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How can you ensure your lab uses appropriate statistical methods?

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Statistical methods are essential tools for analyzing data and drawing conclusions in any scientific field. However, choosing and applying the right methods can be challenging, especially in complex and interdisciplinary research. As a lab manager, you have the responsibility to ensure that your lab uses appropriate statistical methods that are valid, reliable, and ethical. Here are some tips to help you achieve this goal.

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Dennis Odoi

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Herbert Jank

It is not easy to be a pioneer - but oh, it is fascinating! I would not trade one moment, even the worst moment
ABUBAKAR Muhammad Fandirma

Laboratory Scientist | Laboratory Techniques, Equipment

1 Know your data

Before you select any statistical method, you need to understand the nature and characteristics of your data. For example, you should know the type, scale, distribution, and variability of your data, as well as the sources of error and bias. You should also consider the research question, hypothesis, and design that guide your analysis. Knowing your data will help you choose the most suitable methods for describing, summarizing, visualizing, comparing, and testing your data.

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Dennis Odoi

Biomedical Scientist || Health Writer || Public Health Enthusiast || Reproductive Health Advocate || Entrepreneur || Certified Google Digital Marketer
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Knowing your data is critical for ensuring your lab uses appropriate statistical methods. Understanding the characteristics, distribution, and potential biases within the dataset informs the selection of statistical tests and analyses. This knowledge ensures that the chosen methods are suitable for the data structure and research objectives, enhancing the validity and reliability of study outcomes. By tailoring statistical approaches to the specific nature of the data, laboratories can draw more accurate conclusions and contribute to robust scientific research.

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Arslan Arshad

Medical Laboratory Professional | Global Health Security | Quality Assurance | Biorisk Management | Bioethics | One Health | Planetary Health
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Understand data type, scale, distribution, and variability. Consider sources of error and bias. Align with research question, hypothesis, and design. Choose appropriate methods for describing, summarizing, visualizing, comparing, and testing data.

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2 Learn the basics

You don't need to be a statistician to use statistical methods, but you do need to have some basic knowledge and skills. You should be familiar with the concepts and terminology of statistics, such as mean, median, mode, standard deviation, confidence interval, p-value, significance level, effect size, and so on. You should also be able to perform simple calculations and interpret the results of common methods, such as t-tests, ANOVA, correlation, regression, and chi-square. You can learn the basics from books, online courses, workshops, or tutorials.

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Herbert Jank

It is not easy to be a pioneer - but oh, it is fascinating! I would not trade one moment, even the worst moment
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For appropriate quality publications it is crucial to know the basics of statistics. Most used statistic programs are "stupid", they compute everything as long as you give them enough values to work with, even if the outcome is meaningless e.g. due to the short sample size. A standard deviation of 3 values might be mathematically right but does not have any worth. If you do not know the basics, how can you input errors?

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Arslan Arshad

Medical Laboratory Professional | Global Health Security | Quality Assurance | Biorisk Management | Bioethics | One Health | Planetary Health
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Gain familiarity with statistical concepts like mean, median, standard deviation, confidence interval, p-value, significance level, effect size. Learn common methods like t-tests, ANOVA, correlation, regression, chi-square. Utilize resources like books, online courses, workshops, tutorials.

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3 Use reliable software

There are many software programs and packages that can help you perform statistical analysis, such as Excel, SPSS, R, SAS, and MATLAB. However, not all software are equally reliable and user-friendly. You should choose software that is widely used and accepted in your field, that has good documentation and support, that is updated and compatible with your system, and that has the features and functions you need. You should also check the accuracy and validity of the software output by comparing it with other sources or methods.

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Herbert Jank

It is not easy to be a pioneer - but oh, it is fascinating! I would not trade one moment, even the worst moment
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What software you choose depends on your background knowledge and computer skills. Programs like SPSS are easy to handle if you know what you do and mind the informations, the program gives you to avoid useless calculations. If you use Excel or Mathematica might not be as user friendly, they want more comittement of the user.

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Arslan Arshad

Medical Laboratory Professional | Global Health Security | Quality Assurance | Biorisk Management | Bioethics | One Health | Planetary Health
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Choose reliable statistical analysis software like Excel, SPSS, R, SAS, or MATLAB. Select widely used and accepted software with good documentation, support, and compatibility. Ensure features meet your needs. Validate output by comparing with other sources or methods.

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4 Seek expert advice

Even if you have some statistical knowledge and skills, you may encounter situations where you need more guidance or assistance. For example, you may have to deal with complex or novel data, methods, or models, or you may have to report or publish your results in a specific format or style. In these cases, you should seek expert advice from statisticians, consultants, mentors, or colleagues who have more experience and expertise in the relevant area. You should also be open to feedback and suggestions from your peers and reviewers.

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Arslan Arshad

Medical Laboratory Professional | Global Health Security | Quality Assurance | Biorisk Management | Bioethics | One Health | Planetary Health
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Seek expert advice from statisticians, consultants, mentors, or experienced colleagues for complex or novel data, methods, or reporting formats. Be open to feedback and suggestions from peers and reviewers to ensure accuracy and validity in statistical analysis.

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5 Follow ethical principles

Using appropriate statistical methods is not only a matter of technical competence, but also a matter of ethical conduct. You should follow the ethical principles of honesty, integrity, transparency, and accountability when you use statistical methods. For example, you should not manipulate, fabricate, or falsify your data or results, you should not misuse or misinterpret statistical terms or tests, you should not cherry-pick or ignore data or results that do not support your hypothesis, and you should not plagiarize or infringe on the intellectual property of others. You should also acknowledge and cite the sources and methods you use, and disclose any limitations or assumptions of your analysis.

Using appropriate statistical methods can enhance the quality and credibility of your research and help you communicate your findings effectively. As a lab manager, you can ensure that your lab uses appropriate statistical methods by following these tips and by fostering a culture of statistical literacy and ethics in your lab.

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Arslan Arshad

Medical Laboratory Professional | Global Health Security | Quality Assurance | Biorisk Management | Bioethics | One Health | Planetary Health
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Follow ethical principles of honesty, integrity, transparency, and accountability. Avoid data manipulation, fabrication, or falsification. Use statistical terms and tests accurately. Avoid cherry-picking or ignoring data that doesn't support your hypothesis. Acknowledge and cite sources and methods, disclose limitations or assumptions. Foster a culture of statistical literacy and ethics in the lab.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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ABUBAKAR Muhammad Fandirma

Laboratory Scientist | Laboratory Techniques, Equipment
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Collect data from a representative and sufficiently large sample. Choose the right statistical test for your data based on the type of variables, the number of groups, and the assumptions of the test. For example, if you have continuous data that are normally distributed, you can use parametric tests such as t-test, ANOVA, or regression.

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How can you ensure your lab uses appropriate statistical methods?

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1 Know your data

2 Learn the basics

3 Use reliable software

4 Seek expert advice

5 Follow ethical principles

6 Here’s what else to consider

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