There are a lot of contributing factors involved in statistical analysis. If you find yourself feeling lost or confused, or are just looking for some tips on how to do it more efficiently, check out our top tips for successful statistical analysis.
- Your statistical methods should allow for data to answer scientific questions
Your experiments generate data to answer questions, that’s no secret. What separates the experts from the beginners is the contemplation of the uses of such data. You want to generate a technique based on the end goal rather than the data structure.
- You need variability for success
Within the discipline of statistics, variability is bound to make itself known- this can be a good or bad thing. A pro knows how to determine whether the variability at play is worth paying attention to or if it is what analysts refer to as “noise” which is a type of variability that can be considered irrelevant.
- Always plan ahead
Step back and consider all aspects of the data that is being collected and plan ahead for factors that could create errors. An experienced analyst is always looking at the whole and planning for every scenario.
- Maintain quality
Your processing needs to be approached with care. You want all of your work to be clean from the very start to keep things from getting muddy when you’re already well into the experiment.
- Know that what you’re dealing with is more than compiled data
Statistical analysis is all about data and the questions being answered. The software you are working with provides you with the tools to assist in the analyzation. It does not define them.
- Be smart and simplify
Keeping things as simple as possible is always the best idea. Make sure you only add complexity when it is needed, otherwise, stick to the “less is more” mentality.
- Assess your variability
Uncertainty is common as nearly all biological measurements exhibit some amount of variability when being repeated. One of the main purposes of statistical analysis is to help assess the uncertainty.
Follow these tips transform the way you approach statistical analysis. You will become more efficient, produce better results, and find exactly what can be done to make your work more successful.