This training occurs through Michigan Tech’s Online Master of Science in Applied Statistics, where courses combine lessons in communications with the technical skills necessary to apply statistics in research settings. Michigan Tech graduates produce predictive models and engaging research methods that can solve problems across different industries. To learn more, request information.