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Home OPINION

Significance of statistics in fighting corona-virus

OPINION by OPINION
May 23, 2021
in OPINION
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Coronavirus cases in country increases to 137, one more death on Tuesday
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Monthly trend of the positive cases and recoveries in the Union Territory of Jammu & Kashmir. The recoveries are showing an upward trend and on a positive note the cases are also declining.

BY: KHALID UL ISLAM

Biostatisticians and epidemiologists will play an important role in resolving the corona-virus epidemic and bringing our planet back to normal. These experts, who apply traditional statistical processes to human health problems, have advanced expertise that will be critical in the coming months as we battle the pandemic in the name of our common humanity.

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I constantly try to get the practical usefulness of statistics in solving real-world problems as someone who has taught statistics courses for more than two decades. Because once you recognize and regard something as having a high level of functional usefulness, you will begin to understand its value. In my attempts to understand the utility and significance of statistical skills, I’m constantly reminded of how important it is to have a thorough understanding of statistical processes.

The following are five basic ways that people who are familiar with statistics can help put the corona-virus to rest.

A basic understanding of inferential statistics:

People who appreciate inferential statistics will undoubtedly play a role in resolving the corona-virus crisis. Inferential statistics are a form of statistics that focus on the ability to extrapolate results from samples to larger populations. If you work for a pharmaceutical company and are trying to create a vaccine, you should have someone on your team who understands inferential statistics. This person will assess the results in your study (for example, the virus’ effectiveness in a group of 20 young Indian adults) and decide if they are likely to apply to the general population. In reality, this is a crucial part of the entire procedure.

A basic understanding of the concept of effect size:

That’s exactly as it says on the tin. It encompasses a wide range of statistics that describe the magnitude of your impact in your sample data. If you’re part of a vaccine development team and have proof that the trial vaccine’s results are in fact minor, and just slightly more successful than placebos, you have crucial knowledge to help the team’s future productivity.

Skills related to SPSS or R or another cutting-edge statistical software package:

You’ll most likely be introduced to and trained in either SPSS or R during your statistics education, since these are the most top-tier, cutting-edge statistical software packages. Not all can use these programmes, but if you can get halfway literate in one or both of them, you’ll have crazy skills that others can depend on. You’ll be able to easily generate descriptive reports on variables, statistics that look at relationships between variables, statistics that indicate whether any results are likely to be generalized to larger populations, and more.

An understanding of statistical power:

Statistical power refers to the ability to detect a statistically significant effect using a specific methodological design. You will help shape this type of research from the ground up if you know how to estimate statistical capacity, which includes how to manipulate the key independent variables, how many participants to include in the study from the start, and so on. Statistical strength is, well, powerful. Understanding it can give you a big advantage when it comes to designing good research that can address important questions.

An understanding of potential errors in hypothesis testing:

Hypothesis testing, or determining whether a finding in a study would possibly generalise to a larger population of interest, is now a standard part of statistical procedures. A good statistician knows that there are possible errors in the method, such as the error of seeing a finding as “significant” when you are actually incorrect, or the error of not seeing a finding as significant when it should have been. Understanding these principles is a hallmark of good research, and it is critical in the development of successful medical procedures.

Bottom Line:

When you hear a college student complain about a statistics class, smile and explain these five ways that statistics expertise can help us solve the global crisis we are facing today.

The writer is a Research Scholar (STATISTICS)  Email Id: [email protected]

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