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What do you do if you're a statistician making common mistakes and want to learn from them?

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As a statistician, you're well-versed in the language of data, but even the most experienced professionals can slip up. Common mistakes, such as misinterpreting p-values or overlooking sample size considerations, can skew results and conclusions. The key is to embrace these errors as learning opportunities. By acknowledging your mistakes and seeking to understand why they occurred, you can refine your methods and enhance your analytical skills. Continuous learning is essential in the field of statistics, and each mistake offers a unique chance to become a more proficient and insightful statistician.

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1 Acknowledge Errors

When you encounter an error in your statistical analysis, the first step is to acknowledge it. This can be challenging, as it requires admitting that your initial approach may have been flawed. However, recognizing and accepting your mistakes is crucial for growth. It allows you to take a step back and objectively evaluate what went wrong. By doing so, you're setting the stage for improvement and ensuring that future analyses are more accurate. Remember, the goal is not to be perfect but to be better informed and more skilled with each project.

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Tyriek W.

Data Professional | SQL | Python | R | Tableau | Power BI |
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Early in your career, admitting that you made mistakes can be scary. However, this is a necessary step in advancing your career. Not only should you tell your stakeholders that you made mistakes, you should also give them an idea of how you will rectify your errors. This will show that you are honest, proactive in resolving issues (even those that you contributed to), and are forward-thinking. Give a realistic timeframe for correcting the errors and be communicative as you are resolving the errors in the project.

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2 Seek Feedback

Once you've identified a mistake, don't hesitate to seek feedback from colleagues or mentors. Their experience and perspective can provide valuable insights into what went wrong and how to avoid similar errors in the future. Engaging in discussions about your work fosters a collaborative environment where knowledge is shared, and learning is mutual. Keep an open mind to the feedback you receive; it's not a critique of your abilities but rather a tool to help you grow as a statistician.

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Gemma Wood

CEO/Principal Statistician @ Numbers and People Synergy
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Spending time with the person fixing the error as they fix it so you can see what to do next time amd have opportunity to ask why the changes are needed if you don't understand. If not in the same office ask to share screen on a video call if they are comfortable with that

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3 Review Fundamentals

After acknowledging a mistake and seeking feedback, it's beneficial to review statistical fundamentals related to your error. Whether it's a concept like statistical significance or a technique like regression analysis, revisiting the basics can help clarify misunderstandings. This review process reinforces your knowledge foundation and ensures that you're applying statistical principles correctly. It's like re-reading a chapter in a book to fully grasp the story; sometimes, a second look can make all the difference.

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4 Update Methods

With a refreshed understanding of statistical concepts, it's time to update your methods. Incorporate the lessons learned from your mistakes into your analysis process. This might involve changing how you design experiments, collect data, or interpret results. Adapting your approach is not an admission of defeat but a sign of intellectual maturity and professional development. Embrace these changes as part of your evolution as a statistician, and watch as your analyses become more robust and reliable.

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5 Practice Diligently

Practice is essential in honing any skill, and statistics is no exception. Apply your updated methods to new projects and practice with datasets to build confidence in your revised approach. The more you work with data, the more intuitive the process becomes, and the less likely you are to repeat past mistakes. Each analysis is an opportunity to apply what you've learned and to further refine your techniques. Remember, practice doesn't just make perfect; it makes permanent.

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6 Reflect Regularly

Finally, make it a habit to reflect on your work regularly. This means taking the time to assess the outcomes of your analyses and considering how your approach contributed to these results. Reflection is a powerful tool for learning, as it allows you to connect the dots between theory and practice. By reflecting on what worked well and what didn't, you create a feedback loop that continually informs your work and guides your professional growth.

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7 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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What do you do if you're a statistician making common mistakes and want to learn from them?

1

2

3

4

5

6

7

1 Acknowledge Errors

2 Seek Feedback

3 Review Fundamentals

4 Update Methods

5 Practice Diligently

6 Reflect Regularly

7 Here’s what else to consider

Statistics

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What do you do if you're a statistician making common mistakes and want to learn from them?

1

2

3

4

5

6

7

1 Acknowledge Errors

2 Seek Feedback

3 Review Fundamentals

4 Update Methods

5 Practice Diligently

6 Reflect Regularly

7 Here’s what else to consider

Statistics

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