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Every year, Australia spends over $800 million on medical research. That reflects a strong desire to improve the quality of life for Australians. However, there’s a concern among some researchers that this research is compromised by a lack of investment in a closely-related field. Biostatistics are very important because they make an accurate interpretation of research data possible. Researchers have stated that without a solid foundation in biostatistics, they have plenty of data but can simply be overwhelmed by it.

The scientific method is tied closely to statistics. Statistics are key in measuring and interpreting results from experiments. Without being able to properly calculate statistics, it becomes harder than ever to understand what’s actually happening in a given project. In medicine, this is especially problematic. Biostatistics help researchers to understand how diseases progress. They also make it possible to see how and why treatments for a given condition or disease work.

Biostatistics is particularly important for people who are studying the spread of disease. Any project about public health involves big sets of data. It’s crucial that the people working in that field can interpret data properly. Accurately kept statistics make it possible to see patterns in disease outbreaks. If statistics are interpreted incorrectly, it can have detrimental effects on whole populations.

Australia currently doesn’t have the same level of investment in biostatistics as countries like the UK and the US. There are university departments of biostatistics springing up there and in Western Europe. This infrastructure is giving those countries an edge. Recent advances in technology have made it easier to process large data sets. However, without educating, funding and support, Australia may fall behind in biostatistics. Some scientists worry that a lack of understanding in this area could make it hard to reproduce the results of experiments.

The methodology is key when it comes to science. Without a clear understanding of statistical methods, there’s a risk that knowledge can be lost. Some prominent researchers have criticized a “cargo-cult” approach to statistics. They see young scientists replicating behaviors without understanding why. With just a surface-level understanding of statistics, they risk deploying the wrong approach. With more knowledge, they would be able to do more and make more confident accurate interpretations. Better statistical knowledge can help medical scientists uncover solutions.