Is statistics important? Statistics is arguably among the most dreaded concepts, with many students wondering how it is relevant in their lives after school. However, statistics, especially in today’s data-driven world, has proven to be an indispensable tool, helping organizations in all industries to advance. Among the most apparent fields that statistics essence has proved to be paramount is research.
Every research stage is essential, driving towards conclusive findings that determine the next step. In simple terms, statistics in research address the three Cs. The 3Cs are credibility, communication, and convergence. Here is a quick look at the three Cs showing why statistics are important in research.
Credibility
How did you come up with your hypothesis? Can you support it without statistical tests? There is no objective way of supporting your research question without statistically testing the data. That’s where a load of evidence lies, and without the statistical tests, you would be relying on more unknowns, leading to open-ended conclusions and more questions that you had as you started the research. The tests provide a solid foundation, a way to trust what the data is relaying, and making sense of the voluminous pool you have to shape your research and lead to conclusive and reliable answers.
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The statistical tests also account for errors. Raw data is messy, and there is enough room for errors and uncertainties that requires acknowledgment to deliver credible findings. Statistical approach aids in spotting uncertainties and limitations in data. This ensures that you fairly treat the limitations and draw reliable conclusions. From the experimental design, research methods employed to database structure, statistics lead the thinking of the hypotheses to a more dependable path. Through the tests, add an air of credibility to your research.
Convergence
Where does it all come together? What’s true, and what gives you the confidence to draw such a conclusion? Converging the data relationships, laws, and principles lets you concludeconcerning how nature operates. With multivariate statistical questions, you get to model an approach that lets you evaluate the hypotheses from various angles. Such convergence is critical, a statistic contribution that heightens the researcher’s confidence in the final results.
Communication
Communication might seem straightforward, but can you imagine how it would go without statistics? The findings were “greater than” “almost matches.” That’s quite relative, noting that what that means to one researcher isn’t the same as others think. Communicating your research in numbers is a lot more clear and powerful, a consideration that is only made possible by statistics. Utilizing statistical tests to interpret the dataset and drawing fair and objective conclusions make it easier to understand and communicate what the data means. With statistics, you can confidently proceed and communicate what the data says in a way that everyone understands, not just researchers.
The Bottom Line
Statistics help us to present the findings in a definite form. Utilizing certain methods, you can formulate, test hypotheses, and develop theories to guide your research. As you endeavor to furnish your research requirement, you need the data and reliable means to analyze, interpret, and present it understandably, concerns that statistics address. The best part is that you can seek professional help if you are struggling to ensure that you are on track. As you work on your research, here is a link for all stats students in need of data, statistical tests, and help to understand what it is communicating to draw credible conclusions. With professional guidance, your research won’t lead to more questions but dependable findings that can be utilized to formulate policies, inform manufacturers, politicians, and consumers, among other users.
